Program Aplikasi Website Pemilihan Sepeda Motor Listrik Berdasarkan Metode TOPSIS di Wilayah Jakarta Barat
DOI:
https://doi.org/10.55606/jutiti.v6i2.7410Keywords:
Decision Support System, Electric Motorcycle, Next Js, TOPSIS, West JakartaAbstract
The rapid growth of Indonesia’s electric motorcycle market, particularly in West Jakarta, has made consumer decision-making more complex due to the many available alternatives and evaluation criteria. This study aims to develop a web-based decision support system (DSS) for selecting electric motorcycles using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method. Data were obtained through questionnaires distributed to 68 respondents with experience using electric motorcycles in West Jakarta, selected through purposive sampling based on the Cochran formula at a 90% confidence level. Six criteria were applied, namely purchase price, travel range, battery capacity, maximum speed, charging time, and after-sales service, all treated as benefit criteria according to the Likert-scale perception instrument. The system was developed using Next js, JavaScript, and a MySQL/MariaDB database. TOPSIS analysis ranked Polytron Fox 350 first with a preference value of 0.7938, followed by ALVA N3 and Honda CUV e:. Validation through unit, black-box, and end-to-end testing confirmed that the system outputs matched manual calculations.
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Agustina, R., Yuniaristanto, & Sutopo, W. (2025). Factors influencing electric motorcycle adoption in Indonesia: Comprehensive psychological, situational, and contextual perspectives. World Electric Vehicle Journal, 16(2), 1–21. https://doi.org/10.3390/wevj16020106
Ahmed, S. K. (2024). How to choose a sampling technique and determine sample size for research: A simplified guide for researchers. Oral Oncology Reports, 12, 100662. https://doi.org/10.1016/j.oor.2024.100662
Aqmarina, S. N., Nurcahyo, R., & Sumaedi, S. (2024). Accelerating electric motorcycle adoption: Comparison between users and non-users perspectives in Jakarta, Indonesia. TEM Journal, 13(2), 1633–1644. https://doi.org/10.18421/TEM132-76
Ayuningrum, R. (2024). Populasi motor listrik di Indonesia tembus 172 ribu unit. Detikfinance. https://finance.detik.com/industri/d-7615235/populasi-motor-listrik-di-indonesia-tembus-172-ribu-unit
Ccatamayo-Barrios, J. H., Huamán-Romaní, Y. L., Seminario-Morales, M. V., Flores-Castillo, M. M., Gutiérrez-Gómez, E., Carrillo-De la Cruz, L. K., & de la Cruz-Girón, K. A. (2023). Comparative analysis of AHP and TOPSIS multi-criteria decision-making methods for mining method selection. Mathematical Modelling of Engineering Problems, 10(5), 1665–1674. https://doi.org/10.18280/mmep.100516
Chakraborty, P., Parker, R., Hoque, T., Cruz, J., Du, L., Wang, S., & Bhunia, S. (2022). Addressing the range anxiety of battery electric vehicles with charging en route. Scientific Reports, 12, 1–15. https://doi.org/10.1038/s41598-022-08942-2
Ciardiello, F., & Genovese, A. (2023). A comparison between TOPSIS and SAW methods. Annals of Operations Research, 325(2), 967–994. https://doi.org/10.1007/s10479-023-05339-w
French, S. (2023). Reflections on 50 years of MCDM: Issues and future research needs. EURO Journal on Decision Processes, 11, 100030. https://doi.org/10.1016/j.ejdp.2023.100030
Gilang, R., Himawan, I., & Siregar, M. A. H. (2025). Sistem pendukung keputusan rekomendasi pemilihan sepeda motor listrik PT Innolab Sains International dengan metode SAW (Simple Additive Weighting). Jurnal Gateway, 1(1), 17–31. https://ejurnal.umiba.ac.id/index.php/GATEWAY/article/view/38
Hidayat, H. R., Irawan, M. Z., Rizki, M., & Aurarisa, I. (2025). Exploring the determinants of electric motorcycle adoption and changes in travel behavior: Insights from Indonesia. Travel Behaviour and Society, 42, 101121. https://doi.org/10.1016/j.tbs.2025.101121
Humaira, Z., Ariandi, M. I., Qur’ania, A., & Teguh, P. N. (2024). Multi-objective optimization by ratio analysis (MOORA) method for decision support system in selecting the best electric car. Indonesian Journal of Statistics and Its Applications, 8(2), 129–131. https://doi.org/10.29244/ijsa.vxiypno
Kementerian Lingkungan Hidup. (2025). Jabodetabek alarm polusi: KLH/BPLH bergerak serentak, tak ada ruang bagi pencemar udara. Kementerian Lingkungan Hidup. https://kemenlh.go.id/news/detail/jabodetabek-alarm-polusi-klhbplh-bergerak-serentak-tak-ada-ruang-bagi-pencemar-udara
Loganathan, M. K., Mishra, B., Tan, C. M., Kongsvik, T., & Rai, R. N. (2020). Multi-criteria decision making (MCDM) for the selection of Li-ion batteries used in electric vehicles (EVs). Materials Today: Proceedings, 41, 1073–1077. https://doi.org/10.1016/j.matpr.2020.07.179
Maharani, P. (2025). Pengembangan website PT. Rantangin Digital Indonesia menggunakan framework Next.js dan Tailwind CSS. Repeater: Publikasi Teknik Informatika dan Jaringan, 3(1), 129–137. https://doi.org/10.62951/repeater.v3i1.355
Minarwati, Rahman, T. A., & Shimbun, A. F. (2024). Penerapan metode TOPSIS pada sistem pendukung keputusan berbasis web penilaian kinerja guru. FAHMA: Jurnal Informatika Komputer, Bisnis dan Manajemen, 22(2), 82–93. https://doi.org/10.61805/fahma.v22i2.136
Nguyen-Phuoc, D. Q., Nguyen, N. A. N., Tran, P. T. K., Pham, H. G., & Oviedo-Trespalacios, O. (2023). The influence of environmental concerns and psychosocial factors on electric motorbike switching intention in the global south. Journal of Transport Geography, 113, 103705. https://doi.org/10.1016/j.jtrangeo.2023.103705
Nugroho, S. A. (2024). Infrastruktur dan range anxiety jadi faktor penghambat pertumbuhan EV di Indonesia. Oto.com. https://www.oto.com/berita-mobil/infrastruktur-dan-range-anxiety-jadi-faktor-penghambat-pertumbuhan-ev-di-indonesia
Nurhuda, S. F. (2024). Populasi kendaraan listrik di Indonesia dekati 200 ribu unit. Detikoto. https://oto.detik.com/mobil-listrik/d-7673932/populasi-kendaraan-listrik-di-indonesia-dekati-200-ribu-unit
Okfalisa, Mahyarni, Anggraini, W., Saktioto, & Pranggono, B. (2022). Assessing digital readiness of small medium enterprises: Intelligent dashboard decision support system. International Journal of Advanced Computer Science and Applications, 13(4), 98–108. https://doi.org/10.14569/IJACSA.2022.0130412
Ryando, M. B., Mariana, A. R., & Hakim, R. A. (2023). Sistem pendukung keputusan pemilihan sepeda motor second terbaik di kelas matic 150cc menggunakan metode AHP dan TOPSIS. Academic Journal of Computer Science Research, 5(1), 47–59. https://doi.org/10.38101/ajcsr.v5i1.611
Savitri, P. I. (2026). Harga minyak dunia melonjak dampak perang Iran, bagaimana dampaknya ke harga BBM subsidi? ANTARA News Aceh. https://aceh.antaranews.com/berita/402219/harga-minyak-dunia-melonjak-dampak-perang-iran-bagaimana-dampaknya-ke-harga-bbm-subsidi
Sidqi, M. A. (2026). Efek domino perang di Timur Tengah: Ketergantungan BBM ancam ekonomi Indonesia. Katadata. https://katadata.co.id/analisisdata/69cd9f5ac6dc7/efek-domino-perang-di-timur-tengah-ketergantungan-bbm-ancam-ekonomi-indonesia
Simanjuntak, R. L., Siagian, T. R., & Anggriani, V. (2024). Sistem pendukung keputusan menggunakan metode TOPSIS dalam pemilihan smartphone Android. Jurnal Ilmiah Komputasi, 23, 405–412. https://doi.org/10.32409/jikstik.23.3.3610
Soerjopranoto, F., Rokhim, R. K., & Balqiah, T. E. (2025). How dealer characteristics moderate the impact of government policy on electric vehicle adoption in Indonesia. IEEE Access, 13, 180725–180738. https://doi.org/10.1109/ACCESS.2025.3596485
Sugiyono. (2013). Metode penelitian kuantitatif, kualitatif, dan R&D. Alfabeta.
Teta, B. (2025). Pengaruh kemudahan pengguna terhadap niat menggunakan aplikasi Indrive. Jurnal Visi Ekonomi Akuntansi dan Manajemen, 7(2), 43–50.
Turban, E., Sharda, R., Delen, D., Aronson, J. E., Liang, T.-P., & King, D. (2011). Decision support and business intelligence systems (9th ed.). Prentice Hall.
Vercel. (n.d.). Next.js documentation. https://nextjs.org/docs
Wallace, P. (2015). Introduction to information systems (2nd ed.). Pearson Education Limited.
Wang, Y., & Witlox, F. (2025). Global trends in electric vehicle adoption and the impact of environmental awareness, user attributes, and barriers. Energy Reports, 13, 1125–1137. https://doi.org/10.1016/j.egyr.2024.12.054
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