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All Journal Media Statistika Jurnal Ilmiah Pena: Sains dan Ilmu Pendidikan Jurnal PAJAR (Pendidikan dan Pengajaran) MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jambura Journal of Mathematics Jurnal Varian Variansi : Journal of Statistics and Its Application on Teaching and Research Seminar Nasional Pengabdian Kepada Masyarakat VARIANSI: Journal of Statistics and Its Application on Teaching and Research Indonesian Journal of Fundamental Sciences ARRUS Jurnal Pengabdian Kepada Masyarakat Pinisi: Journal of Teacher Proffesional
Annas, Suwardi
Fakultas Matematika Dan Ilmu Pengetahuan Alam, Universitas Negeri Makassar
Humanities Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Immunology & microbiology Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Physics Public Health Social Sciences Other

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Implementation of K-Means Clustering on Poverty Indicators in Indonesia Suwardi Annas; Bobby Poerwanto; Sapriani Sapriani; Muhammad Fahmuddin S
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 21 No. 2 (2022)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v21i2.1289

Abstract

This study aims to cluster all districts/cities in Indonesia related to poverty indicators. The attributes used are poverty gap index and poverty severity index. The data used comes from BPS. The method used is K-Means clustering, and the results show that by using the elbow and silhouette index methods, the optimal number of clusters is 2, where for cluster 1, it can be defined as a cluster with an area with a high poverty gap index and poverty severity index compared to cluster 2. As a result, cluster 1 has 42 districts/cities, and 472 for cluster 2.
Implementasi K-Affinity Propagation dalam Pengelompokan Provinsi di Indonesia Berdasarkan Kasus Pencemaran Lingkungan Hidup Derliani Natalia D.; Suwardi Annas; Zulkifli Rais
VARIANSI: Journal of Statistics and Its application on Teaching and Research Vol. 7 No. 03 (2025)
Publisher : Program Studi Statistika Fakultas MIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/variansiunm475

Abstract

Indonesia memiliki tingkat pencemaran lingkungan yang berbeda di setiap provinsi. Penelitian ini bertujuan untuk mengetahui gambaran dan hasil pengelompokan provinsi di Indonesia berdasarkan indikator pencemaran lingkungan yang meliputi pencemaran air, tanah, dan udara akibat limbah rumah tangga maupun limbah pabrik. Metode yang digunakan adalah K-Affinity Propagation (K-AP) dengan uji validasi Davies-Bouldin Index. Hasil analisis menunjukkan bahwa jumlah cluster optimum adalah 2, dimana Cluster 1 yang terdiri atas 3 provinsi dengan tingkat pencemaran lingkungan tertinggi, serta Cluster 2 yang terdiri atas 35 provinsi lainnya dengan tingkat pencemaran lebih rendah. Oleh karena itu, pemerintah perlu memberikan perhatian khusus pada provinsi yang masuk dalam Cluster 1, melalui pengawasan industri, pengelolaan limbah, serta peningkatan kesadaran masyarakat mengenai pentingnya pelestarian lingkungan.
Workshop on Student Graduation Decisions Using Statistical Methods at Takalar State Senior High School 7 Suwardi Annas; Ansari Saleh Ahmar; Zulkifli Rais; Rahmat H.S; Agung Tri Utomo
ARRUS Jurnal Pengabdian Kepada Masyarakat Vol. 4 No. 2 (2025)
Publisher : PT ARRUS Intelektual Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.abdiku4458

Abstract

This community service program was conducted at SMA Negeri 7 Takalar to enhance teachers’ ability to utilize statistical methods specifically logistic regression to support data-driven graduation decisions. The training addressed challenges related to manual graduation assessment processes that often lack objective analytical support. Participants were introduced to the basic concepts of logistic regression, followed by hands-on practice using an interactive R Shiny dashboard to analyze student data and estimate graduation probabilities. The results indicate that teachers were able to understand and apply statistical analysis procedures, interpret logistic regression outputs, and recognize the importance of evidence-based decision-making. This activity not only improved teachers’ data literacy but also supported digital transformation efforts in education and strengthened collaboration between Universitas Negeri Makassar and SMA Negeri 7 Takalar. The program is expected to contribute to more accurate, transparent, and data-informed graduation assessments in the future.
Co-Authors Adi Rahmat Faisal Agung Tri Utomo Ahmad Fudhail  Majid Ahmar, Ansari Saleh Alakbar Akbar Alin Liana Andi Muhammad Ridho Yusuf Sainon Andi Pandjajangi Asdar Ahmad Aswi, Aswi BAKHRANI RAUF Bobby Poerwanto Bobby Poerwanto Derliani Natalia D. Fajar Arwadi Fithriyah Azzahrah Hastuti Hastuti Irwan Irwan Irwan Irwan Irwan Irwan Irwan Irwan Laksono Trisnantoro Luthfiah Arradiah Mahrani Mahrani Mega Fatimah Rosana Muh Yahya Muh.Nadjib Bustan Muhammad Abdy Muhammad Fahmuddin Muhammad Fahmuddin Muhammad Kasim Aidid Muhammad Kasim Aidid Muhammad Nadjib Bustan Muharram Muharram Nur Aisyah Nur Isra Nurhamidah Mursyidin Nurul Fadhilah Syahrul Nurul Imania Kalla Nusrang, Muhammad P. Paramita Rahmat H.S Rahmat Hesha Safei Ridawati Ridawati Rika Nasir Ruliana Sapriani Sapriani Saripuddin D Sitti Faika Syafruddin Side Uca Sideng Wahidah Sanusi Zulkifli Rais Zulkifli Rais