O le malo o Indonesia o loʻo faʻatutuina le vaetamaina o le 2.1 miliona iunite o taʻavale eletise uili e lua ma le 2,200 iunite o uili uili e fa i le 2025 e ala i le Faʻatonutonuina a le Peresetene a le Malo Tele o Indonesia i le numera 22 i le 2017 e uiga i le National Energy General Plan. I le 2019, na faʻatuina ai e le Malo o Indonesia le Peresetene Faʻatonuga Nu. I le 2018, o le vaetamaina o uila eletise e lua uili na oʻo atu i le 0.14% o le malo faʻatulagaina mo le 2025. O le mea lea, o le vaetamaina o le Eletise uila afi (EM) tekonolosi tatau foi ona mafaufau i le tele o mea e faʻamanuiaina ai. O lenei suʻesuʻega e atiaʻe ai se faʻaaoga le eletise e le o ni amioga faʻaaoga eletise. O mea taua e aofia ai sociodemographic, tupe, tekonolosi, ma macrolevel. O le suʻesuʻega i luga ole laiga na aofia ai le 1,223 tagata na tali ane. Logistic regression e faʻaaogaina e maua ai le aoga ma le ono aoga o le faʻamoemoe e talia EM i Indonesia. Faʻatele o le tufatufaina i luga o ala o faasalalauga lautele, tulaga o le siʻosiʻomaga malamalama, faʻatauina o tau, tausiga tau, maualuga saosaoa, maa molia taimi, maua ai o le faʻatupeina o nofoaga faʻatulagaina galuega i le galuega, mauaina o le fale paoa faʻavae - molia 'auʻaunaga, faʻatau faatosina faiga faʻavae, ma le totogiina o tau paʻu o faʻamalosiʻau faiga faʻavae e matua aafia ai le faʻamoemoe e faʻaaogaina eletise taʻavale. Ua faʻaalia ai foi o le avanoa mo tagata Initonesia e faʻaaogaina uila afi eletise e oʻo atu i le 82.90%. O le iloaina o le vaetamaina o uila eletise i Indonesia e manaʻomia ai sauniuniga sauniuniga ma tau e mafai ona taliaina e tagata faʻatau. Ma le mea mulimuli, o iʻuga o lenei suʻesuʻega o loʻo tuʻuina mai ai ni fautuaga mo le malo ma pisinisi e faʻatelevaveina le faʻaaogaina o uila afi i Indonesia.

FAATOMUAGA

O le vaega o le tamaoaiga i Indonesia (felauaiga, gaosiga o le eletise, ma aiga) tele lava faʻaaogaina fualaʻau afi. O nisi o aʻafiaga le lelei o le faʻalagolago tele i suauʻu o loʻo avea ma faʻateleina o vaegatupe mo le suauʻu fesoasoani, faʻafitauli tau malosiaga faʻamalosia, ma tulaga maualuga o le CO2 emissions. O feʻaveaʻiga o se vaega taua e fesoasoani i le maualuga o le CO2 i le ea ona o le tele o faʻaoga o taʻavale afi. O lenei suʻesuʻega e taulaʻi i uila afi aua o Indonesia, o se atunuʻu atiaʻe, e tele atu uila afi nai lo taʻavale. O le numera o uila afi i Initonesia na oʻo atu i le 120,101,047 iunite i le 2018 [1] ma le faʻatau atu o uila afi e oʻo atu i le 6,487,460 iunite i le 2019 [2]. Suia le feʻaveaʻiga vaega i isi malosiʻaga malosiʻaga mafai faʻaititia maualuga CO2 tulaga. O le fofo talafeagai mo lenei faʻafitauli o le faʻatinoina o lanumeamata logistics ala i le ofi o eletise taʻavale i Indonesia pei o hybrid eletise taʻavale, plug-in hybrid eletise taʻavale, ma maa eletise taʻavale [3]. Eletise eletise afi tekonolosi fou ma maa tekonolosi fou mafai ona maua ai fofo fofo e lelei siʻosiʻomaga, malosi lelei, ma maualalo faʻagaioiga ma tausiga tau [4]. O taʻavale eletise e tele na talanoaina e atunuʻu ole lalolagi. I le lalolagi eletise pisinisi taʻavale eletise, sa i ai se taua faʻatau tuputupu aʻe mo uili-uila uili uila afi na oʻo atu i le 58% poʻo le latalata 1.2 miliona iunite mai le 2016 i le 2017. O lenei faʻatau tuputupu ae faʻailoa mai se lelei tali mai atunuʻu i le lalolagi e uiga i le atinaʻeina o le eletise tekonolosi uila afi lea e iai se aso, uila afi eletise e faamoemoe e suia ai afi-afi afi. O le suʻesuʻega o le uila afi eletise (EM) o loʻo aofia ai le Fuafua Fou o uila afi eletise (NDEM) ma le liua uila afi eletise (CEM). O le ituaiga muamua, o le New Design of Electric Motor uila (NDEM), o se taʻavale na fuafuaina e le kamupani o loʻo faʻaaogaina tekinolosi eletise mo ana gaioiga. O nisi atunuu i le lalolagi e pei o Ausetalia, Siamani, Egelagi, Farani, Iapani, Taiwan, Korea i Saute, ma Saina ua uma ona faaaogaina uila eletise e fai ma sui oloa mo afi afi uila afi faatosina [5]. Tasi le ituaiga o uila afi eletise o le Zero Motorcytical lea e gaosi ai taʻaloga uila afi eletise [6]. PT. O le Gesits Technologies Indo na ia gaosia foi uila afi eletise uili e lua i lalo o le igoa Gesits. O le ituaiga lona lua o le CEM. O le uila afi eletise ua liua o se uila afi-fafieina o le afi ma vaega afi suia i Lithium Ferro Phosphate (LFP) maa pusa o se malosiaga punaoa. E ui lava o le tele o atunuʻu gaosia uila eletise, e leai se tasi na faia le taʻavale e ala i le faʻaaogaina o metotia faʻaliliuga. Faʻaliliuga e mafai ona faia i luga o se uila uili e lua-uili ua le toe faʻaaogaina e ona tagata faʻaoga. Universitas Sebelas Maret o se paionia i le gaosiga o CEM ma tekinolosi faʻamaonia o Lithium-Ion maa e mafai ona suia fossil suauʻu malosiaga faʻavae luga masani uila afi. E faʻaaogaina e le CEM le tekonolosi LFP, o lenei maa e le pa pe a tupu se taamilosaga puʻupuʻu. E le gata i lea, o le maa LFP e umi lona ola faʻaaoga e oʻo atu i le 3000 faʻaaogaina taʻamilosaga ma umi atu nai lo pisinisi EM o loʻo i ai nei (pei o le Lithium-Ion Battery ma LiPo Battery). E mafai e le CEM ona faimalaga i le 55 km / charge ma faʻateleina le saoasaoa e oʻo atu i le 70 km / itula [7]. Jodinesa, ma isi. [8] suʻesuʻe le maketi faʻasoa o uila afi eletise mafai ona suia i Surakarta, Indonesia ma mafua ai na tali lelei tagata o Surakarta i le CEM. Mai le faʻamatalaga i luga atu, e mafai ona iloa ai o le avanoa mo uila eletise e tele. E tele suʻesuʻega i tulaga faʻatatau e fesoʻotaʻi i taʻavale eletise ma maʻa ua atiaeina, e pei o le Lithium Ion maa tulaga masani e Sutopo et al. [9], o le faʻatonutonuina o le faʻatonutonuina o le maa e Rahmawatie et al. [10], ma eletise taʻavale faʻatonuina tulaga e Sutopo et al. [11]. O le faifai lemu o le faʻaaogaina o taʻavale eletise i Indonesia ua unaʻia ai le malo e faʻamatuʻu mai ni tulafono mo le atinaʻeina o pisinisi taʻavale ma fuafua e faʻatutu le vaetamaina o le 2.1 miliona iunite o uila afi ma 2,200 iunite o taʻavale eletise i le 2025. E le gata i lea, o le malo O loʻo faʻamoemoe foʻi Indonesia ia mafai ona gaosia ni taʻavale eletise 2,200 poʻo ni hybrid o loʻo taʻua i le Faʻatonutonu a le Peresetene a le Malo Tele o Indonesia, numera 22 o le 2017 e faʻatatau ile National Energy General Plan. O lenei tulafono faʻatonutonu na faʻaaogaina e atunuʻu eseʻese e pei o Farani, Egelagi, Nouei, ma Initia. O le Matagaluega o Malosiaga ma Minerale Punaʻoa ua faʻatulagaina se faʻamoemoega e amata i le 2040, faʻatauina o Totonu afi afi afi (ICEV) e faʻasaina ma tagata lautele e talosagaina le faʻaaogaina eletise-faʻavae taavale [12]. I le 2019 na tuuina mai ai e le Malo o Indonesia le tulafono a le Peresetene Nu. O lenei taumafaiga o se sitepu e foʻia ai ni faʻafitauli se lua, e aofia ai le faʻaleaogaina o le suauʻu o suauʻu ma le faʻaleagaina o le ea. E tusa ai ma le filogia o le ea, ua tuutoina Indonesia e tuuitiitia le 29% o kasa oona mai i le 2030 ona o le Paris Climate Change Conference na faia i le 2015. I le 2018, o le tuʻuina i totonu o taavale eletise uili e lua uʻamea na oʻo atu i le 0.14% o le faamoemoe a le malo. 2025, ae mo le fa eletise uʻamea na oʻo atu i le 45%. Ia Tesema 2017, sa i ai le sili atu ma le 1,300 faitele uila afi nofoaga faʻatumuina avanoa i le atunuʻu atoa i 24 taulaga, lea 71% (924 toe faʻatumu nofoaga) o loʻo i DKI Jakarta [13]. Tele atunuʻu ua suʻesuʻe e uiga i le faʻaaogaina o taʻavale eletise, ae i Indonesia, e leʻi faia muamua suʻesuʻega a le atunuʻu. E tele ituaiga o suʻesuʻega i nisi o atunuʻu na latou faia suʻesuʻega i le taliaina o tekonolosi fou e ala i le faʻaaogaina o ni metotia e pei o le tele o laina faʻafouina e iloa ai le faʻaaogaina o le eletise e faʻaaoga i Malaysia [14], Structural Equation Modeling (SEM) ia iloa vaetama o papala eletise uila 'pa i Tianjin, Saina [15], exploratory factor analysis & multivariate regression model ia iloa papupuni i totonu o taʻavale afi eletise i le United Kingdom [16], ma logistic regression e iloa ai mea taua e aʻafia ai le aveina o uila eletise i Beijing, Saina [17]. O le mafuaʻaga o lenei suʻesuʻega o le atiaʻeina o se vaetamaina faʻataʻitaʻiga mo uila afi eletise i Indonesia, ia maua ai mea taua e aʻafia ai le faʻamoemoe o le faʻaaogaina o uila eletise i Initonesia, ma ia fuafuaina le aoga avanoa mo le vaetamaina o uila eletise i Indonesia. O le faʻataʻitaʻiga o mea taua e taua e iloa ai poʻo a mea taua e faʻatosinaina ai le faʻamoemoe e faʻaaogaina uila afi eletise i Indonesia. O nei mea taua e mafai ona faʻaaogaina o se faʻasino e fausia ai ni tulafono talafeagai e faʻatele ai le taliaina o uila eletise. Nei taua mea taua o se ata o le sili lelei tulaga manaʻomia e ono ono eletise uila afi i Indonesia. O nisi matagaluega i Indonesia e fesoʻotaʻi ma le faʻatulagaina o aiaiga faʻatatau i taʻavale eletise o le Matagaluega o Alamanuia o loʻo tagofia tulafono tau lafoga o taʻavale e faʻavae i luga o ana mea e faʻatatau tuʻusaʻo ma gaosi eletise, o le Matagaluega o Felaʻuaiga e faʻatautaia le faʻataʻitaʻiga talafeagai o taʻavale eletise o le a auala i luga o le alatele e pei o le faʻataʻitaʻiga o maa ma isi tulaga, faʻapea foi ma le Matagaluega o Malosiaga ma Malosiaga o loʻo mafai ona faʻatulagaina le totogiina o le eletise mo le faʻatupeina o le eletise i le fausiaina o pisinisi eletise. E faʻaosofia foi le faʻaosofia o le eletise fou i le fausiaina o pisinisi fou i totonu o le kamupani sapalai e aofia ai ma tekinolosi ma amataga mai le au atinaʻe, kamupani e gaosia oloa, kamupani gaosi oloa, ma tagata e tufatufaina atu oloa tau eletise / auaunaga ma latou mea e maua mai i le maketi [24]. E mafai foi e tagata fai pisinisi uila afi eletise mafai ona atiaʻe tekonolosi ma maketiina i le iloiloina o mea taua ia mafai ona lagolagoina le faʻatauaina o uila eletise nai lo le masani ai uila afi i Indonesia. Ordinal logistic regression na faʻaaogaina e maua ai le gaioiga ma le ono aoga o le faʻamoemoe e faʻaaogaina uila eletise i Indonesia e faʻaaoga ai le SPSS 25 polokalama. Logistic regression poʻo logit regression o se auala e faia ai valoʻaga faʻataʻitaʻiga. Lologa faʻafouina i fuainumera na faʻaaogaina e valoia ai le ono tupu o se mea na tupu e ala i le faʻatusatusaina o faʻamatalaga i le logit curve logistic function. Lenei metotia o se lautele laina faʻataʻitaʻiga mo binomial regression [18]. Logistic regression na faʻaaogaina e valoia le taliaina o initaneti ma telefoni feaveaʻi vaetamaina [19], vaʻaia le taliaina o ata voltaic tekinolosi vaetamaina i Netherlands [20], vavalo le taliaina o telemonitoring tekonolosi tekonolosi mo le soifua maloloina [21], ma ia maua fafo faʻalavelave faʻafuaseʻi e afaina ai le faʻaiuga e faʻaoga tautua ao [22]. Utami et al. [23] o le na faia muamua suʻesuʻega i le aufaʻatau manatu o le eletise taʻavale i Surakarta, maua o faʻatau tau, faʻataʻitaʻiga, taʻavale faʻaleleia, ma atinaʻe sauniuni o le sili atu pa pupuni mo tagata faʻaaogaina eletise taʻavale. METHOD O faʻamatalaga na aoina mai i lenei suʻesuʻega o faʻamatalaga muamua na maua mai i suʻesuʻega i luga o le upega tafailagi e sailia ai avanoa ma mea taua e faʻatosinaina ai le manatu e faʻaaogaina uila afi eletise i Indonesia. Fesili ma Fesili O le suesuega i luga ole laiga na tufatufaina atu i le 1,223 tali atu i itumalo e valu i Indonesia e suʻesuʻe ai itu taua na aafia ai le manatu e faaaoga uila afi eletise i Indonesia. O nei itumalo filifilia na sili atu i le 80% o faʻatauga uila afi i Initonesia [2]: West Java, East Java, Jakarta, Central Java, North Sumatra, West Sumatra, Yogyakarta, South Sulawesi, South Sumatra, ma Bali. O mea na suʻesuʻeina o loʻo faʻaalia i le Laulau 1. O le poto lautele e uiga i uila afi eletise na maua i le amataga o le fesili e ala i le faʻaaogaina o le video e aloese ai mai le le femalamalamaaʻi. O le fesili na vaevaeina i vaega e lima: vaega e siakiina, vaega o le vafealoaʻi, vaega o mea tau tupe, vaega o tekonolosi, ma le vaega o le tulaga maualuga. O le fesili na tuʻuina mai i le Likert scale o le 1 i le 5, lea e 1 mo le matua le malie, 2 mo le le malie, 3 mo le masalosalo, 4 mo le malie, ma le 5 mo le matua malilie. Fuafuaina o le laʻititi faʻataʻitaʻiga lapoʻa e faʻasino i le [25], na taua ai o le maitauina o suʻesuʻega ma le tele o le aofaʻi o tagata e aofia ai le toe faʻatulagaina o le logistic, e manaʻomia le laʻititi o le aofaʻi o le 500 e maua ai faʻamaumauga e fai ma sui. O faʻataʻitaʻiga o fualaʻau male vaega o loʻo fai ai faʻataʻitaʻiga o loʻo faʻaaogaina i lenei suʻesuʻega talu ai o le faitau aofai o tagata e faʻaaogaina uila afi i Indonesia e tele tele. E le gata i lea, o faʻamoemoega faʻataʻitaʻi o loʻo faʻaaogaina e fuafua ai faʻataʻitaʻiga faʻavae i luga o nisi faʻavae [26]. O suʻesuʻega i luga ole laiga e faia e ala ile Facebook Ads. O tagata agavaʻa e tali mai o tagata e ≥ 17 tausaga le matutua, o loʻo iai le SIM C, ose tasi o tagata e faia faʻaiuga e sui pe faʻatau se uila afi, ma o loʻo nonofo i se tasi o itumalo i le Laulau 1. Theoretical Framework She et al. [15] ma Habich-Sobiegalla et al. [28] faʻaaoga faʻavae mo le faʻavasegaina faʻavasegaina o mea e unaʻia pe faʻalavelaveina ai le faʻaaogaina o le eletise taʻavale e tagata faʻatau. Na matou fetuʻunaʻia nei faʻavae e ala i le toe faʻaleleia e faʻavae i luga o la matou suʻesuʻega o le eletise uila uila i luga o le tagata faʻatau taliaina o uila eletise. Ua matou vaʻaia i le Laulau 1.Tulau 1. Faʻamatalaga ma Faʻamatalaga o Mea Taua ma Uiga Taua Fact Atrtibute Ref. SD1 Tulaga faʻaipoipoga [27], [28] SD2 Vaitau SD3 Itupa Tulaga SD4 Aʻoga mulimuli SD5 Galuega Sociodemographic SD6 Masina masina taumafaina SD7 Masina masina tupemaua SD8 Aofai o puleʻaga uila afi SD9 Faʻatele o le fefaʻasoaaʻi luga o agafesoʻotaʻi SD10 Tele o 'upega tafaʻilagi fesoʻotaʻiga SD11 Faʻalauiloa siʻosiʻomaga Siosiomaga FI1 Faʻatau faʻatau [29] FI2 Paʻu tau [30] FI3 Totogiina tau [31] FI4 Tau tausiga tausiga [32] Tekinolosi TE1 Mileage agavaʻa [33] TE2 Malosiaga [33] TE3 Taimi faʻatonuina [33] TE4 Saogalemu [34] TE5 O le ola o le maa [35] Macro-level ML1 Faʻatonuga avanoa nofoaga i nofoaga faitele [36] ML2 Faʻasaʻoga nofoaga avanoa i le galuega [15] ML3 Faʻasaʻoga nofoaga avanoa i le fale [37] ML4 Nofoaga avanoa avanoa [38] ML5 Faʻatauga faʻamalosia aiaiga [15] ML6 Faʻaletausaga lafoga lafoga faiga faʻavae [15] ML7 Totogiina tau faʻaitiitiga faʻavae [15] Faʻatagaina faamoemoe IP Faamoemoega e faʻaaoga [15] Sociodemographic Factor Sociodemographic factor o uiga taua a le tagata lava ia e aʻafia ai amioga a le tagata i le faiga o filifiliga. Failarius ma isi. [28] taua i luga o la latou vaetamaina faʻataʻitaʻiga o tausaga, itupa, tulaga faʻaipoipoga, aʻoaʻoga, tupe maua, galuega, ma le umiaina o taʻavale o ni mea taua e afaina ai le faʻaaogaina o le eletise. HabichSoebigalla et al faʻamalamalamaina fesoʻotaʻiga lautele fesoʻotaʻiga pei o le numera o uila afi umiaina, taimi masani o faʻasoa luga o ala o agafesoʻotaʻi, ma le tele o luga o le upega tafaʻilagi fesoʻotaʻiga avea ma mafuaʻaga mafuaʻaga mo le faʻaaogaina o taʻavale eletise [28]. Failarius ma isi. [27] ma HabichSobiegalla et al. [28] faʻapea foi mafaufauina o le siʻosiʻomaga malamalama e aofia ai i agafesoʻotaʻi itu. Tulaga Faʻatupe Tupe faʻatau o le tau muamua o se uila afi eletise e aunoa ma se faʻatau fesoasoani. Sierzchula et al. [29] fai mai o le maualuga o le faʻatauina o taʻavale eletise mafua mai ile maualuga maualuga paoa. O le tau o le tau o le tau e sui ai le maa pe a fai ua uma le ola maa tuai. Krause et al. suʻesuʻe o le tau o le maa o le paʻu tautupe mo se tasi na te faʻaaogaina se eletise eletise [30]. O le tau o le tau o le eletise e faʻaola ai le uila afi eletise pe a faʻatusatusa i le tau o le penisini [31]. Tausiga o tau o tau masani mo le tausiga o uila afi eletise, ae le o le toe faaleleia ona o se faʻalavelave na aʻafia ai le faʻaaogaina o taʻavale eletise [32]. Tekinolosi Malosiaga Mileage gafatia o le mamao mamao mamao ina ua maeʻa ua maeʻa molia le uila afi uila afi. Zhang et al. [33] fai mai o taʻavale faʻatinoina e faʻasino i tagata faʻatau iloiloga i luga o eletise taʻavale aofia ai mileage gafatia, paoa, molia taimi, saogalemu, ma maa ola. Ole malosi ole televave ole uila afi. O le taimi e faʻatonu ai o le taimi atoa e totogi atoa ai le uila afi. Saogalēmū lagona peʻa tiʻetiʻe i se uila afi eletise e fesoʻotaʻi ma le leo (dB) o mea taua na faʻaalia e Sovacool et al. [34] ia avea ma mea e afaina ai le malamalama o tagata faʻatau ile taʻavale eletise. Graham-Rowe et al. [35] fai mai o le ola maa ua manatu e faʻaleagaina. Macro-level Factor Infrastructure o le faʻatonuina o avanoa nofoaga o se mea e le mafai ona 'alofia mo eletise uila afi adopter. O le totogiina o avanoa i nofoaga faitele e taua tele e lagolago ai le faʻaaogaina o taʻavale eletise [36]. Totogiina avanoa i le galuega [15] ma le faʻatupeina avanoa i le fale [37] manaʻomia foi e tagata faʻatau e faʻataunuʻu le maa o la latou taʻavale. Krupa et al. [38] fai mai o le mauaina o tautua nofoaga mo masani tausiga ma le faʻaleagaina o afaina ai le taliaina o le eletise taʻavale. She et al. [15] fautuaina nisi faʻamalosia tagata lautele o loʻo manaʻomia tele e tagata faʻatau i Tianjin pei o le tuʻuina atu o fesoasoani mo le faʻatauina o uila eletise, paʻu lafoga faʻaletausaga mo uila eletise, ma le totogiina o paʻu tau paʻu pe a manaʻomia e tagata faʻatau le uila afi i nofoaga faitele [15]. Ordinal Logistic Regression O le Ordinal logistic regression o se tasi o metotia faʻafuainumera e faʻamatalaina ai le sootaga i le va o le faʻalagolago fesuiaʻiga ma le tasi pe sili atu tutoʻatasi fesuiaʻiga, lea o le faalagolago fesuiaʻiga e sili atu i le 2 vasega ma le fuaina fua o le tulaga pe faʻasolosolo [39]. Faʻatusatusaga 1 o se faʻataʻitaʻiga mo le faʻasolosolo faʻasolosolo faʻafouina ma le Faʻatusatusaga 2 faʻaalia le g gaioiga g (x) e pei o logit equation. eegxgx P x () () 1 () + = (1)  = = + mkjk Xik gx 1 0 ()   (2) IʻUGA MA TALANOAGA O le fesili na tufatufaina i luga ole laiga ia Mati - Aperila, 2020, e ala ile Facebook Ads totogi e ala i le faʻatulagaina o nofoaga faʻavasega: West Java, East Java, Jakarta, Central Java, North Sumatra, West Sumatra, Yogyakarta, South Sulawesi, South Sumatra, ma Bali na oʻo atu i le 21,628 tagata faʻaoga. Ole aofaʻi o tali na taunuʻu mai 1,443 tali, ae naʻo le 1,223 tali na agavaʻa mo faʻagaioiga o faʻamatalaga. O le siata 2 o loʻo faʻaalia ai le faitau aofaʻi o tagata na faʻaali. Faʻamatalaga Faʻamaumauga Lisi 3 faʻaalia faʻamatala fuainumera mo aofaʻi aofaʻi. Totogiina tau paʻu, paʻu lafoga faʻaletausaga, ma faʻatau tau fesoasoani e sili atu le averesi i isi mea. Lenei faʻaalia ai o le toʻatele o tagata tali mai latou te manatu o loʻo iai se aiaiga faʻavae na tuʻuina atu e le malo na mafai ona faʻamalosia latou e faʻaaogaina uila afi eletise. I mea tau tupe, faʻatauga ma tau paʻu e maualalo le averesi i isi mea. Lenei faʻaalia ai o le tau faʻatau o se uila afi eletise ma maa tau e le talafeagai ma le paketi a le tele o tali. O le tele o tagata na teteʻe na latou manatu o le tau ole uila afi eletise e matua taugata lava pe a faatusatusa i le tau o le uila afi masani. O le suia o le tau o le maa i le taʻi tolu tausaga e oʻo atu i le 5,000,000 e matua taugata tele foʻi i le toʻatele o tagata tali atu, o le tau o le faʻatau ma le tau o le maa o se pa pupuni lea mo Indonesia e faʻaaoga uila afi. O le ola o le maa, paoa, taimi faʻatonuina e maualalo togi togi i faʻamatalaga faʻamaumauga ae o le averesi togi mo nei mea taua e tolu sili atu nai lo le 4. O le taimi e faʻaalu ai le taimi e tolu itula na umi tele mo le toʻatele o tagata na tali ane. Ole maualuga ole saoasaoa ole uila eletise ole 70 km / h ma le umi ole ola ole 3-tausaga e leʻo faʻamalieina manaʻoga ole au tali. Lenei faʻaalia ai o le tele o tagata tali mai mafaufau faʻatinoina uila afi eletise e le ausia o latou tulaga masani. Altough respondents latou te leʻi faʻatuatuaina atoatoa le faʻatinoina o uila eletise, EM mafai ona ausia o latou manaʻoga i aso uma. O le toʻatele o i latou na tali atu na latou mauaina le tele o togi i le totogiina o latou fale ma ofisa nai lo nofoaga faitele. Ae ui i lea, o se papupuni e masani ona maua o le eletise fale eletise o loʻo i lalo lava o le 1300 VA, ma faia ai ma le naunautai le faʻamoemoe o le malo e mafai ona fesoasoani e faʻatupeina fale molia i le fale. O le maua o le totogiina i le ofisa e sili atu le fiafia nai lo nofoaga faitele ona o le fealuaʻi o tagata tali mai i aso uma e aofia ai fale ma ofisa. O le siata 4 o loʻo faʻaalia ai tali a tagata tali atu i le taliaina o uila eletise. Ua faʻaalia ai o le 45,626% o tagata tali mai o loʻo iai le naunautaʻiga e faʻaaoga se uila afi eletise. Lenei iʻuga faʻaalia ai se lumanaʻi lumanaʻi mo le eletise uila afi maketi faʻasoa. O loʻo faʻailoa mai foi ile siata 4 e toeititi 55% tagata tali mai e leai se naunautaiga malosi e faaaoga se uila afi eletise. O le manaia taunuʻuga mai nei faʻamaumauga fuainumera faʻauigaina e ui lava o le naunautaiga mo le faʻaaogaina o uila eletise e manaʻomia pea le faʻaosofia, lautele taliaina o uila eletise o uila e lelei. O leisi mafuaʻaga atonu e tupu o tagata tali mai i ai le uiga e faʻatali ai ma vaʻai le vaetamaina o se uila afi eletise pe o iai seisi faʻaaogaina se uila afi eletise pe leai. Ordinal Logistic Regression Data o gaioiga ma auiliiliina e fuafua ai le vaetamaina manaʻoga o uila eletise i Indonesia e faʻaaoga ai le toe faʻatonuina o le logistic logistic. Ole fesuiaʻiga faʻalagolago i lenei suʻesuʻega o le naunautaiga e faʻaaoga se uila afi eletise (1: matua le manaʻo, 2: le manaʻo, 3: masalosalo, 4: naunau, 5: matua naunau). Ordinal logistic regression na filifilia e avea ma metotia i lenei suʻesuʻega ona o le faalagolago fesuiaʻiga faʻaaogaina le fua masani. O faʻamaumauga na faʻatautaia e faʻaaoga ai le SPSS 25 polokalama ma le tulaga mautinoa o le 95%. Multicollinearity suʻesuʻega na faia e fuafua Fesuiaʻiga Inflation Factors (VIF) ma le averesi VIF o le 1.15- 3.693, o lona uiga e leai se multicollinearity i le faʻataʻitaʻiga. O le manatu faʻaoga na faʻaaogaina i le faʻasolosolo faʻasolosolo faʻasolosolo o loʻo faʻaalia i le Laulau 5. O le laulau 6 o loʻo faʻaalia ai ni vaega o suʻega o suʻega e avea ma faʻavae mo le teʻena poʻo le taliaina o le manatu faʻapitoa mo le faʻavasegaina o mea masani. Laulau 2. Faʻamaumauga a le au tali Tali Demographic item Freq% Demographic Item Freq% Domicile West Java 345 28.2% Galuega Tamaiti aʻoga 175 14.3% East Java 162 13.2% Tagata faigaluega lautele 88 7.2% Jakarta 192 15.7% Aufaigaluega tumaoti 415 33.9% Central Java 242 19.8% Tagata fai pisinisi 380 31.1% North Sumatera 74 6.1% Isi 165 13.5% Yogyakarta 61 5.0% Sulawesi i Saute 36 2.9% Tausaga 17-30 655 53.6% Bali 34 2.8% 31-45 486 39.7% West Sumatera 26 2.1% 46-60 79 6.5% Saute Sumatera 51 4.2%> 60 3 0.2% Tulaga faʻaipoipo Nofofua 370 30.3% Tulaga mulimuli Aʻoaʻoga Tulaga SMP / SMA / SMK 701 57.3% Faʻaipoipo 844 69.0% Tipiloma 127 10.4% Isi 9 0.7% Bachelor 316 25.8% Itupa Tane 630 51.5% Matai 68 5.6 % Tamaʻitaʻi 593 48.5% Faʻailoga Fomaʻi 11 0.9% Tupe maua i masina taʻitasi 0 154 12.6% Tulaga faʻaalu masina <IDR 2,000,000 432 35.3% <IDR 2,000,000 226 18.5% IDR2,000,000-5,599,999 640 52.3% IDR 2,000,000-5,999,999 550 45% IDR6,000,000- 9,999,999 121 9.9% IDR 6,000,000-9,999,999 199 16.3% ≥ IDR 10,000,000 30 2.5% IDR10,000,000- 19,999,999 71 5.8% ≥ I DR 20,000,000 23 1,9% Laulau 3. Faʻamatalaga Faʻamaumauga mo Tupe, Tekonolosi, ma Macro-level Fesuiaʻiga Tulaga Fua Faʻatulaga Faʻatulagaina Tulaga Tulaga ML7 (molia tau tisiki.) 4.4563 1 ML3 (CS i le fale) 4.1554 9 ML6 (faʻaletausaga lafoga tisiketi. ) 4.4301 2 ML2 (CS i nofoaga faigaluega) 4.1055 10 ML5 (faʻatauga faʻatau) 4.4146 3 ML1 (CS i nofoaga faitele) 4.0965 11 TE4 (saogalemu) 4.3181 4 TE5 (ola maa) 4.0924 12 FI3 (totogiina o tau) 4.2518 5 TE2 (paoa ) 4.0597 13 TE1 (agavaʻa gafatia) 4.2396 6 TE3 (taimi faʻatupeina) 4.0303 14 ML4 (nofoaga tautua) 4.2142 7 FI1 (tau faʻatau) 3.8814 15 FI4 (tau faʻaleleia) 4.1980 8 FI2 (tau o le maa) 3.5045 16 Lisi 4. Faʻamatalaga Faʻamaumauga mo Faʻatagaina Autu 1: matua le manaʻo 2: le manaʻomia 3: masalosalo 4: naunau 5: naunau naunau e faʻaaoga uila eletise 0.327% 2.044% 15.863% 36.141% 45.626% O iʻuga o logistic regression auiliiliga mo fesuiaʻiga SD1 e oʻo i SD11 e ona le sociodemographic mea faʻaalia faʻaalia ai iʻuga e naʻo le tele o taimi o faʻasoa i luga ala o faasalalauga lautele (SD9) ma le maualuga o le siʻosiʻomaga popole (SD11) ei ai se aafiaga taua i luga o le faʻamoemoe o uila eletise i Initonesia. O le taua taua mo le fesuiaʻiga taua o tulaga faʻaipoipoga o 0.622 mo nofofua ma 0.801 mo faaipoipo. O na taua e le lagolagoina Lagolagoina 1. O le faʻaipoipoga tulaga e le matua aʻafia ai le faʻamoemoe o le faʻaaogaina o se uila eletise ona o le taua taua e sili atu i le 0.05. O le taua taua mo tausaga o le 0.147 ina ia le tausaga matua aʻafia ai le faʻamoemoe e faʻaaogaina se uila eletise. O le aoga o le tala faʻatatau mo le tausaga o le -0.168 e le lagolagoina Hypothesis 2. O le faʻailoga le lelei o lona uiga o le maualuga o le tausaga, o le maualalo o le faʻamoemoe e vaʻaia se uila afi eletise. O le taua taua mo le fesuiaʻiga agavaʻa, itupa, (0.385) e le lagolagoina Hypothesis 3. Gender e le o matua taua le faʻamoemoe e faaaoga se uila afi eletise. O le taua taua mo le tulaga mulimuli o le aʻoaʻoga (0.603) e le lagolagoina Hypothesis 4. O lea, o le mulimuli aʻoga e le o matua taua le faʻamoemoe e faʻaaoga se uila afi eletise. O le aoga o le tala faʻatatau mo le mulimuli tulaga aʻoaʻoga o le 0.036 o lona uiga o se faʻailoga lelei o lona uiga o le maualuga o le tulaga o aʻoga o le maualuga atu o le faʻamoemoe e faʻaaogaina se uila afi eletise. O le taua taua mo le fesuiaʻiga agavaʻa o le galuega o 0.487 mo tamaiti aʻoga, 0.999 mo tagata faigaluega lautele, 0.600 mo tagata faigaluega tumaoti, ma 0.480 mo le aufaipisinisi e le lagolagoina Hypothesis 5. O le galuega e le o aʻafia tele le faʻamoemoe e faʻaaoga se uila afi eletise. UTAMI ET AL. / FOLAFOLAGA I TUPE MAUA O TOTONU I ALA - VOL. 19 LEAI. 1 (2020) 70-81 DOI: 10.25077 / josi.v19.n1.p70-81.2020 Utami et al. 75 Tabel 5. Hypothesis Hypothesis Socio- H1: o le tulaga faʻaipoipoga e i ai sona aafiaga taua tele i le faʻamoemoe e faʻaaoga se uila afi eletise. Demo- H2: tausaga ei ai se aoga taua aafiaga i luga o le faʻamoemoe o le taliaina o se uila afi eletise. kalafi H3: itupa ei ai se aoga taua aafiaga i luga o le faʻamoemoe o le vaetamaina o se uila afi. H4: tulaga aʻoaʻoga mulimuli ua i ai se lelei taua aafiaga i luga o le faʻamoemoe o le taliaina o se uila afi eletise. H5: galuega o loʻo i ai se aoga taua aafiaga i luga o le faʻamoemoe o le taliaina o se uila afi eletise. H6: masina faʻatatau taumafaina tulaga i ai se lelei taua aafiaga i luga o le faʻamoemoe o le taliaina o se uila afi eletise. H7: masina faʻatupeina tulaga e i ai se lelei taua aafiaga i luga o le faʻamoemoe o le taliaina o se eletise uila afi. H8: numera o le umiaina uila afi o loʻo i ai se lelei taua aafiaga i luga o le faʻamoemoe o le taliaina o se uila afi eletise. H9: taimi masani o le fefaʻasoaaʻi i luga o ala o faasalalauga lautele ei ai se lelei taua aafiaga i luga o le faʻamoemoe o le taliaina o se uila afi uila afi. H10: tele o luga ole laiga fesoʻotaʻiga fesoʻotaʻiga i ai se lelei taua aafiaga i luga o le faʻamoemoe o le taliaina o se eletise uila afi. H11: o le faʻalauiloaina o le siosiomaga e i ai sona aoga taua tele ile faʻamoemoe e faʻaaoga se uila afi eletise. Tupe H12: faʻatau tau e iai sona aoga taua ile faʻamoemoe e faʻaaoga se uila afi eletise. H13: o le tau o le maa e iai sona aoga taua i le faʻamoemoe e faʻaaoga se uila afi eletise. H14: o le totogiina o tau e iai sona aoga taua ile faʻamoemoe e faʻaaoga se uila afi eletise. H15: tau o tausiga e i ai se lelei taua aafiaga i luga o le faʻamoemoe o le vaetamaina o se uila afi. H16: agavaʻa agavaʻa gafatia ei ai se lelei taua aafiaga i luga o le faʻamoemoe o le taliaina o se uila afi eletise. H17: o le paoa e i ai sona aoga taua tele i le faʻamoemoe e faʻaaoga se uila afi eletise. Techno- H18: o le faʻatupeina o le taimi e i ai sona aoga taua tele i le faʻamoemoe e faʻaaoga se uila afi eletise. talafeagai H19: saogalemu ei ai se aoga taua aafiaga i luga o le faʻamoemoe o le taliaina o se uila afi eletise. H20: o le ola maa o loʻo i ai sona aoga taua i le faʻamoemoe o le taliaina o se uila afi. H21: maua o le faʻatupeina o nofoaga faʻatulagaina i nofoaga faitele o loʻo i ai se lelei taua aafiaga i le faʻamoemoe o le faʻaaogaina o se uila afi. H22: maua o le faʻatupeina o nofoaga faʻatulagaina i le galuega o loʻo i ai se lelei taua aafiaga i luga o le faʻamoemoe o le taliaina o se eletise uila afi. Macrolevel H23: maua o le faʻatupeina o nofoaga faʻatulagaina fale i le fale ei ai se lelei taua aafiaga i luga o le faʻamoemoe o le taliaina o se uila afi eletise. H24: tautua nofoaga avanoa o loʻo i ai se lelei taua aafiaga i luga o le faʻamoemoe o le vaetamaina o se eletise uila afi. H25: faʻatauga faʻamalosia tulafono faʻatonutonu e i ai se lelei taua aafiaga i luga o le faʻamoemoe o le taliaina o se eletise uila afi. H26: tausaga faʻaletulafono lafoga lafoga aiaiga ei ai se lelei taua aafiaga i luga o le faʻamoemoe o le taliaina o se uila afi eletise. H27: o le faʻatupeina o tau faʻaitiitiga faʻavae o loʻo i ai sona aoga taua tele i le faʻamoemoe o le taliaina o se uila afi eletise. Laulau 6. Faʻataʻitaʻiga Faʻafuaina Faʻafuainumera Faʻataʻitaʻiga Var Value Sig Var Value Sig SD1: nofofua 0.349 0.622 TE1 0.146 0.069 SD1: faʻaipoipo 0.173 0.801 TE2 0.167 0.726 SD1: isi 0 TE3 0.240 0.161 SD2 -0.168 0.147 TE4 -0,005 0.013 * SD3: male 0.117 0.385 TE5 0,068 0.765 SD3: fafine 0 ML1 -0.127 0.022 * SD5: tamaiti aʻoga -0.195 0.487 ML2 0.309 0.000 * SD5: civ. tautua 0,0000 0.999 ML3 0.253 0.355 SD5: tumaoti. emp -0.110 0.6 ML4 0.134 0.109 SD5: entrepr 0.147 0.48 ML5 0.301 0.017 * SD5: isi 0 ML6 -0.059 0.107 SD6 0.227 0.069 ML7 0.521 0.052 SD7 0.032 0.726 TE1 0.146 0.004 * SD8 0.180 0.161 TE2 0.167 0.962 SD9 0.111 0.04 0.2 SD10 0.016 0.765 TE4 -0.005 0.254 SD11 0.226 0.022 * TE5 0.068 0.007 * FI1 0.348 0.000 * ML1 -0.127 0.009 * FI2 -0.069 0.355 ML2 0.309 0.181 FI3 0.136 0.109 ML3 0.253 0.017 * FI4 0.193 0.017 * ML4 0.134 0.672 * tulaga mautinoa O le taua taua mo le masina taumafaina tulaga (0.069) e le lagolagoina Hypothesis 6, o le masina taumafaina tulaga e le o aafia tele ai le faamoemoe e faaaoga se uila afi eletise. O le tau faʻatatau mo le masina taumafaina 0.227, o se faʻailoga lelei o lona uiga o le maualuga o le tulaga o tupe faʻaalu i le masina o le maualuga le faʻamoemoe e faʻaaogaina se uila afi eletise. O le taua taua mo le masina tupemaua tulaga (0.726) e le lagolagoina Hypothesis 7, o le masina tupemaua tulaga e le tele aʻafia ai le faʻamoemoe e faʻaaogaina se eletise uila afi. O le tau aoga mo le masina tupemaua tulaga o le 0,032, lelei faʻailoga o lona uiga o le maualuga le maualuga o le masina tupemaua o le maualuga atu o le faʻamoemoe e vaʻaia se uila afi eletise. O le taua taua mo le numera o uila afi uila (0.161) e le lagolagoina Hypothesis 8, o le numera o le umiaina uila afi e le o aafia tele ai le faʻamoemoe e faaaoga se uila afi eletise. O le tau aoga mo le tulaga o le umiaina o uila afi o le 0.180, o le faʻailoga lelei o lona uiga o le tele o numera o uila afi o loʻo ia te oe, o le maualuga o le faʻamoemoe e faʻaaoga se uila afi eletise. O le taua taua mo le taimi o le fefaʻasoaaʻi i luga o ala o faasalalauga lautele (0.013) lagolagoina Hypothesis 9, o le tele o taimi e fefaʻasoaaʻi ai i luga o ala o faasalalauga lautele ei ai se aafiaga taua i luga o le faʻamoemoe o le taliaina o se uila afi eletise ona o le taua taua e laititi atu i le 0.05. UTAMI ET AL. / JURNAL OPTIMASI SISTEM INDUSTRI - VOL. 19 LEAI. 1 (2020) 70-81 76 Utami et al. DOI: 10.25077 / josi.v19.n1.p70-81.2020 O le tau o le fuafuaina mo le fefaʻasoaaʻi o taimi i luga o ala o agafesoʻotaʻi o 0.111, faʻailoga lelei o lona uiga o le maualuga o le tele o taimi e fefaasoaaʻi ai se tasi i luga o ala o faasalalauga lautele, o le maualuga o le avanoa o le vaetamaina o se eletise uila afi. Taua taua mo le tele o luga o le initoneti fesoʻotaʻiga fesoʻotaʻiga (0.765) e le lagolagoina Hypothesis 10, o le tele o le aapa atu o le sosaiete fesoʻotaʻiga e le taua tele le faʻamoemoe o le taliaina o se uila afi. O le tau o le tala faʻatatau mo le aofaʻi o tagata na oʻo atu i le upega tafailagi o le 0.016, o faʻailoga lelei o lona uiga o le maualuga atu o le tele o upega tafailagi o fesoʻotaʻiga le maualuga o le faʻamoemoe e faʻaaogaina se uila afi eletise. O le taua taua mo le tulaga o le siʻosiʻomaga malamalama (0.022) lagolagoina Hypothesis 11, o le tulaga o le siʻosiʻomaga popolega ei ai se aafiaga tele i luga o le faʻamoemoe e faʻaaoga se uila afi eletise. O le aoga o le tala faʻatatau mo le tulaga o le malamalama i le siʻosiʻomaga o le 0.226, o faʻailoga mautinoa o lona uiga o le maualuga o le tulaga o le siosiomaga popolega o i ai i se tagata, o le maualuga foʻi lea o le faʻamoemoe e faʻaaoga se uila afi eletise. O iʻuga o suʻesuʻega o loʻo faʻatonuina mo le suiga o fesuiaʻiga FI1 i le FI4 o loʻo iai i mea tau tupe o loʻo faʻaalia ai o iʻuga o le tau o le faʻatau (FI1) ma tau o le tausiga (FI4) e iai se aafiaga taua ile faʻamoemoe o uila afi eletise i Indonesia. O le taua taua mo le tau faʻatau (0.00) lagolagoina le Hypothesis 12, o le faʻatau tau e iai sona taua tele ile faʻamoemoe e faʻaaoga se uila afi eletise.O le tau aoga mo le tau o le faʻatau o le 0.348, o le faʻailoga mautinoa o lona uiga o le sili atu ona talafeagai o le faʻatau o se uila afi mo se tasi, o le maualuga foʻi lea o le faʻamoemoe e faʻaaoga se uila afi eletise. O le taua taua mo le maa tau (0.355) e le lagolagoina Hypothesis 13, maa tau e le matua aʻafia ai le faʻamoemoe e faʻaaoga se uila afi eletise. O le taua taua mo le totogiina o tau (0.109) e le lagolagoina le Hypothesis 14, o le tau o le tau e leai sona aoga tele i le faʻamoemoe e faʻaaoga se uila afi eletise. O le tau aoga mo le totogiina o tau o le 0.136, faʻailoga mautinoa o lona uiga o le sili atu ona talafeagai o le tau o le faʻatupeina o se uila afi mo se tasi, o le maualuga o le faʻamoemoe e vaʻaia se uila afi eletise. O le taua taua mo tau tausiga (0.017) e le lagolagoina Hypothesis 15, tau tausiga o loʻo i ai se aafiaga taua i luga o le faʻamoemoe e faaaoga se uila afi eletise. O le tau o le tala faʻatatau mo le tausiga o tau o 0.193, faʻailoga mautinoa o lona uiga o le sili atu ona talafeagai o le tau o le eletise uila afi mo se tasi, o le maualuga le faʻamoemoe e vaʻaia se uila afi eletise. O iʻuga o suʻesuʻega o loʻo faʻatonuina mo le fesuiaʻiga o ituaiga TE1 e oʻo atu i le TE5, o mea taua ia o loʻo faʻaalia mai ai, o taimi ole taimi e faʻaalu ai le maa (TE3) e iai sona aafiaga taua ile faʻaogaina o uila afi i Indonesia. O le taua taua mo agavaʻa agavaʻa (0.107) e le lagolagoina Hypothesis 16, agavaʻa agavaʻa e leai se taua aafiaga i luga o le faʻamoemoe e faʻaaoga se uila afi eletise. O le tau aoga mo se mileage sili ona maualuga o le 0.146, o le faʻailoga lelei o lona uiga o le sili atu ona talafeagai o le maualuga mileage o se uila afi eletise mo se tasi, o le maualuga le faʻamoemoe e vaʻaia se uila afi eletise. O le taua taua mo le tutoatasi fesuiaʻiga paoa poʻo le maualuga saosaoa (0.052) e le lagolagoina Hypothesis 17, maualuga saoasaoa e le matua aafia ai le faʻamoemoe e faaaoga se uila afi eletise. O le aoga o le malosi o le malosi poʻo le maualuga o le saoasaoa o le 0.167, o faʻailoga mautinoa o lona uiga o le sili atu ona talafeagai o le maualuga o le saoasaoa o le uila afi mo se tagata, o le maualuga foʻi lea o le faʻamoemoe e faʻaaogaina se uila afi eletise. O le taua taua mo le faʻatupeina o taimi (0.004) lagolagoina Hypothesis 18, taimi faʻatupeina ei ai se aafiaga taua i luga o le faʻamoemoe e faʻaaoga se uila afi eletise. O le tau fuafuaina mo le faʻatupeina o le taimi o le 0.240, faʻailoga mautinoa o lona uiga o le sili atu ona talafeagai le maualuga o le saoasaoa o se uila afi mo se tasi, o le maualuga o le faʻamoemoe e vaʻaia se uila afi eletise. O le taua taua mo le saogalemu (0.962) e le lagolagoina Hypothesis 19, saogalemu e le o aafia tele ai le faʻamoemoe e faaaoga se uila afi eletise. O le aoga o le tala faʻatatau mo le saogalemu o le -0.005, faʻailoga le lelei o lona uiga o le sili atu le saogalemu o se tasi e faʻaogaina le uila eletise, o le maualalo o le faʻamoemoe e vaʻaia se uila afi eletise. O le taua taua mo ola maa (0.424) e le lagolagoina Hypothesis 20, o le ola maa e leai se taua aafiaga i luga o le faʻamoemoe e faaaoga se uila afi eletise. O le aoga o le tala faʻatatau mo le ola maa o le 0.068, o le faʻailoga lelei o lona uiga o le sili atu ona talafeagai o le olaga atoa o se uila afi uila afi, o le maualuga le faʻamoemoe e vaʻaia se uila afi eletise. O iʻuga o suʻesuʻega o le toe faʻatonuina o loʻo lelei mo fesuiaʻiga ML1 i le ML7 o loʻo aofia ai i tulaga maualuluga o loʻo faʻaalia ai iʻuga e naʻo le totogiina o avanoa i falefaigaluega (ML2), faʻatupeina o avanoa i le nofoaga e nonofo ai (ML3), ma le faʻaeeina atu o tau faʻavae mo tau paʻu (ML7) e i ai aafiaga taua i le vaetamaina faʻamoemoe o uila eletise i Initonesia. O le taua taua mo le mauaina o avanoa i nofoaga faitele (0.254) e le lagolagoina le Hypothesis 21, o le faʻaavanoaina o avanoa i nofoaga faitele e le matua aʻafia ai le faʻamoemoe e faʻaaogaina eletise uila afi. O le taua taua mo le mauaina o avanoa i falefaigaluega (0,007) lagolagoina Hypothesis 22, molia maua i falefaigaluega ei ai le taua aafiaga i le faʻamoemoe o le taliaina o se uila afi uila afi. O le taua taua mo le mauaina o avanoa i se fale (0,009) lagolagoina Hypothesis 22, maua o le molia i le fale ei ai se aafiaga taua i le faʻamoemoe o le taliaina o se uila afi. O le taua taua mo le mauaina o nofoaga tautua (0.181) e le lagolagoina Hypothesis 24, o le mauaina o tautua nofoaga e leai se taua aafiaga i luga o le faʻamoemoe o le faʻaaogaina o se uila afi eletise. O le taua taua mo le faʻatauga faʻamalosi tulafono (0.017) lagolagoina le Masaniaga 25, faʻatauga faʻamalosia tulafono faʻatonutonu e i ai se aafiaga taua i luga o le faʻamoemoe o le taliaina o se uila afi eletise. O le taua aoga mo le lafoga faʻaletulafono lafoga faʻavae (0.672) e le lagolagoina Hypothesis 26, faaletausaga lafoga faʻamalosia tulafono faʻaititia e leai se taua aafiaga i le faʻamoemoe o le faʻaaogaina o se uila afi uila afi. O le taua taua mo le faʻatupeina o tau paʻu (0,00) lagolagoina le Hypothesis 27, o le totogiina o tau faʻaititia o tau faʻaititia, e i ai sona aafiaga taua i le faʻamoemoe e faʻaaoga se uila afi eletise. E tusa ai ma le iʻuga mai le macro-level factor, o le faʻaaogaina o uila afi eletise e mafai ona mautinoa pe a fai o le faʻatonuina o nofoaga i nofoaga o galuega, nofoaga e faʻatupe ai le fale i le fale, ma le faʻatupeina o tau faʻaititia o tau o tulafono ua sauni e faʻaaoga e tagata faʻatau. I le aotelega, o le tele o taimi e tufatufaina ai i luga o ala o faasalalauga lautele, le maualuga o le siʻosiʻomaga malamalama, faʻatauina o tau, tausiga tau, o le maualuga saosaoa o uila eletise, taimi faʻatupeina maa, mauaina o le faʻatonuina o nofoaga faʻatulagaina galuega i le galuega, mauaina o le paoa fale faʻavae - faʻatupeina atinae tetele, UTAMI ET AL. / FOLAFOLAGA I TUPE MAUA O TOTONU I ALA - VOL. 19 LEAI. 1 (2020) 70-81 DOI: 10.25077 / josi.v19.n1.p70-81.2020 Utami et al. 77 faʻatau faʻamalosi faiga faʻavae, ma le totogiina o tau paʻu faʻaosofia faiga faʻamalosi e matua aafia ai le faʻamoemoe e faʻaaoga eletise taʻavale. Equation Model ma Probability Function Equation 3 o se logit equation mo le filifiliga o le tali "matua le manaʻomia" e vaetamaina ai se uila afi eletise.  =  = + 27 1 01 (1 |) kg Y Xn   k Xik (3) Equation 4 o se logit equation mo le filifiliga o le tali "le manaʻo" e vaʻaia ai se uila afi eletise.  =  = + 27 1 02 (2 |) kg Y Xn   k Xik (4) Equation 5 o se logit equation mo le filifiliga o le tali "masalosalo" e faʻaaogaina ai se uila afi eletise.  =  = + 27 1 03 (3 |) kg Y Xn   k Xik (5) Equation 6 o se logit equation mo le tali filifiliga "naunau" e vaʻaia se uila afi eletise.  =  = + 27 1 04 (4 |) kg Y Xn   k Xik (6) Faigofie gaioiga o vaetamaina manaʻoga uila afi faʻaalia i le Faʻatulaga 7 i le Faʻatusa 11. Equation 7 o le probablility gaioiga mo le filifiliga o le tali " matua le fia ”faaaoga se uila afi eletise. eenng YX g YXP Xn PY Xn (1 |) (1 |) 1 1 () (1 |)   + = =  (7) Equation 8 o le probablility function mo le filifiliga o le tali "le manaʻo" e faʻaaoga se uila afi eletise. eeeennnng YX g YX g YX g YX nnnn PYXPYXPXPYX (1 |) (1 |) (2 |) (2 |) 2 1 1 (2 |) (1 |) () (2 |)     + - + = =  -  = = (8) Equation 9 o le probablility function mo le filifiliga o le tali "masalosalo" e faʻatutu ai se uila afi eletise. eeeennnng YX g YX g YX g YX nnnn PYXPYXPXPYX (2 |) (2 |) (3 |) (3 |) 3 1 1 (3 |) (2 |) () (3 |)     + - + = =  -  = = (9) Equation 10 o le probablility function mo le filifiliga o le tali "naunau" e vaʻaia se uila afi eletise. eeeennnng YX g YX g YX g YX nnnn PYXPYXPXPYX (3 |) (3 |) (4 |) (4 |) 4 1 1 (4 |) (3 |) () (4 |)     + - + = =  -  = = (10) Equation 11 o le probablility function mo le filifiliga o le tali "matua naunau" e faʻaaoga se uila afi eletise. eenng YX g YX nnn PYXPXPYX (4 |) (4 |) 5 1 1 1 (4 |) () (5 |)   + = - = -  = = (11) Faʻaaogaina Faʻamoemoega Faʻatagaina Le faʻasologa faʻasolosolo o le faʻafetauiina o faʻafitauli i le taimi lena faatatau i se faʻataʻitaʻiga o tali a le au tali. Laulau 8 faʻaalia uiga ma tali o le faʻataʻitaʻiga. Ma o le avanoa e tali ai taʻitaʻiga taʻitasi i luga o le faalagolago fesuiaʻiga e fuafua faʻavae luga o le Faʻamatalaga 7 - 11. O se faʻataʻitaʻiga o tali o loʻo iai tali e pei ona faʻaalia i le Laʻasaga 7, e ono maua le 0,0013 mo le matua le manaʻo e faʻaaoga uila afi, o le ono mafai o le 0,0114. mo le le manaʻo e faʻaaoga uila afi eletise, o le ono mafai ona 0.1788 mo le masalosalo e faʻaaoga uila eletise, o le avanoa o le 0.563 e naunau e faʻaaoga se uila afi eletise, ma le ono mafai ona 0.2455 e matua naunau e faʻaaoga se uila afi eletise. Ole taliaina ole uila afi eletise mo 1,223 tali na fuafuaina foi ma le averesi ole aoga ole tali mo le le mananaʻo e faʻaaoga le uila afi eletise o le 0,000031, le manaʻo e faʻaaoga uila afi eletise o le 0,0198, masalosalo ole faʻaaogaina o uila afi eletise o le 0.1482, naunau e faʻaaoga se uila afi eletise o le 0.3410, ma le naunautaiga malosi e faaaoga se uila afi eletise o 0.4880. Afai o le avanoa mo naunau ma matua naunau ua totalized, o le avanoa mo Initonesia e faʻaaogaina uila eletise taunuu 82.90%. Fautuaga mo Pisinisi ma Faiga Faʻavae Faʻatino I le faʻavasegaina faʻasolosolo o loʻo vaʻavaʻaia, o le tele o taimi e tufatufaina ai i luga o upega tafailagi o se taua tele mafuaʻaga o le faʻamoemoe e vaʻaia se uila afi eletise. O le taua o ala o faasalalauga lautele o se tulaga mo tagata lautele e maua ai faʻamatalaga e uiga i uila eletise o le a aʻafia ai le naunautaʻi e faʻaaogaina uila eletise. E mafai e le malo ma le aufaʻatau ona taumafai e faʻaoga lenei alagaʻoa, mo se faʻataʻitaʻiga, e mafai e tagata fai pisinisi ona faʻalauiloa e ala i ponesi poʻo le faʻafetaia o tagata faʻatau na faʻatau uila afi ma faʻasoa mea lelei e fesoʻotaʻi i uila afi i la latou upega tafailagi. Lenei auala ono faʻaosofia ai isi e avea ma fou faʻaaogaina o se uila afi. E mafai e le malo ona faʻafesoʻotaʻi pe faʻalauiloa uila afi i tagata lautele e ala i ala o fesoʻotaʻiga lautele e faʻaosofia ai tagata lautele fesuiaʻi mai masani uila afi i uila eletise. Lenei suʻesuʻega faʻamaonia le taua o le aafiaga o le toner-level mea i le taliaina o uila eletise i Indonesia. I le faʻamaumauga masani o le faʻavasegaina o faʻafitauli, o le faʻatupeina o nofoaga o loʻo maua i le falefaigaluega, faʻatupeina o mea e maua i le fale, o le faʻamalosia o faʻatauga, ma le totogiina o tau faʻaalu, e matua aʻafia ai le faʻamoemoe o le faʻaaogaina o se uila afi. UTAMI ET AL. / JURNAL OPTIMASI SISTEM INDUSTRI - VOL. 19 LEAI. 1 (2020) 70-81 78 Utami et al. DOI: 10.25077 / josi.v19.n1.p70-81.2020 Laulau 7. Faʻataʻitaʻiga Tali Tali Variabel Tali Fua Faatatau Faʻaipoipo Tulaga Faʻaipoipo X1b 2 Tausaga 31-45 X2 2 Itupa Tane X3a 1 Tulaga Aʻoaʻoga Maualuga Matai X4 4 Galuega Tumaʻoti Tagata faigaluega X5c 3 Masina Taʻitasi tulaga taumafaina Rp2.000.000-5.999.999 X6 2 Masina tupemaua tulaga Rp. 6.000.000-9.999.999 X7 3 Aofai o le umiaina uila afi ≥ 2 X8 3 Faʻatele o le tufatufaina i luga o ala o agafesoʻotaʻi ni nai taimi / masina X9 4 Tele o luga o le upega tafailagi fesoʻotaʻiga 100-500 tagata X10 2 Siʻosiʻomaga malamalama 1 X11 1 Harga beli 3 X12 3 Tau o le maa 3 X13 3 Totogiina o tau 3 X13 3 Tau Tausiga 5 X14 5 Mafai gafatia 4 X15 4 Malosiaga 5 X16 5 Taimi Faʻatonutonu 4 X17 4 Saogalēmū 5 X18 5 Maea ola 4 X19 4 Avanoa ofisa faʻasalalau avanoa i nofoaga faitele i le galuega 4 X21 4 Avanoa faʻatupeina avanoa i le fale 4 X22 4 Nofoaga avanoa avanoa 2 X23 2 Faʻatauga faʻamalosia faatosina 5 X24 5 Faʻaletupe lafoga faʻavae faiga faʻavae 5 X25 5 Totogiina tau paʻu faʻavae 5 X26 5 Totogiina tau 5 X27 5 Tausiga tau 3 X13 3 Mileage agavaʻa 5 X14 5 Malosiaga 4 X15 4 Faʻafoeina o taimi 5 X16 5 O le toʻatele o tagata tali atu e manatu e faʻatupeina le fausiaina o mea tetele i fale, falefaigaluega ma nofoaga faitele e matua aʻafia ai le taliaina o uila eletise. E mafai e le malo ona faʻatulaga le faʻapipiʻiina o nofoaga e faʻatutu ai le faʻatonuina o nofoaga i nofoaga faitele e lagolagoina ai le taliaina o uila eletise. E mafai foi ona galulue faʻatasi le malo ma le vaega o pisinisi e faʻatauaina lenei mea. I le fausiaina o tulaga maualuga-faʻailo, o lenei suʻesuʻega fuafuaina nisi o faʻamalosia faiga faʻavae filifiliga. O le sili taua taua faʻamalosia faiga faʻavae e tusa ma le suʻesuʻega o le faʻatau faatosina faiga faʻavae ma le totogiina o tau paʻuʻu faʻamalosia ai aiaiga e mafai ona iloiloina e le malo e lagolagoina le taliaina o uila eletise i Indonesia. I mea tau tupe, o le faʻatau tau e iai sona taua tele ile faʻamoemoe e faʻatau se uila afi eletise. Ole mafuaʻaga lea o le faʻamalosiʻau mo le faʻatau fesoasoani ua matuaʻi aʻafia ai foʻi le faʻamoemoe fai. O le taugofie tau tausiga o uila eletise nai lo le masani ai uila afi e matua aafia ai le vaetamaina faʻamoemoe o uila eletise. O le mea lea o le mauaina o auaunaga e faʻamalieina manaʻoga tagata faʻatau o le a atili faʻamalosia ai le faʻamoemoe o le faʻaaogaina uila eletise ona o le tele o tagata faʻaaoga e le iloa vaega i uila eletise o lea latou te manaʻomia ai ni tagata atamamai tomai pe a fai e i ai ni mea faʻaleagaina. O le faʻatinoina o uila eletise o loʻo faʻamalieina ai manaʻoga o tagata faʻatau e faʻafetaui a latou feoaʻi i aso uma. Ole maualuga ole saoasaoa ole uila eletise ma le taimi e faʻaalu ai le taimi e mafai ai ona ausia tulaga manaʻomia e tagata faʻatau. Ae ui i lea, sili atu lelei faʻatinoina uila afi e pei o le faateleina le saogalemu, maa ola, ma isi mileage o le a mautinoa lava faateleina ai le faamoemoe o le vaetamaina o se uila afi eletise. I le faʻaopopoga i le faʻateleina o tekonolosi faʻatupeina, le malo ma pisinisi tatau foi ona faʻaleleia le saogalemu ma le faʻatuatuaina iloiloina faʻavasega mo uila eletise e faʻateleina le talitonuina o tagata lautele. Mo pisinisi, faʻalauteleina le lelei ma faʻatinoina o se tasi o auala sili ona lelei e faʻateleina ai le naunautaʻi o tagata faʻatau mo uila afi. Tagata faʻatau o loʻo talavou ma i ai le maualuga maualuga o aʻoaʻoga e mafai ona faʻatulagaina e avea ma vave faʻatosinaina e avea ma aʻafiaga aua ua uma ona latou maua se lagona sili atu faʻamoemoega lelei ma ua i ai se lautele fesoʻotaʻiga. Maketi vaevaega mafai ona ausia e ala i le faʻalauiloaina faʻapitoa faʻapitoa mo taulaʻi tagata faʻatau. I se faʻaopopoga, o tagata tali atu ma le maualuga o le siʻosiʻomaga malamalama na ono manaʻo e faʻaaoga uila afi. UTAMI ET AL. / FOLAFOLAGA I TUPE MAUA O TOTONU I ALA - VOL. 19 LEAI. 1 (2020) 70-81 DOI: 10.25077 / josi.v19.n1.p70-81.2020 Utami et al. 79 FAAIUGA O le fesuiaiga mai uila afi masani i uila afi eletise e mafai ona avea ma tali sili ona lelei e foia ai le faafitauli o maualuga CO2 tulaga i Indonesia. Na iloa foi e le malo o Indonesia ma ua laa i totonu e ala i le setiina o tulafono eseese e faatatau i eletise i Indonesia. Ae o le mea moni, o le vaetamaina o taʻavale eletise i Initonesia o loʻo i ai lava i se amataga vave tusa lava pe mamao mai le faʻatulagaina setiina e le malo. O le siʻosiʻomaga e le lagolagoina le vaetamaina o uila eletise e pei o le le toe auiliiliina o tulafono faʻatonutonu ma le leai o ni lagolago atinaʻe mafua ai le maualalo vaetamaina o eletise taʻavale i Indonesia. O lenei suʻesuʻega na suʻesuʻe ai le 1,223 tali mai 10 o itumalo sa i ai le aofaʻi o le 80% o le aofaʻi o le faʻatauina atu o uila afi i Initonesia e suʻesuʻe ai itu taua e aʻafia ai le faʻamoemoe e faʻaaogaina uila afi eletise i Indonesia ma saili ai le ono aoga o gaioiga. E ui lava o le toʻatele o tagata faʻamalosi e fiafia e uiga i uila afi ma ua mananaʻo ia fai latou uila afi eletise i le lumanaʻi, o lo latou fiafia e faʻaaoga se uila afi eletise i nei vaitaimi e fai lava sina maualalo. E le mananao le au tetee e faaaoga uila afi eletise i le taimi nei ona o mafuaaga eseese e pei o le leai o ni mea tetele ma ni faiga faavae. Ole toʻatele o tali e iai le uiga ole faʻatali ma tilotilo agai ile faʻaogaina ole uila afi eletise, faʻatasi ai ma mea tau tupe, mea tau tekonolosi, ma tulaga ole maketi e tatau ona mulimulitaʻi ile manaʻoga ole au faʻatau. O lenei suʻesuʻega faʻamaonia le taua o le tele o taimi e tufatufaina ai luga o ala o agafesoʻotaʻi, le maualuga o le siʻosiʻomaga faʻalauiloaina, faʻatauina o tau, tausiga tau, le maualuga o le saoasaoa o uila eletise, taimi faʻatupeina maa, mauaina o le faʻatonuina o nofoaga tetele i le galuega, mauaina o le faʻatupeina o atinaʻe tetele fale, faʻatau faiga faʻamalosiʻau, ma le faʻatupeina o tau faʻaititia le faʻaosofia o totogi o loʻo lagolagoina le taliaina o uila eletise i Indonesia. E manaʻomia le lagolago a le malo ile tuʻuina atu o le faʻatupeina o nofoaga tetele ma le unaʻia o faiga faʻavae ina ia faʻatelevaveina le faʻaaogaina o uila afi i Indonesia. Tekinolosi mea taua e pei o mileage ma maa ola tatau manaʻomia e tagata gaosi ia faʻaleleia e lagolagoina le vaetamaina o uila eletise. O mea tau tupe e pei o le tau o faʻatau ma le tau o maa e tatau ona avea ma atugaluga i pisinisi ma le malo. O le maualuga faʻaaogaina o fesoʻotaʻiga fesoʻotaʻi tatau ona faia e faʻalauiloa atu ai se uila eletise i le alalafaga. O nuʻu i tausaga talavou e mafai ona faʻalauiloaina pei o ni tagata faʻaaoga vave aua e tele a latou upega tafaʻilagi lautele. O le iloaina o le vaetamaina o uila eletise i Indonesia e manaʻomia ai sauniuniga sauniuniga ma tau e mafai ona taliaina e tagata faʻatau. O lenei ua mafai ona faʻagaioia e le malo e ala i le malosi o le malo tautinoga i le tele o atunuʻu ua manuia i le suia o masani taʻavale. O isi suʻesuʻega o le a taulaʻi atu i le sailia o aiaiga talafeagai e faatelevave ai le taliaina o uila eletise i Initonesia. FAʻAMATALAGA [1] Initonesia. Badan Pusat Statistik; Perkembangan Jumlah Kendaraan Bermotor Menurut Jenis 1949-2018, 2019 [Online]. Avanoa: bps.go.id. [2] Asosiasi Industri Sepeda Motor Indonesia: Domestic Distribution and Export Statistic, 2020. [Luga o le Initaneti]. https://www.aisi.or.id/statistic. [Avanoa: Mati. 20, 2020]. [3] G. Samosir, Y. Devara, B. Florentina, ma R. Siregar, "O taʻavale eletise i Initonesia: o le auala e agaʻi i le gafataulimaina o femalagaiga", Solidiance: Market Report, 2018. [4] W. Sutopo, RW Astuti, A. Purwanto, ma M. Nizam, "Faʻasalalauga faʻataʻitaʻiga o fou tekonolosi lithium ion maa: O se suʻega suʻesuʻega mo le eletise atamai eletise", Taualumaga o le 2013 Joint International Conference on Rural Information and Communication Technology and Electric-Vehicle Technology, rICT ma ICEV -T 2013, 6741511.https: //doi.org/10.1109/rICTICeVT.2013.6741511. [5] M. Catenacci, G. Fiorese, E. Verdolini, ma V. Bosetti, "Alu i le eletise: Suʻesuʻe faʻapitoa i le lumanaʻi o tekonolosi maa mo taʻavale eletise. In Innovation under Unciguro, "i le Edward Elgar Publishing, 93. Amsterdam: Elsevier, 2015. [6] M. Weiss, P. Dekker, A. Moro, H. Scholz, ma MK Patel," I le eletise o auala felauaiga– o se toe iloiloga o le siʻosiʻomaga, tamaoaiga, ma agafesoʻotaʻi faʻatinoina o eletise uili-uili, "Felauaiga Suesuega Vaega D: Felauaiga ma Siosiomaga, vol. 41, pp. 348-366, 2015. https://doi.org/10.1016/j.trd.2015.09.007. [7] M. Nizam, "Produksi Kit Konversi Kendaraan Listrik Berbasis Baterai Untuk Sepeda Motor Roda Dua Dan Roda Tiga," Laporan Akhir Hibah PPTI, Badan Pengelola Usaha Universitas Sebelas Maret, 2019. [8] MNA Jodinesa, W. Sutopo, ma R. Zakaria, "Markov Chain Analysis e Faʻailoa ai le Maketi Faʻasoa Valoaga o Fou Tekonolosi: O se Suʻesuʻega Mataupu o le Eletise Faʻafouina uila afi i Surakarta, Indonesia", AIP Conference Taualumaga, vol. 2217 (1), pp. 030062), 2020. AIP Publishing LLC. [9] W. Sutopo ma EA Kadir, "O le Initonesia Faʻatulagaina o le Lithium-ion Battery Cell Ferro Phosphate mo Eletise Taʻavale Vaʻaia", TELKOMNIKA Indonesian Journal of Electrical Engineering, vol. 15 (2), itulau 584-589, 2017. https://doi.org/10.12928/telkomnika.v15i2.6233. [10] B. Rahmawatie, W. Sutopo, F. Fahma, M. Nizam, A. Purwanto, BB Louhenapessy, ma le ABMulyono, "Fuafuaina faʻavae mo tulaga faʻatulagaina ma suʻega manaʻoga o le puleaina o maa mo le faʻaaogaina o taʻavale eletise", Faʻagasologa - 4 Konafesi Faʻavaomalo i luga o le Eletise Faʻapitoa Tekonolosi, itulau 7-12, 2018. https://doi.org/10.1109/ICEVT.2017.8323525. [11] W. Sutopo, M. Nizam, B. Rahmawatie, dan F. Fahma, "O se Iloiloga o Eletise Taʻavale Taʻitaʻi Atinae Atinae: Suesue Mataupu I Initonesia", Taualumaga - 2018 5th International Conference on Electric Vehicular Technology, vol. 8628367, pp. 152-157, 2018. https://doi.org/10.1109/ICEVT.2018.8628367. [12] Gaikindo: Tahun 2040 Indonesia Taofi Mobil Berbahan Bakar Minyak, 2017. [Luga o le Initaneti]. gaikindo.or.id. [Avanoa: Mati. 20, 2020]. [13] S. Goldenberg, ”Initonesia e tipi Karaponi Emissions e 29% i le 2030 ″, le Guardian, 2015. UTAMI ET AL. / JURNAL OPTIMASI SISTEM INDUSTRI - VOL. 19 LEAI. 1 (2020) 70-81 80 Utami et al. DOI: 10.25077 / josi.v19.n1.p70-81.2020 [14] YN Sang ma HA Bekhet, "Faʻataʻitaʻiga o le faʻaaogaina o taʻavale afi eletise: O se suʻesuʻega faʻamalosi tino i Meleisia," Journal of Cleaner Production, vol. 92, pp. 75-83, 2015. https://doi.org/10.1016/j.jclepro.2014.12.045. [15] ZY She, Q. Sun, JJ Ma, ma BC Xie, "O a Pupuni i le salalau lautele faʻaaogaina o maa eletise uila afi? Se Suʻesuʻega o Manatu Lautele i Tianjin, Saina, ”Journal of Transport Policy, vol. 56, pp. 29-40, 2017. https://doi.org/10.1016/j.tranpol.2017.03.001. [16] N. Berkeley, D. Jarvis, ma A. Jones, "Iloiloina o le aveina o maa eletise taʻavale: O se suʻesuʻega o papupuni i totonu o avetaʻavale i Peretania," Felauaiga Suesue Vaega D: Felauaiga ma Siosiomaga, vol. 63, pp. 466-481, 2018. https://doi.org/10.1016/j.trd.2018.06.016. [17] C. Zhuge ma C. Shao, "Suʻesuʻeina o Mea Taua na Faʻaosofia ai le Uptake o Eletise Taʻavale i Beijing, Saina: Fuainumera Faʻamaumauga ma Spatial Perspectives," Journal of Cleaner Production, vol. 213, pp. 199-216, 2019. https://doi.org/10.1016/j.jclepro.2018.12.099. [18] A. Widardjono, Analisis Multivariat Terapan dengan Program SPSS, AMOS, dan SMARTPLS (2nd Ed). Yogyakarta: UPP STIM YKPN, 2015. [19] T. Laukkanen, "Le taliaina e le aufaʻatau i le teena o faʻaiuga i foliga foliga tutusa o auaunaga fou: O le mataupu o Initaneti ma faletupe feaveaʻi", Journal of Business Research, vol. 69 (7), pp. 2432–2439, 2016. https://doi.org/10.1016/j.jbusres.2016.01.013. [20] V. Vasseur ma R. Kemp, "O le vaetamaina o le PV i Netherlands: O le fuainumera o faʻamaumauga o tulaga vaetamaina", Renewable and Sustainable Energy Review, vol. 41, pp. 483–494, 2015. https://doi.org/10.1016/j.rser.2014.08.020. [21] MP Gagnon, E. Orruño, J. Asua, AB Abdeljelil ma J. Emparanza, "Faʻaaogaina o se Modified Technology Acceptance Model e Iloilo ai le Soifua Maloloina Polofesa 'Faʻaaogaina se Fou Telemonitoring System", Telemedisinia ma e-Soifua Maloloina, vol. 18 (1), itulau 54-59, 2012. https://doi.org/10.1089/tmj.2011.0066. [22] N. Phaphoom, X. Wang, S. Samuel, S. Helmer, ma P. Abrahamamsson, "O se suʻesuʻega suʻesuʻega i le tele o papupuni faʻapitoa e aʻafia ai le faʻaiuga e vaʻaia tautua ao", Journal of Systems and Software, vol. 103, pp. 167–181, 2015. https://doi.org/10.1016/j.jss.2015.02.002. [23] MWD Utami, AT Haryanto, ma W. Sutopo, "Suʻesuʻega o le Suʻesuʻega o le eletise i Taavale Afi i Initonesia", AIP Conference Processings (Vol. 2217, Nu. 1, i. 030058), 2020. AIP Publishing LLC [24 ] Yuniaristanto, DEP Wicaksana, W. Sutopo, ma M. Nizam, "Fautuaina pisinisi faʻagasologa faʻatekinolosi faʻasalalauga: O se suʻesuʻega suʻesuʻega o le eletise afi eletise incubation", Taualumaga o le 2014 International Conference on Electrical Engineering and Computer Science, ICEECS, 7045257, pp. 254-259. https://doi.org/10.1109/ICEECS.2014.7045257. [25] MA Bujang, N. Saʻat, ma le TM Bakar, "Faʻataʻitaʻiga o le lapoʻa taiala mo le toe faʻaleleia o mea mai suesuega ma le faitau aofaʻi o tagata. faasaienisi faafomai: MJMS, vol. 25 (4), pp. 122, 2018. https://doi.org/10.21315/mjms2018.25.4.12. [26] E. Radjab ma A. Jamʻan, "Metodologi Penelitian Bisnis", Makasar: Lembaga Perpustakaan dan Penerbitan Universitas Muhammadiyah Makasar, 2017. [27] T. Eccarius ma CC Lu, "Faʻamalosiʻau lua-uili mo gafataulimaina gaioiga: O se toe iloiloga o le faʻaaogaina e tagata o uila afi eletise ”, International Journal of Sustainable Transport, vol. 15 (3), itulau 215-231, 2020. https://doi.org/10.1080/15568318.2018.1540735. [28] S. Habich-Sobiegalla, G. Kostka, ma N. Anzinger, "Faʻatauga taʻavale eletise faʻamoemoe o tagatanuu o Saina, Lusia ma Pasila: O se faʻatusatusaga faʻavaomalo suʻesuʻega", Tusi o faʻamaumauga mama, vol. 205, pp. 188- 200, 2018. https://doi.org/10.1016/j.jclepro.2018.08.318. [29] W. Sierzchula, S. Bakker, K. Maat, ma B. Van Wee, "O le aʻafiaga o mea tau tupe ma isi mea tau le tamaoaiga-i luga o le faʻaaogaina o taʻavale eletise", Energy Policy, vol. 68, pp. 183–194, 2014. https://doi.org/10.1016/j.enpol.2014.01.043. [30] RM Krause, SR Carley, BW Lane, ma JD Graham, "Malamalamaaga ma le mea moni: malamalama lautele o plug-in eletise taʻavale i 21 US taulaga", Malosiaga Faʻavae, vol. 63, pp. 433–440, 2013. https://doi.org/10.1016/j.enpol.2013.09.018. [31] D. Browne, M. O'Mahony, ma B. Caulfield, "Faʻafefea tatau ona faʻavasega papupuni i isi suauʻu ma taʻavale ma mafai ai ona iloiloina ni aiaiga faʻavae fou?", Journal of Cleaner Production, vol. 35, pp. 140–151, 2012. https://doi.org/10.1016/j.jclepro.2012.05.019. [32] O. Egbue ma S. Long, "Faʻafitauli i le salalau lautele taliaina o taʻavale eletise: o se auiliiliga o tagata faʻatau uiga ma manatu", Journal of Malosiaga Faʻavae, vol. 48, pp. 717– 729, 2012. https://doi.org/10.1016/j.enpol.2012.06.009. [33] X. Zhang, K. Wang, Y. Hao, JL Fan, ma YM Wei, "O le aʻafiaga o faiga faʻavae a le malo i le manaʻomia o NEV: o le faʻamaoniga mai Saina", Malosiaga Faʻavae, vol. 61, pp. 382–393, 2013. https://doi.org/10.1016/j.enpol.2013.06.114. [34] BK Sovacool ma RF Hirsh, "I tua atu maa: o le suʻesuʻeina o penefiti ma papupuni i plug-in hybrid eletise taʻavale (PHEVs) ma le taʻavale-to-grid (V2G) suiga", Malosiaga Faʻavae, vol. 37, pp. 1095–1103, 2009. https://doi.org/10.1016/j.enpol.2008.10.005. [35] E. Graham-Rowe, B. Gardner, C. Abraham, S. Skippon, H. Dittmar, R. Hutchins, ma J. Stannard, "O le aufaʻatau masani o loʻo aveina moli-uila-eletise ma faʻaola uila afi eletise: o se suʻesuʻega lelei o tali ma iloiloga ", Transp. Res. Vaega A: Faiga Faʻavae., Vol. 46, pp. 140–153, 2012. https://doi.org/10.1016/j.tra.2011.09.008. [36] AF Jensen, E. Cherchi, ma SL Mabit, "O le aufaʻatau masani o loʻo momoli le plug-in battery-electric and plugin hybrid eletise taʻavale: o se suʻesuʻega lelei o tali ma iloiloga", Transp. Res. Vaega D: Transp. Siosiomaga., Vol. 25, pp. 24–32, 2013. [Luga o le initoneti]. Avanoa: ScienceDirect. [37] ND Caperello ma KS Kurani, "Aiga 'tala o latou fetaiaʻiga ma se plugin hybrid eletise taʻavale", En environment. Behav., Vol. 44, pp. 493–508, 2012. https://doi.org/10.1177/0013916511402057. [38] JS Krupa, DM Rizzo, MJ Eppstein, D. Brad-Lanute, DE Gaalema, K. Lakkaraju, ma le CE Warrender, "O tala a le au aiga e uiga i a latou fetaiaʻiga ma se plugin hybrid eletise taʻavale", Suʻesuʻega o se faʻamatalaga a tagata faʻatau i UTAMI ET AL. / FOLAFOLAGA I TUPE MAUA O TOTONU I ALA - VOL. 19 LEAI. 1 (2020) 70-81 DOI: 10.25077 / josi.v19.n1.p70-81.2020 Utami et al. 81 plug-in hybrid eletise taʻavale. Transp. Res. Vaega A: Faiga Faʻavae., Vol. 64, pp. 14-31, 2014. https://doi.org/10.1016/j.tra.2014.02.019. [39] DW Hosmer ma S. Lemeshow, "Faʻaaogaina Logistic Regression. Lomiga Lua ”, New York: John Willey & Sons, 2000. https://doi.org/10.1002/0471722146. NOMENCLATURE j faalagolago fesuiaʻiga vaega (j = 1, 2, 3, 4, 5) k tutoʻatasi fesuiaʻiga vaega (k = 1, 2, 3,…, m) i agavaʻa tutoʻatasi fesuiaʻiga vaega ma okaina o tali β0j faʻalavelaveina tali taʻitasi o faʻamoemoe fesuiaʻiga Xk aofaʻiga tutoatasi fesuiaʻiga Xik quanlitative tutoatasi fesuiaʻiga Y faalagolago fesuiaʻiga Pj (Xn) le avanoa mo vasega taʻitasi o tutoatasi fesuiaʻi mo tali taʻitasi AUTHORS BIOGRAPHY Martha Widhi Dela Utami Martha Widhi Dela Utami o se tamaititi aoga aʻoga o Alamanuia Engineering Matagaluega o Universitas Sebelas Maret. O ia e aofia i le Logistics ma le Business System Laboratory. O ana suʻesuʻega fiafia i ai o loʻo faʻatulagaina & sapalai filifili pulega ma maketi suʻesuʻega. Na ia lomia faʻasalalau lana uluaʻi tusitusiga e uiga i le auiliiliga o le faʻaaogaina o le taʻavale eletise i Initonesia i le 2019. O Yuniaristanto Yuniaristanto o se faiaʻoga ma o se tagata suʻesuʻe i le Matagaluega o Alamanuia tau Inisinia, Universitas Sebelas Maret. O ana suʻesuʻega fiafia i ai o sapalai filifili, faʻataʻitaʻiga faʻataʻitaʻiga, faʻatinoga o galuega ma tekinolosi faʻapisinisi. O loʻo ia te ia lomiga na faʻasino e le Scopus, 41 tusitusiga ma le 4 H-index. O lana imeli o le yuniaristanto@ft.uns.ac.id. Wahyudi Sutopo Wahyudi Sutopo, o loʻo ia te ia le inisinia faʻapitoa tikeri (Ir) mai Suʻesuʻega Polokalama o Polofesa Inisinia - Universitas Sebelas Maret (UNS) i le 2019. Na ia mauaina lona Doctorate i le matata o Alamanuia Engineering ma Pulega mai Institut Teknologi Bandung (ITB) i 2011, Master of Science in Management mai Universitas Indonesia i le 2004 ma le Bachelor of Engineering in Industrial Engineering mai le ITB i le 1999. O ana suʻesuʻega fiafia i ai o oloa sapalai, inisinia tamaoaiga & tau faʻatauina, ma tekinolosi faʻapisinisi. Na ia mauaina le sili atu ma le 30 fesoasoani faʻapitoa mo suʻesuʻega. O loʻo ia te ia lomiga na faʻasino e le Scopus, 117 tusitusiga ma le 7 H-index. O lana imeli ole wahyudisutopo@staff.uns.ac.idO iʻuga o suʻesuʻega o loʻo faʻatonuina mo le fesuiaʻiga o ituaiga TE1 e oʻo atu i le TE5, o mea taua ia o loʻo faʻaalia mai ai, o taimi ole taimi e faʻaalu ai le maa (TE3) e iai sona aafiaga taua ile faʻaogaina o uila afi i Indonesia. O le taua taua mo agavaʻa agavaʻa (0.107) e le lagolagoina Hypothesis 16, agavaʻa agavaʻa e leai se taua aafiaga i luga o le faʻamoemoe e faʻaaoga se uila afi eletise. O le tau aoga mo se mileage sili ona maualuga o le 0.146, o le faʻailoga lelei o lona uiga o le sili atu ona talafeagai o le maualuga mileage o se uila afi eletise mo se tasi, o le maualuga le faʻamoemoe e vaʻaia se uila afi eletise. O le taua taua mo le tutoatasi fesuiaʻiga paoa poʻo le maualuga saosaoa (0.052) e le lagolagoina Hypothesis 17, maualuga saoasaoa e le matua aafia ai le faʻamoemoe e faaaoga se uila afi eletise. O le aoga o le malosi o le malosi poʻo le maualuga o le saoasaoa o le 0.167, o faʻailoga mautinoa o lona uiga o le sili atu ona talafeagai o le maualuga o le saoasaoa o le uila afi mo se tagata, o le maualuga foʻi lea o le faʻamoemoe e faʻaaogaina se uila afi eletise. O le taua taua mo le faʻatupeina o taimi (0.004) lagolagoina Hypothesis 18, taimi faʻatupeina ei ai se aafiaga taua i luga o le faʻamoemoe e faʻaaoga se uila afi eletise. O le tau fuafuaina mo le faʻatupeina o le taimi o le 0.240, faʻailoga mautinoa o lona uiga o le sili atu ona talafeagai le maualuga o le saoasaoa o se uila afi mo se tasi, o le maualuga o le faʻamoemoe e vaʻaia se uila afi eletise. O le taua taua mo le saogalemu (0.962) e le lagolagoina Hypothesis 19, saogalemu e le o aafia tele ai le faʻamoemoe e faaaoga se uila afi eletise. O le aoga o le tala faʻatatau mo le saogalemu o le -0.005, faʻailoga le lelei o lona uiga o le sili atu le saogalemu o se tasi e faʻaogaina le uila eletise, o le maualalo o le faʻamoemoe e vaʻaia se uila afi eletise. O le taua taua mo ola maa (0.424) e le lagolagoina Hypothesis 20, o le ola maa e leai se taua aafiaga i luga o le faʻamoemoe e faaaoga se uila afi eletise. O le aoga o le tala faʻatatau mo le ola maa o le 0.068, o le faʻailoga lelei o lona uiga o le sili atu ona talafeagai o le olaga atoa o se uila afi uila afi, o le maualuga le faʻamoemoe e vaʻaia se uila afi eletise. O iʻuga o suʻesuʻega o le toe faʻatonuina o loʻo lelei mo fesuiaʻiga ML1 i le ML7 o loʻo aofia ai i tulaga maualuluga o loʻo faʻaalia ai iʻuga e naʻo le totogiina o avanoa i falefaigaluega (ML2), faʻatupeina o avanoa i le nofoaga e nonofo ai (ML3), ma le faʻaeeina atu o tau faʻavae mo tau paʻu (ML7) e i ai aafiaga taua i le vaetamaina faʻamoemoe o uila eletise i Initonesia. O le taua taua mo le mauaina o avanoa i nofoaga faitele (0.254) e le lagolagoina le Hypothesis 21, o le faʻaavanoaina o avanoa i nofoaga faitele e le matua aʻafia ai le faʻamoemoe e faʻaaogaina eletise uila afi. O le taua taua mo le mauaina o avanoa i falefaigaluega (0,007) lagolagoina Hypothesis 22, molia maua i falefaigaluega ei ai le taua aafiaga i le faʻamoemoe o le taliaina o se uila afi uila afi. O le taua taua mo le mauaina o avanoa i se fale (0,009) lagolagoina Hypothesis 22, maua o le molia i le fale ei ai se aafiaga taua i le faʻamoemoe o le taliaina o se uila afi. O le taua taua mo le mauaina o nofoaga tautua (0.181) e le lagolagoina Hypothesis 24, o le mauaina o tautua nofoaga e leai se taua aafiaga i luga o le faʻamoemoe o le faʻaaogaina o se uila afi eletise. O le taua taua mo le faʻatauga faʻamalosi tulafono (0.017) lagolagoina le Masaniaga 25, faʻatauga faʻamalosia tulafono faʻatonutonu e i ai se aafiaga taua i luga o le faʻamoemoe o le taliaina o se uila afi eletise. O le taua aoga mo le lafoga faʻaletulafono lafoga faʻavae (0.672) e le lagolagoina Hypothesis 26, faaletausaga lafoga faʻamalosia tulafono faʻaititia e leai se taua aafiaga i le faʻamoemoe o le faʻaaogaina o se uila afi uila afi. O le taua taua mo le faʻatupeina o tau paʻu (0,00) lagolagoina le Hypothesis 27, o le totogiina o tau faʻaititia o tau faʻaititia, e i ai sona aafiaga taua i le faʻamoemoe e faʻaaoga se uila afi eletise. E tusa ai ma le iʻuga mai le macro-level factor, o le faʻaaogaina o uila afi eletise e mafai ona mautinoa pe a fai o le faʻatonuina o nofoaga i nofoaga o galuega, nofoaga e faʻatup