Analisis Pola Pembelian Mobil di Indonesia Menggunakan Metode ID3

Authors

  • Maria Yohana Gabriela Sasi STIKOM Uyelindo Kupang
  • Yampi R Kaesmetan STIKOM Uyelindo Kupang

DOI:

https://doi.org/10.55123/jumintal.v4i1.5352

Keywords:

Car, Entropy, Gain, Indonesia, ID3 Method

Abstract

Indonesia's geographical conditions consisting of islands encourage the need to develop efficient transportation, especially automotive, to improve the country's economy. Cars are seen as safer vehicles than motorbikes, and with the increasing number of automotive companies, competition in the market is getting tighter. Car sales, especially from brands such as Toyota, Honda, and Mitsubishi, have shown rapid growth, with Toyota recording sales growth of 6.5% and Honda increasing by 56% in 2023. This condition requires companies to understand consumer needs and implement the right business strategies. The comfort and quality of the car are the main priorities in choosing a vehicle, although price is also an important consideration. With the growth of marketing through social media, the expected data can be used for further analysis, so that manufacturers can improve the quality of their products. The purpose of using the ID3 Method (Iterative Dichotomiser 3) as an algorithm to explore patterns in car purchasing decisions in Indonesia, given its ability to form decision trees that can reflect alternative choices and decision results. This study aims to analyze car purchase data and provide more insight into consumer preferences in the context of the Indonesian automotive market

Downloads

Download data is not yet available.

References

Santosa, B. (2014) ‘Algoritma Iterative Dichotomiser 3 (ID3) untuk Pengambilan Keputusan’, Jurnal Teknologi Informasi, 10(2), pp. 45–52. Available at: https://media.neliti.com/media/publications/59658-ID-algoritma-iterative-dichotomizer-3-id3-p.pdf

Jayapana, R.D. & Yuniarsi, R. (2015) ‘Analisis Pola Pembelian Konsumen dengan Algoritma Apriori pada Apotek Rahayu Jepara’, UG Jurnal, 8, pp. 1–10. Available at: https://core.ac.uk/download/pdf/35381950.pdf

Wianto, P.W.A. (2018) ‘Analisis Sentimen Media Sosial untuk Teks Berbahasa Indonesia Menggunakan Algoritma CNN (Convolutional Neural Network) (Studi Kasus: Politik)’, Skripsi, Institut Teknologi Sepuluh Nopember. Available at: https://repository.its.ac.id/52593/

Utomo, D.P. & Mesran. (2020) ‘Analisis Komparasi Metode Klasifikasi Data Mining dan Reduksi Atribut pada DataSet Penyakit Jantung’, Jurnal Media Informatika Budidarma, 4(2), pp. 437–444. Available at: https://ejurnal.stmik-budidarma.ac.id/mib/article/view/2080/1541

Rahim, A. & Jusia, P.A. (2024) ‘Prediksi Mahasiswa Berpotensi Non-Aktif Menggunakan Algoritma Decision Tree Classifier’, Indonesian Journal of Computer Science, 13(1), pp. 1308–1322. Available at: https://ijcs.net/ijcs/index.php/ijcs/article/view/3692

Kohsasih, R.A. (2022) ‘Analisis Sentimen Produk Permainan Menggunakan Metode TF-IDF dan Algoritma K-Nearest Neighbor’, Jurnal Nasional Informatika dan Teknologi Jaringan, 6(1), pp. 134–139. Available at: https://repository.horizon.ac.id/items/show/3362

Pratama, D.A.P., Nugraha, N.S., Maulana, R., Rahmasari, A. & Fauzi, A. (2021) ‘Implementasi Algoritma ID3 untuk Klasifikasi Kualitas Mobil’, Proceedings of the Global Digital Communication Symposium (GDCS). Available at: https://www.conferences.uinsgd.ac.id/index.php/gdcs/article/view/97

Hendra, F. (2017) ‘Analisis Tingkat Kematangan Industri Komponen Otomotif di Indonesia’, SINTEK JURNAL: Jurnal Ilmiah Teknik Mesin, 11(1), pp. 38–48. Available at: https://jurnal.umj.ac.id/index.php/sintek/article/view/1473

KL, & Kotler, P. (2022). Branding dalam perusahaan B2B. Dalam Handbook of business-to-business marketing (hlm. 205-224). Edward Elgar Publishing.

David, MCG (2004) Tutorial Algoritma Pohon Keputusan ID3 , Fakultas Teknologi Informasi Universitas Monash. Available at https://books.google.co.id/books?id=zLHGEAAAQBAJ&printsec=frontcover&hl=id&source=gbs_ge_summary_r&cad=0#v=onepage&q&f=false

Han, J. & Kamber, M. (2006) Data Mining: Concepts and Techniques , Morgan Kaufmann Publishers, San Francisco. Available at https://liacs.leidenuniv.nl/~bakkerem2/dbdm2012/03_dbdm2012_Data.pdf

Hendra, F. (2017) 'Analisis Tingkat Kematangan Industri Komponen Otomotif di Indonesia', SINTEK JURNAL: Jurnal Ilmiah Teknik Mesin, 11(1), pp.38–48. Available at : https://jurnal.umj.ac.id/index.php/sintek/article/view/1473 .

Hikmatulloh, RAWD & Ambarsari, DA (2019) 'Penerapan Algoritma Iterative Dichotomiser Three (ID3) Dalam Mendiagnosa Kesehatan Kehamilan', Jurnal Ilmu Komputer, 6(2), pp.116–127. Available at https://www.academia.edu/download/101003403/pdf.pdf

Isnawati, SIPMI & Bangsa, JR (2023) 'Pelatihan Konten Marketing Pada Industri Otomotif Dengan Media Video Marketing Di PT Wahana Investasindo Salatiga', Jurnal Abadimas Adi Buana, 6(2), pp.240–247. Available at https://jurnal.unipasby.ac.id/index.php/abadimas/article/view

https://industri.kontan.co.id/news/honda-raih-kenaikan-penjualan-retail-58-pada-oktober-2024)

https://otomotif.bisnis.com/read/20241026/46/1810861/gaikindo-pangkas-target-penjualan-mobil-honda-sebut-lebih-realistis)

Downloads

Published

2025-05-20

How to Cite

Maria Yohana Gabriela Sasi, & Yampi R Kaesmetan. (2025). Analisis Pola Pembelian Mobil di Indonesia Menggunakan Metode ID3. JUMINTAL: Jurnal Manajemen Informatika Dan Bisnis Digital, 4(1), 85–99. https://doi.org/10.55123/jumintal.v4i1.5352

Issue

Section

Articles