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All Journal E-Dimas: Jurnal Pengabdian kepada Masyarakat Prosiding Seminar Nasional Teknoka Jurnal Nasional Komputasi dan Teknologi Informasi STRING (Satuan Tulisan Riset dan Inovasi Teknologi) Jurnal Ilmu Komputer dan Bisnis JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Jurnal ABDIKU International Journal of Business and Information Technology Jurnal Riset dan Aplikasi Mahasiswa Informatika (JRAMI) Aptekmas : Jurnal Pengabdian Kepada Masyarakat Jurnal Ilmiah Teknik Mesin, Elektro dan Komputer (JURITEK) Jurnal Rekayasa Komputasi Terapan Kapas: Kumpulan Artikel Pengabdian Masyarakat Seminar Nasional Riset dan Teknologi (SEMNAS RISTEK)
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Journal : JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH)

 1 
Pengembangan Model Decision Tree Menggunakan Particle Swarm Optimization untuk Klasifikasi Popularitas, Infrastruktur, dan Potensi Pasar Wilayah Jabodetabek Ambarsari, Erlin Windia; Kustian, Nunu; Mardika, Putri Dina
Journal of Information System Research (JOSH) Vol 6 No 4 (2025): July 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i4.7216

Abstract

Traditional markets play a vital role in local economies; however, they face challenges related to competitiveness, infrastructure quality, and legal operational status. This study aims to develop a classification model for traditional markets in the Greater Jakarta (Jabodetabek) region based on three main aspects: popularity, infrastructure readiness, and market potential. The model utilizes a Decision Tree (DT) algorithm optimized with Particle Swarm Optimization (PSO) to enhance classification accuracy while maintaining model interpretability. The dataset comprises 1,253 market entries with 15 predictive features. The classification model categorizes markets into popular or unpopular, infrastructure-ready or not-ready, and potential or non-potential groups. Experimental results demonstrate that the model achieves an average accuracy of 97.48%. Key factors influencing the classification outcomes include the number of vendors, the availability of basic facilities (electricity, clean water, toilets, and drainage), the age of the market, and the presence of an official operating license (IUP2T). The findings provide valuable insights for local governments and policymakers to prioritize market revitalization efforts based on data-driven classification results. Furthermore, this study opens future research opportunities to integrate spatial data and real-time market analytics to improve classification accuracy further and support more adaptive and effective policy-making.
Co-Authors Aan Risdiana Adha, Muhammad Faisal Agus Darmawan Agus Setiawan Anugrahni, Asih CLEOPATRA, MARIA Dudi Parulian Ek Ajeng Rahmi Pinahayu Erlin Windia Ambarsari Fathudin, Dedin Fathur, Aji Frasdica Fujianto Nugraha Hidayatullah, Reko Syarif Irfan Ismunandar JUHRIAH, EEN khusnul khotimah Mardiana Mardiana Mochamad Rizki Adityo mufti, abdul Muhammad Tri Habibie Ningsih, Retna Nirwana, Bunga Niswati, Za’imatun Parulian, Dudi Pinahayu, Ek Ajeng Pramarta, Pandhu Prayogo, Rachmad Danu Putri Dina Mardika Rahayu, Wanti Retna Ningsih Ridwan, Rizki Risma Nurul Auliya Rizki Ridwan Rizki Ridwan Rudi Prasetya Saputra, Sendy Alfigo Yoga Saputro, Bambang Adi Siti Julaeha Siti Julaeha Siti Julaeha, Siti Sonny, Michael Syafrudin, Nita Najiah Syahputra, Fadel Maulana Triyono, Anugrah Hendri Wanti Rahayu Wanti Rahayu Wulan Anggraeni