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Journal : building of informatics technology and science

Comparison of Clustering Algorithms for Analyzing the Impact of Conflict on Poverty and Inflation M Raykah Alam Ramadan; Dhio Pratama Wiransyah; Satria Ramadhani; Rayya Ramadhan Simangunsong; Ken Dhita Tania; Alsella Meiriza; Ahmad Rifai
Building of Informatics, Technology and Science (BITS) Vol 7 No 4 (2026): March 2026
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v7i4.9512

Abstract

Armed conflict can have significant impacts on the social and economic conditions of a region, particularly on poverty levels and inflation. This study aims to analyze the impact of conflict on key economic indicators using a Knowledge Management System (KMS) approach and to compare the performance of clustering algorithms in identifying underlying data patterns. The research applies clustering analysis by comparing K-Means, DBSCAN, and Hierarchical Clustering algorithms to group data based on similarities in economic characteristics. The dataset used in this study consists of several indicators, including poverty levels before and during conflict, extreme poverty rates, inflation rates, GDP changes, and currency devaluation. Data preprocessing techniques such as normalization are applied to ensure comparability among variables. The evaluation of clustering performance is conducted using Silhouette Score and Davies–Bouldin Index to determine the most effective algorithm. The results show that clustering methods are able to identify distinct grouping patterns of regions based on the level of conflict impact on economic conditions. Among the evaluated algorithms, DBSCAN demonstrates superior performance in handling complex and uneven data distributions. The analysis also indicates a consistent tendency for poverty and inflation to increase during periods of conflict, highlighting the economic vulnerability of affected regions. Furthermore, the integration of clustering results into a Knowledge Management System enables the transformation of analytical outputs into structured knowledge that can support data-driven decision making. These findings are expected to contribute to the development of more effective economic policies and analytical frameworks in conflict-affected areas.
Co-Authors A. Salwa Aurelya Putri Abd. Rasyid Syamsuri Adelia Rizki Putri Ahmad Fadhil Rizqi Al Amin Mulya Al Farissi Ali Ibrahim Alifa Putri Shahabiyah Aliya Faiza Allsela Meiriza, Allsela Allsella Meiriza Alsella Meiriza Alsella Meiriza Athiyyah Nuha Rotifa Aulia Pinkasari Bagus Prihantoro Bambang Tutuko Danny Matthew Saputra Dedy Kurniawan Dhio Pratama Wiransyah Dinda Lestarini Dinna Yunika Hardiyanti Donny Giovanna Karo Karo Edo Wicaksono Eka Prasetyo Ariefin Endang Lestari Ruskan Fathoni - Fidela Tertia Alfino Fransiska Prihatini Sihotang, Fransiska Gabriel Sebastian Santoso Gibral Abdurahman Haniifah Putriani Hardini Novianti Hardini Novianti Hardini Novianti Hardini Novianti Huda Ubaya Jaidan Jauhari Jeremiah Alwin Siahaan Kemahyanto Exaudi Ken Dhita Tania Ken Dhita Tania Ken Ditha Tania Kesuma, Lucky Indra Lailla Syal Syabilla Lina Oktarina M Raykah Alam Ramadan M. Rudi Sanjaya M. Thoriqul Fadli Mei Intan Natasyah Meiyin Monica Amilia Putri Melisa Tri Cahya Ningsih Mira Afrina Muhammad Bayu Samudra Muhammad Dzaky Hasyim Muhammad Fachri Nuriza Muhammad Iqbal Disriansyah Muhammad Mayda Ary Pratama Muhammad Naufal Rachmamtullah Muhammad Rafly Muhammad Rendi Muhammad Wahyu Hikmalsyah Octa Dama Yanti Osvari Arsalan Pacu Putra Pascal Adhi Kurnia Tarigan Pibriana, Desi Purwita Sari Puti Chalisa Wardhana Putri Eka Sevtiyuni Putri Rahel Alifia Rahmad Fadli Isnanto Rahmat Izwan Heroza Rahmat Izwan Heroza Rayya Ramadhan Simangunsong Richa Pratiwi Rizka Dhini Kurnia Rossi Passarella Samsuryadi - Sarifah Putri Raflesia Sarmayanta Sembiring Satria Ramadhani Shafa Aurelliza Arian Sutarno - Sutarno Sutarno Syifa Alfariani Syifa Naura Milla Celesta Winda Kurnia