Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal Jurnal Sistem Informasi dan Informatika
Paskal Arienda Epindonta Ginting
Ilmu Komputer, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Negeri Medan
Computer Science & IT Electrical & Electronics Engineering Materials Science & Nanotechnology

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Penerapan Metode Agglomerative Clustering Untuk Segmentasi Data Dalam Lingkungan Big Data Paskal Arienda Epindonta Ginting; Risky Immanuel Situmorang; Muhammad Raihansyah Lubis; Raja Ansel Hartama Sihombing; Arnita Piliang
Jurnal Sistem Informasi Dan Informatika Vol 4 No 1 (2026): Januari 2026
Publisher : Prodi Sistem Informasi Universitas Dharma Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jiska.v4i1.2639

Abstract

The exponential growth of data in the digital era has increased the need for analytical methods capable of handling Big Data characteristics. This study examines the application of Agglomerative Hierarchical Clustering (AHC) for data segmentation using two datasets: (1) an Iris dataset of 24 samples with 8 morphological attributes, and (2) an e-commerce transaction dataset of 10 customer records. Ward linkage was selected based on literature evidence of its superiority. Results on the Iris dataset yielded 3 optimal clusters with a Silhouette Score of 0.4196 and an Adjusted Rand Index of 0.3635, achieving 70.83% classification accuracy. In the e-commerce dataset, three customer segments were formed: premium, middle-tier, and passive customers. These findings confirm AHC as an effective multidimensional data segmentation method.
Co-Authors Arnita Piliang Muhammad Raihansyah Lubis Raja Ansel Hartama Sihombing Risky Immanuel Situmorang