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All Journal Jurnal Informatika dan Teknik Elektro Terapan POROS TEKNIK Jurnal Noken: Ilmu-Ilmu Sosial INTECOMS: Journal of Information Technology and Computer Science JURNAL PENDIDIKAN TAMBUSAI International Journal of Social Service and Research Shautuna: Jurnal Ilmiah Mahasiswa Perbandingan Mazhab Prosiding Seminar Nasional Biologi, Teknologi dan Kependidikan (Biotik) Sisfo: Jurnal Ilmiah Sistem Informasi Sewagati PARAPOLITIKA: Journal Of Politics and Democracy Studies Transcendent Journal of Mathematics and Applications VISA: Journal of Vision and Ideas Al-Ihtiram: Multidisciplinary Journal of Counseling and Social Research DISCOURSE : Indonesian Journal of Social Studies and Education Indonesian Journal of Islamic Law (IJIL) Jurnal Audit, Pajak, Akuntansi Publik Jurnal Transportasi dan Bahari (ALTAIR) Journal of Engineering and Technological Sciences
Saputra, Ilham
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Journal : VISA: Journal of Vision and Ideas

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Analisis Performa Algoritma K-Means Clustering untuk Segmentasi Pasar di UMKM Afrizal, Muhammad; Saputra, Ilham; Satria, Riyan; Rahmaddeni, Rahmaddeni
VISA: Journal of Vision and Ideas Vol. 5 No. 2 (2025): Journal of Vision and Ideas (VISA)
Publisher : IAI Nasional Laa Roiba Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47467/visa.v5i2.6942

Abstract

This study aims to analyze the performance of the K-Means Clustering algorithm in market segmentation for Micro, Small, and Medium Enterprises (MSMEs). Using a quantitative approach, the data collected includes demographic information, purchasing behavior, and product preferences from respondents. The analysis process begins with data preprocessing, including normalization and outlier removal, before applying the K-Means algorithm to group customers into several segments. The performance evaluation of the algorithm is conducted using the Silhouette Score and Davies-Bouldin Index metrics. The analysis results indicate that the K-Means algorithm successfully identifies four distinct customer clusters, each with unique characteristics. The average Silhouette Score of 0.72 and a Davies-Bouldin Index of 0.45 suggest that the resulting clusters are well-defined and clearly separated. These findings provide valuable insights for MSMEs in formulating more effective and targeted marketing strategies.
Co-Authors Achmad Suryadi Nasution Ahmad, M. Ridwan Said Alhanannasir, Alhanannasir Amelia, Devi Amin, Abd. Rauf Muhammad Anderson, Ranap Angraini, Ria Apriade Voutama Ari Purnawan Ayu, Fidia Banggu, Masni Berlian, Alviona Bukhari Bukhari Chang, Shyang-Jye Dea Rizky Amalia Putri Ditta Kharisma Yolanda Putri FAQIH, ABDULLAH Gomes, Efrem Olivio Hartati, Diah Vitaloka Hayatul Khairul Rahmat Idealistuti, Idealistuti Jufri , Agustion Laila, Dwi Nuraini Mardianto, Lutfi Muhammad afrizal Mulawarman Murtado, Asep Dodo Musyfikah Ilyas, Musyfikah Ni Luh Darmayanti Nofriadi Nofriadi Nurmala, Eka Oktaviani, Melinda Parameswara, Prasetyo Prisiantika, Intan Rahmaddeni Rahmaddeni Rahmi Rahmi Ravitilova, Ravitilova Rinda, Rinda Rosidha, Anisa Nur Sari, Difka Augustina Diana Satria, Riyan Sebayang, Nico Setiyoko, Didik Tri Surbakti , Valina Singka Tusriadi Widjatma, Ridho Rahadina Yuli Yetri Zamzamia, Izatun Zuhriah Mumtazah Zulqarnain, A Muhammad Iman