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All Journal Jurnal Edukasi dan Penelitian Informatika (JEPIN) CESS (Journal of Computer Engineering, System and Science) Sistemasi: Jurnal Sistem Informasi Sinkron : Jurnal dan Penelitian Teknik Informatika JOURNAL OF APPLIED INFORMATICS AND COMPUTING JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Jurnal Teknologi Sistem Informasi dan Aplikasi JOURNAL OF SCIENCE AND SOCIAL RESEARCH Journal of Information Systems and Informatics JTIK (Jurnal Teknik Informatika Kaputama) Journal of Applied Science, Engineering, Technology, and Education Journal of Computer Networks, Architecture and High Performance Computing Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Jurnal IPTEK Bagi Masyarakat Journal of Computer Science and Informatics Engineering Edu Society: Jurnal Pendidikan, Ilmu Sosial dan Pengabdian Kepada Masyarakat Malcom: Indonesian Journal of Machine Learning and Computer Science
Fakhriza, M.
Unknown Affiliation
Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Industrial & Manufacturing Engineering Mechanical Engineering Physics Public Health Social Sciences Other

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Penerapan Metode Double Exponential Smoothing untuk Pemberdayaan Apotek melalui Sistem Prediksi Penjualan Vitamin Dayatila, Nada; Fakhriza, M.; Nasution, Adnan Buyung
Jurnal IPTEK Bagi Masyarakat Vol 5 No 2 (2025)
Publisher : Ali Institute of Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/j-ibm.v5i2.1261

Abstract

Penjualan vitamin di Apotik Pandu Jaya perlu diprediksi secara akurat untuk mencegah terjadinya kelebihan maupun kekurangan stok yang dapat menimbulkan kerugian. Penelitian ini bertujuan merancang dan mengembangkan aplikasi berbasis web yang mampu melakukan prediksi penjualan vitamin selama empat bulan ke depan sebagai dasar pengambilan keputusan pengelolaan persediaan. Data yang digunakan berupa catatan historis penjualan vitamin pada Apotik Pandu Jaya dengan rentang waktu tertentu yang diolah secara runtut. Metode yang diterapkan adalah Double Exponential Smoothing (DES) dengan proses optimasi parameter α (alpha) dan β (beta) untuk memperoleh hasil peramalan paling akurat. Evaluasi kinerja model dilakukan menggunakan metrik Root Mean Square Error (RMSE) dan Mean Absolute Percentage Error (MAPE). Hasil pengujian menunjukkan bahwa model DES dengan parameter optimal menghasilkan nilai error yang relatif kecil (RMSE = 61.96289), sehingga prediksi empat bulan ke depan memperlihatkan tren penjualan yang meningkat secara stabil. Temuan ini menunjukkan bahwa sistem prediksi berbasis web yang dikembangkan dapat menjadi alat bantu efektif bagi manajemen apotek dalam merencanakan kebutuhan stok, mengurangi risiko kerugian, serta mendukung strategi pengadaan yang lebih efisien.
Clustering Modeling of Divorce-Causing Factors Using the K-Means Algorithm Hasibuan, Salsabila Arifa; Fakhriza, M.
MALCOM: Indonesian Journal of Machine Learning and Computer Science Vol. 6 No. 4 (2026): MALCOM October 2026
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/malcom.v6i4.3011

Abstract

The increasing divorce rate in North Sumatra is a complex social problem. Traditional policy approaches often generalize root causes across regions, especially by assuming economic issues as the main trigger. Unlike previous studies that group regions solely by geographical proximity or raw case volume, this research introduces a novel approach that clusters regions based on interaction patterns among substantive causal variables. This research applies the K-Means clustering algorithm to map the dominant factors contributing to divorce across 33 districts/cities in North Sumatra, using 2023-2025 Statistics Indonesia (BPS) data. The clustering model was evaluated using the Elbow Method and Davies-Bouldin Index (DBI). The optimal evaluation resulted in 3 clusters () with a highly valid DBI score of 0.62. The clustering revealed three regional typologies: extreme multi-crisis, high-conflict, and low-case regions. The results showed that ongoing disputes consistently dominate as the primary cause across all clusters, significantly surpassing economic factors. Practically, these clustering results provide a critical, data-driven foundation for policymaking. Rather than providing generalized financial assistance, local governments and Religious Courts can use this model to deploy targeted, region-specific psychological interventions and revitalize Pre-Marriage Guidance (Bimwin) programs tailored to each region's crisis profile.
Co-Authors Abdul Halim Hasugian Andini Wulandari Angga Ardiansyah Aninda Muliani Armanda, Akbar Agustama Astuti, Andriani Dwi Baihaqi, Abdullah Afif Baratih, Ira Iranda Isyha Br Sembiring, Nadia Dayatila, Nada Fadilla, Nurul Haerani, Sintia Hafidz, Hasbanur Harahap, Putri Sari Febrianty Hasibuan, Maria Hikmah Hasibuan, Salsabila Arifa Heri Santoso Hidayati, Lily Ilka Zufria Irawati, Cici Lubis, Desy Ramadhani Manurung, Haidar Azra Muchain, Alfira Nafhan Muhammad Dedi Irawan Nasution, Adnan Buyung Nasution, Muhammad Adnan Buyung Raissa Amanda Putri Rangkuti, Syawaliah Putri Ritonga, Fazrul Umri Salim, Putra Silalahi, Dinah Makhroza Sinaga, Imam Adlin Sitorus, Andriani Situmeang, Monica Tarigan, Putri Amelia Triutami, Anggun