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All Journal Bulletin of Electrical Engineering and Informatics Jurnal Teknologi Informasi dan Ilmu Komputer POSITIF JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Abdimas BSI: Jurnal Pengabdian Kepada Masyarakat Jurnal Ilmiah Matrik Martabe : Jurnal Pengabdian Kepada Masyarakat Informatik : Jurnal Ilmu Komputer SEINASI-KESI Jurnal Teknologi Informasi dan Pendidikan Technologia: Jurnal Ilmiah Jurnal Pendidikan dan Konseling PREPOTIF : Jurnal Kesehatan Masyarakat Journal of Intelligent Decision Support System (IDSS) Community Development Journal: Jurnal Pengabdian Masyarakat Journal of Applied Computer Science and Technology (JACOST) International Journal of Basic and Applied Science JITSI : Jurnal Ilmiah Teknologi Sistem Informasi Jurnal Pengabdian Teratai Madani : Jurnal Pengabdian Kepada Masyarakat Engagement: Jurnal Pengabdian Kepada Masyarakat ABDIKOM Informasi interaktif : jurnal informatika dan teknologi informasi
Erly Krisnanik
Universitas Pembangunan Nasional Veteran Jakarta
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Mathematics Physics Public Health Social Sciences Other

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Journal : International Journal of Basic and Applied Science

 1 
Classification of stunting for early childhood in indramayu using machine learning methods Krisnanik, Erly; Cholil, Widya; Adrezo, Muhammad; DP, Catur Nugrahaeni; Binti Mohamad, Mumtazimah
International Journal of Basic and Applied Science Vol. 14 No. 2 (2025): Optimization and Computer Science
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/ijobas.v14i2.833

Abstract

The stunting prevalence rate in 2020 of the Ministry of Health of the Republic of Indonesia was 38.9%. The stunting prevalence rate in Central Java itself is 33.9%, of which 17.0% are stunted and 16.9% are very short. The purpose of the study is to obtain valid data on the factors causing stunting and carry out the classification process quickly. The method used in this study is machine learning by comparing three algorithms, namely: SVM, KNN and Random Forrest. The results of this study are said that the average calculation of the accuracy level of early childhood stunting data using SVM and KNN is above 80% and Random Forrest is below 80%. While the calculation results of the average precision value of 84% and recall value of 80% using SVM, the average precision value of 95% and the recall value of 91% using KNN with K = 1, and the average precision value of 87% and the recall value of 52% using Random Forrest.  The conclusion of the comparison between SVM, Random Forest and KNN methods to calculate precision and recall values can be said that KNN is better with K = 1 close to 100%.
KMS for overcoming stunting in early childhood and pregnant women using the Soft System Methodology (SSM) with the Learning Lesson System (LLS) approach Krisnanik, Erly; Adrezob, Muhammad; Kraugusteeliana, Kraugusteeliana; Yulistiawan, Bambang Saras; Susramae, I Gede
International Journal of Basic and Applied Science Vol. 14 No. 3 (2025): Optimization and Artificial Intelligence
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/ijobas.v14i3.834

Abstract

This study addresses the concerning prevalence of stunting among early childhood and pregnant women in Indramayu Regency, which reached 18.4% in 2024, exceeding the national target of 14%. It aims to develop a Knowledge Management System (KMS) to support integrated stunting control efforts by employing Soft Systems Methodology (SSM) for comprehensive problem identification and the Learning Lesson System (LLS) to incorporate proven best practices. The KMS is designed to optimize information distribution regarding the causes, impacts, and interventions for the stunting issue, while enhancing collaboration among government, community, and families. The integration of SSM and LLS allows the system to adapt to changing local conditions and needs, providing relevant, evidence-based information. This research result suggests that the implementation of KMS can significantly improve the effectiveness of health policies and intervention programs at reducing stunting, particularly among vulnerable populations. However, questions remain regarding the specific features of the KMS, the implementation strategy within communities, and the evaluation measures for assessing its long-term effectiveness in combating stunting.
Co-Authors Adrezob, Muhammad Airlambang, Dwiki Anita Muliawati Artika Arista Atika, Rifdah Diah Ayasha Zahwa Bambang Saras Yulistiawan Bambang Saras Yulistiawan Bambang Yuwono Bandiyani, Mia Setya Binti Mohamad, Mumtazimah Catur Nugrahaeni Puspita Dewi Deni Mahdiana Devi, Ramla Shantika DP, Catur Nugrahaeni Duma Lumban Tobing Fikastiana Cahya Firyal, Hana Hananto, Bayu Helena Nurramdhani Irmanda Hesti Indriana, Intan Husna, Kholifatul I Wayan Widi Pradnyana I Wayan Widi Pradnyana Indriasari, Vini Intan Hesti Indriana Intan Hesti Indriana Kamila, Alya Hasna Keka, Christyani Rannu Kesuma, Lucky Indra Kraugusteeliana Kraugusteeliana Kusumawardhani, Damar Lomo Mula Tua Luthfi Jatmiko Nugroho Mardiah Matondang, Nurhafifah Maulita, Wike Mawar Melly Kristanti Mirza Rabbani Kobandaha Muhammad Adrezo Muliawai, Anita Nadia Mustika Sari Naraloka, Therezia Naturesa, Ferena Titan Noor Falih Nurramdhani, Helena Pankrasius Aryo Wicaksono Pinastika, I Wayan Rangga Putra Arianto Putri, Jasmin Maula Rahmawan, Fauzan Ahmat Ramadhani, Nadya Rudhy Ho Purabaya Saputra, Rezi Sephira, Qinthara Sharhana, Masayu Heppy Siahaan, Sekar Griselda Nadine Siti Khusnul Khotimah, Siti Khusnul Supriyanto Susramae, I Gede Sutomo, Muhammad Syamsiar, Syamsiar Tambun, Kraugusteeliana Theresiawati Tjahjanto , Tahjanto Tjahjanto Tjahjanto Tjahjanto, Tjahjanto Tri Rahayu Tri Rahayu Tri Rahayu Tri Rahayu Tri Wahyono , Bambang Triyanto, Alzidan Arif Uli, Tresia Shinta Wahyuni, Yosha Putri Widiastiwi, Yuni Widya Cholil Wijayanti Mulia, Dina Mukti Wirawan, Rio Yosef Adityanto Aji Yulistiawan, Bambang Saras Yulnelly Yulnelly Yulnelly Yulnelly Yulnelly, Yulnelly Yuniar, Erina Zaidiah, Ati