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All Journal Scientific Journal of Informatics Jurnal Edik Informatika : Penelitian Bidang Komputer Sains dan Pendidikan Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Georafflesia : Artikel Ilmiah Pendidikan Geografi Jurnal Ipteks Terapan J SIG (Jurnal Sains Informasi Geografi) JOISIE (Journal Of Information Systems And Informatics Engineering) Jurnal Ekonomi Jurnal Teknologi Dan Sistem Informasi Bisnis JTIK (Jurnal Teknik Informatika Kaputama) TIN: TERAPAN INFORMATIKA NUSANTARA Majalah Ilmiah UPI YPTK Jurnal Ipteks Terapan : research of applied science and education pendidikan, science, teknologi, dan ekonomi Jurnal Hasi Penelitian Dan Pengkajian Ilmiah Eksakta - JPPIE Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi) Jurnal Sains dan Teknologi Jurnal Pemberdayaan: Publikasi Hasil Pengabdian kepada Masyarakat (JPM ITTC ) Jurnal Sains dan Informatika : Research of Science and Informatic Jurnal Pengabdian Masyarakat Dharma Andalas Jurnal Sistem Informasi dan Informatika
Renita Astri
Universitas Dharma Andalas
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Serendipity-Aware Decision Support System Using Entropy-Weighted Hybrid GA-PSO Ahmad Kamal; Suaini Binti Sura; Lai Po Hung; Renita Astri; Johan Johan
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 10 No 3 (2026): Juni 2026
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v10i3.7668

Abstract

The rapid growth of social commerce has intensified competition among online handicraft businesses, making effective store planning increasingly important. While most studies focus on consumer recommendation systems, limited research supports entrepreneurs during the early stage of store configuration. This study proposes a serendipity-aware Decision Support System (DSS) for handicraft store planning using an entropy-weighted hybrid Genetic Algorithm–Particle Swarm Optimization (GA-PSO). A dataset of 105 handicraft stores in West Sumatra was encoded into 19-bit chromosomes representing materials, product types, location, and digital commerce visibility. Entropy-based weighting objectively determined attribute importance without subjective judgment. GA explored store configurations, while PSO optimized evolutionary parameters to balance preference similarity and serendipitous exploration. The proposed framework generated store configurations superior to those in the original dataset. The best solution achieved a preference similarity score of P(x)=0.9108, outperforming the best existing store (P(x)=0.8513) by 6.99%. The hybrid GA-PSO also showed stable performance across multiple runs, indicating robust convergence. This study contributes a data-driven DSS framework integrating entropy weighting, hybrid GA-PSO optimization, and serendipity-aware exploration for entrepreneurial decision support in social commerce.
Co-Authors ,, Isnardi ., Faradika A, M. Razi Ahmad Kamal Ahmad Kamal ahmad kamal Ahmad Kamal Ahmad Kamal Ahmad Kamal ahmad kamal, ahmad Anggraini, Putri Anggraini, Putri Azman, Heru Aulia Binti Sura, Suaini Faradika Dika Faradika, Faradika Indrayeni, Indrayeni Isnardi , Johan Johan Lai Po Hung Lusia, Siska Marcellino, Anggit Mariyanti, Eka Mazni, Deni Irda Mohammad Abdilla Mulya, Dio Prima Nasrah, Rasidah Po Hung, Lai Randi Yudha Pratama Saputra, David Srihasnita, Rita Suaini Binti Sura Sularno Sularno Sularno Sularno Sularno, Sularno Utnasari, Intan Vitri, Gusni Yanni Suherman Zulfahmi - Zulfahmi . Zulfahmi Fahmi Zulfahmi Zulfahmi