Latar, Egis Natasantika
Unknown Affiliation

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

Found 1 Documents
Search

Application of Hierarchical Cluster Analysis for Sub-District Grouping Based on Plantation Production Latar, Egis Natasantika; Pusung, Yulia Betania; Wael, Nurvia Imran; Maspaitella, Paskalina; Gaitian, Joni; Wattimanela, Henry Junus
Parameter: Jurnal Matematika, Statistika dan Terapannya Vol 4 No 3 (2025): Parameter: Jurnal Matematika, Statistika dan Terapannya
Publisher : Jurusan Matematika FMIPA Universitas Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/parameterv4i3pp441-458

Abstract

Plantation production is the result of plantation cultivation which includes the of commodities such as coconut, cloves, nutmeg, cocoa, and coffee which have a high sales and economic value and are good for income, as well as being the main source of income for the community's life. Central Maluku Regency is one of the areas in Maluku Province that has great potential in the plantation sector, but the production level between sub-districts shows considerable variation due to differences in geographical conditions, infrastructure, and market access. This study aims to group sub-districts in Central Maluku Regency based on plantation production using a hierarchical cluster analysis approach. Distance measurement uses Single linkage, Average linkage, Complete linkage, and Ward linkage methods. In addition, descriptive analysis, standardization, KMO tests, and multicollinearity tests were carried out with the data used is in the form of plantation production data per sub-district in 2024 sourced from the Central Statistics Agency. Data processing using Microsoft Excel, SPSS, and R applications. The results of the study showed the formation of several sub-district clusters with similar production characteristics, where the Average linkage and Complete linkage methods with the number of clusters as many as three produced the best grouping with the highest Silhouette Score value of 0.477. Each cluster shows the basis for making policies for the development of the plantation sector. These results are expected to be the basis for local governments in formulating plantation development policies that are more targeted and effective.