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All Journal Jurnal Pengabdian Masyarakat dan Riset Pendidikan Karya Nyata: Jurnal Pengabdian Kepada Masyarakat
Kelvin Andrean
Universitas Pamulang
Agriculture, Biological Sciences & Forestry Humanities Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Other

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Penerapan K-Means Klustering dengan Algoritma Kluster Dinamik untuk Meningkatkan Kualitas Kluster pada Segmentasi Dokter Potensial: Studi Kasus PT. XYZ: Penelitian Hari Setyawan; Jiyan Suhada; Kelvin Andrean
Jurnal Pengabdian Masyarakat dan Riset Pendidikan Vol. 4 No. 3 (2026): Jurnal Pengabdian Masyarakat dan Riset Pendidikan Volume 4 Nomor 3 (Januari 202
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jerkin.v4i3.4781

Abstract

The traditional K-Means algorithm has a significant weakness in its reliance on random cluster center initialization, which often results in unstable and suboptimal segmentation. This study aims to improve the quality of potential physician segmentation by proposing the integration of a dynamic clustering algorithm into the K-Means framework. The applied method is K-Means augmented with a dynamic clustering algorithm, using RFM (Recency, Frequency, Monetary) attributes derived from physician profile data. Cluster quality is evaluated using the Davies- Bouldin Index (DBI) and Purity. The proposed approach successfully improved segmentation accuracy by 25.15% compared to traditional K-Means. Quantitative analysis shows a significant improvement in cluster quality, indicated by a decrease in the DBI value from 0.846 to 0.411. Furthermore, the Purity value increased from 0.5294 to 0.7647, indicating improved cluster homogeneity. These results demonstrate that the dynamic clustering algorithm effectively addresses initialization sensitivity by iteratively adjusting cluster configurations based on inter- cluster and intra-cluster similarity. The final segmentation yielded four clusters of potential physicians with distinct RFM characteristics, enabling more targeted marketing strategies. The implementation of this model provides strategic benefits for pharmaceutical companies, including the ability to allocate promotional and sponsorship resources more efficiently based on a more accurate and reliable mapping of potential physicians.
Interactive Digital Story Learning Optimalisasi Literasi melalui Storytelling Berbasis Teknologi dan Aktivitas Gamifikasi di TBM Kolong Ciputat Nisak Ruwah Ibnatur Husnul; Kelvin Andrean; Muhammad Ikhwan Bayu Handono
Karya Nyata : Jurnal Pengabdian kepada Masyarakat Vol. 3 No. 3 (2026): September : Karya Nyata : Jurnal Pengabdian kepada Masyarakat
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/karyanyata.v3i3.3567

Abstract

The use of digital technology among children and adolescents has not always been accompanied by the ability to utilize it productively to support literacy activities. This condition was identified at TBM Kolong Ciputat, where participants’ digital activities still needed to be directed from information and entertainment consumption toward learning, interaction, and creative content production. This community service program aimed to optimize literacy through the implementation of Interactive Digital Story Learning, integrating technology-based storytelling and gamification. The activities were conducted participatively through needs identification, learning activity design, implementation of digital storytelling and gamification, digital content production, mentoring, and evaluation. Evaluation used pretest and posttest instruments covering access and technology use, information searching and processing, digital communication and collaboration, digital content production, and digital ethics and security. The results demonstrated an overall improvement in digital literacy, with the average score increasing from 58.40 in the pretest to 82.17 in the posttest, representing an increase of 23.77 points. The highest improvement occurred in digital content production, increasing from 55.00 to 82.50, or 27.50 points. The findings indicate that integrating technology-based storytelling and gamification increases participant engagement and encourages a shift in technology use from consumption toward creative and educational digital content production. This program has the potential to serve as an adaptive community-based literacy learning model for children and adolescents in digital environments.
Co-Authors Hari Setyawan Ibnatur Husnul, Nisak Ruwah Jiyan Suhada Muhammad Ikhwan Bayu Handono