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INDONESIA
ALGORITMA : JURNAL ILMU KOMPUTER DAN INFORMATIKA
Published by Universitas Islam Negeri Sumatera Utara
ISSN : -     EISSN : 25986341     DOI : 10.30829/algoritma
Core Subject : Science,
Computer Science & IT
Arjuna Subject : -
Articles 1 Documents
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Search results for , issue "Vol 9, No 2 (2025): November 2025" : 1 Documents clear
Studi Pengelompokan Multimetode Provinsi di Sumatera Utara Menggunakan Pendekatan PCA dan K-Means Lubis, Fitra Hidayat; Ashar, Suthan Farras; M.S, OK Mhd Fahri Al-Faruqy; Amari, Ahmad Boby
Algoritma: Jurnal Ilmu Komputer dan Informatika Vol 9, No 2 (2025): November 2025
Publisher : Universitas Islam Negeri Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/algoritma.v9i2.25017

Abstract

This study aims to classify regions in North Sumatra based on a set of social and economic indicators by applying a multi-method clustering approach. Principal Component Analysis (PCA) is employed to reduce data dimensionality and identify the most influential variables, while the K-Means algorithm is used to form clusters based on similarity of characteristics. The results indicate that the combination of PCA and K-Means can cluster provinces or regions more efficiently and interpretably. The resulting clusters reflect patterns of similarity among regions in terms of social and economic development, thus providing a basis for formulating more targeted regional development policies. These findings demonstrate that a multi-method approach can yield more comprehensive results in spatial data clustering.Keywords: Clustering, Principal Component Analysis (PCA), K-Means, multi-method, North Sumatra.

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