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All Journal Journal of Education and Learning (EduLearn) SainsTech Innovation Journal
Asno Azzawagama Firdaus
Universitas Qamarul Huda Badaruddin Bagu
Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Education Library & Information Science Social Sciences Other

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CLUSTERING DAFTAR PEMILIH TETAP (DPT) DI DESA KEREMBONG PADA PILKADA 2024 MENGGUNAKAN ALGORITMA K-MEANS DENGAN RAPIDMINER Samsul Arifin; Yuan Sa'adati; Asno Azzawagama Firdaus; M. Afriansyah; Joni Saputra
SainsTech Innovation Journal Vol. 8 No. 2 (2025): SIJ VOLUME 8 NOMOR 2 TAHUN 2025
Publisher : LPPM Universitas Qamarul Huda Badaruddin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37824/sij.v8i2.2025.1120

Abstract

Pemilihan Kepala Daerah (Pilkada) merupakan elemen krusial dalam sistem demokrasi yang menuntut pengelolaan Daftar Pemilih Tetap (DPT) secara akurat dan efisien. Penelitian ini bertujuan untuk mengelompokkan Daftar Pemilih Tetap (DPT) di Desa Kerembong pada Pilkada 2024 menggunakan algoritma K-Means dengan bantuan RapidMiner. Latar belakang penelitian ini adalah masih ditemukannya penempatan pemilih yang tidak sesuai dengan domisili dusun, sehingga berpotensi menurunkan partisipasi pemilih. Metode penelitian meliputi tahap pra-pemrosesan data (preprocessing), konversi data kategorikal menjadi numerik dengan operator Nominal to Numerical, pelaksanaan clustering K-Means dengan nilai K = 12, serta evaluasi hasil menggunakan Davies-Bouldin Index (DBI). Jumlah data yang digunakan sebanyak 5.554 pemilih. Hasil clustering menunjukkan bahwa seluruh data berhasil dikelompokkan ke dalam 12 klaster yang mewakili pola lokasi tempat tinggal serupa. Nilai DBI sebesar 0.093 menunjukkan pemisahan antar klaster yang baik. Analisis perbandingan data sebelum dan sesudah clustering juga menunjukkan adanya TPS yang mengalami peningkatan jumlah pemilih hingga 70,11% (TPS 6) dan penurunan hingga 43,12% (TPS 7), sedangkan Tps 9 dan Tps 12 tetap stabil. Kesimpulan dari penelitian ini adalah algoritma KMeans efektif membantu Komisi Pemilihan Umum (KPU) dalam menata ulang distribusi pemilih agar penempatan TPS lebih tepat sasaran, logistik lebih efisien, dan partisipasi pemilih dapat meningkat.
Classification of Child Stunting Status Using the K-Nearest Neighbor (KNN) Algorithm Based on Toddler Growth Data in East Lombok Regency, West Nusa Tenggara Asno Azzawagama Firdaus; Arif Himawan; Junaedi; Anggun Sindiana; Istianah; Baiq Selviana Pertiwi; Baiq Wangi Narsih; Kartika Yundia; Ahmad Azhari
SainsTech Innovation Journal Vol. 9 No. 1 (2026): SIJ VOLUME 9 NOMOR 1 TAHUN 2026
Publisher : LPPM Universitas Qamarul Huda Badaruddin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37824/sij.v9i1.2026.1351

Abstract

Stunting is a major nutritional issue in Indonesia that significantly impacts children's physical growth, cognitive development, and future quality of life. Childhood stunting can be identified using nutritional status indicators—such as weight-for-age (W/A), height-for-age (H/A), and weight-for-height (W/H)—specifically by observing a Z-score below -2 for the H/A indicator. The growing volume of anthropometric data on children under five necessitates a rapid and objective method for identifying stunting status. This study aims to classify children's stunting status using the K-Nearest Neighbor (KNN) algorithm based on growth data from children under five in East Lombok Regency, West Nusa Tenggara. The dataset comprises records for 3,416 children, including information on gender, age, weight-for-age (W/A), weight-for-height (W/H), and height-for-age (H/A). Data preprocessing involved removing duplicates, handling missing values, transforming categorical data, and applying Min-Max normalization. The data was split into 70% training data and 30% testing data, with the KNN algorithm applied using k = 5. Model evaluation was conducted using a confusion matrix. The results demonstrate that the KNN model achieved an accuracy rate of 83.15%, indicating a strong capability to classify stunting status based on the children's anthropometric characteristics. These findings confirm that the KNN algorithm can serve as a tool for healthcare professionals to identify stunting more rapidly, objectively, and efficiently, thereby supporting early prevention and management efforts.
Prophetic sufism in Muhammadiyah: Tuan Guru Haris’ education model Palahuddin Palahuddin; Mhd. Lailan Arqam; Asno Azzawagama Firdaus; Moh. Juhad
Journal of Education and Learning (EduLearn) Vol 20, No 4: November 2026
Publisher : Intelektual Pustaka Media Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/edulearn.v20i4.26101

Abstract

This study examines how prophetic sufism is embodied and pedagogically transmitted within Muhammadiyah through the life and educational practices of Tuan Guru Haji (TGH) Haris in Lombok, Indonesia. It aims to demonstrate how spirituality operates as a lived, community-based learning model rather than merely a theological discourse. The research employed a qualitative life-history design with a historical-critical-philosophical orientation. Data were collected through manuscript analysis, observation, literature review, and in-depth interviews with six purposively selected informants representing familial, organizational, and community perspectives. Data were analyzed using the Miles-Huberman interactive model, including reduction, display, and verification through triangulation. The findings reveal that TGH Haris practiced prophetic sufism as an embodied pedagogical framework grounded in ikhlas (sincerity), kana’ah (contentment), and khauf (fear of God). His berugak (traditional Sasak pavilion) functioned as an informal learning center characterized by dialogical interaction, experiential teaching, and community-based moral formation. Spiritual values were transmitted through exemplarity, relational authority, and everyday engagement rather than institutionalized mystical structures. This study demonstrates that prophetic sufism operates as a practical Islamic pedagogical model integrating reformist theology, ethical discipline, and informal community learning. It contributes empirically grounded insights into how spirituality is enacted and reproduced within Muhammadiyah’s grassroots educational context.
Co-Authors Anggun Sindiana Arif Himawan Azhari, Ahmad Baiq Selviana Pertiwi Baiq Wangi Narsih Istianah Joni Saputra Junaedi Kartika Yundia M. Afriansyah Mhd. Lailan Arqam Moh. Juhad Palahuddin Samsul Arifin Yuan Sa'adati