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All Journal JATI (Jurnal Mahasiswa Teknik Informatika) Jurnal Informatika Teknologi dan Sains (Jinteks) Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi) Journal of Artificial Intelligence and Engineering Applications (JAIEA) AMMA : Jurnal Pengabdian Masyarakat
Martanto
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Humanities Automotive Engineering Chemistry Computer Science & IT Control & Systems Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Nursing

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Pelatihan Pembuatan Toko Online Berbasis Marketplace untuk Pemberdayaan Ibu Rumah Tangga Khaerul Anam; Martanto; Azzahra Moudy Fajria; Bagus Hermawan
AMMA : Jurnal Pengabdian Masyarakat Vol. 1 No. 04 (2022): AMMA : Jurnal Pengabdian Masyarakat
Publisher : CV. Multi Kreasi Media

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Abstract

This community service program aims to empower housewives through the creation and management of online stores based on marketplaces. This activity is motivated by the great potential of e-commerce in providing time flexibility and additional economic opportunities for housewives. The implementation method includes intensive training on online store creation, product management, digital marketing, and customer service. As a result, participants are able to create their own online stores and manage their operations well. This program provides a practical solution for housewives to increase income and economic independence. Further assistance and program expansion are recommended to reach more participants.
K-Means Algorithm for Clustering High-Achieving Student at Madrasah Tsanawiyah Yami Waled Muhammad Hilman; Martanto; Dikananda, Arif Rinaldi; Rifai, Ahmad
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 4 No. 3 (2025): June 2025
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v4i3.771

Abstract

This study aims to apply the K-Means algorithm to cluster students based on their mathematics grades at Madrasah Tsanawiyah Islamiyyah Yami Waled. By categorizing students into clusters of low, medium, and high academic achievement, the institution can develop more effective and targeted learning strategies. The data consisted of semester mathematics grades from 112 students, analyzed using the K-Means clustering algorithm. Clusters were evaluated using the Davies-Bouldin Index (DBI), with results showing three distinct clusters: Cluster 0 (low achievers, 54 students), Cluster 1 (medium achievers, 37 students), and Cluster 2 (high achievers, 21 students). The DBI score of 0.893 indicates good clustering quality, providing valuable insights for personalized learning approaches.
Optimization of Kebaya Product Grouping Using K-Means Algorithm for Marketing Strategy of Rental Services at Gifaattire Store Nuraeni; Martanto; Dikananda, Arif Rinaldi; Rifai, Ahmad
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 4 No. 3 (2025): June 2025
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v4i3.776

Abstract

This study aims to implement the K-Means algorithm to improve the kebaya clustering model to support the rental marketing strategy at Gifaattire Store. The K-Means algorithm was used to analyze eight months of historical kebaya rental data, focusing on the attributes of kebaya type and color. Using the Knowledge Discovery in Database (KDD) approach, the research conducted data selection, preprocessing, transformation, data mining, and evaluation of clustering results. Davies-Bouldin Index (DBI) was utilized to assess the quality of clustering, resulting in an optimal value of 6 clusters with a DBI of 0.580. The results showed that each cluster has unique characteristics that reflect customer demand patterns. Cluster 0, the largest cluster, indicates kebayas with high demand but limited color variations. In contrast, Cluster 1 indicates kebayas with a wide variety of colors but specific demand. This information enables Gifaattire Store to design more targeted data-driven marketing strategies and improve stock management efficiency. The research contributes to the development of literature on the application of K-Means in the fashion rental sector and offers practical insights into understanding customer preferences.
Co-Authors Ahmad Rifai Ahmad Rifai Ahmad Rifa’i Arif Budi Setiawan Arif Rifaldi Dikananda Arif Rinaldi Dikananda Arif Rinaldi Dikanda Artoti, Azzahra Rizky Ayu Febrian Lesmana, Alfira Azzahra Moudy Fajria Bagus Hermawan Candra, Candra Rahmawati Dadang Sudrajat Dede Rohman Dian Ade Kurnia Dikananda, Arif Rinaldi Dikananda, Fatihanursari Fahmi Naufal Fatihanursari Dikananda Hanifah Nur Aulia Hayati, Umi Hery Widijanto Ica, Ica Pandia Ika Riantika Irfan Ali Jannah, Eka Roehatul Jayawarsa, A.A. Ketut Laylatunna'imah Masdarul Rizqi Muhamad Abdul Fatah Muhammad Hilman Mulyawan Nasakh Nuraeni Pamungkas, Vicky Rai Fatkaozi, Ahmad Ramadan, Muhamad Firly Rano Renaldi , Betran Ridho Nugraha Rifa'i, Ahmad Rohayati, Eti Rohman, Dede Rudi Kurniawan Satria Turangga Wahyudin, Edi Wiratriyana Yudhistira Arie Wijaya