RANCANG BANGUN SISTEM OPEN-DATA ANALYTICS UNTUK PEMETAAN WILAYAH JAWA TIMUR MENGGUNAKAN ALGORITMA K-MEANS CLUSTERING

Melathi, Ayu (2026) RANCANG BANGUN SISTEM OPEN-DATA ANALYTICS UNTUK PEMETAAN WILAYAH JAWA TIMUR MENGGUNAKAN ALGORITMA K-MEANS CLUSTERING. S1 thesis, Universitas PGRI Madiun.

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Abstract

The prevalence of numerical tables on the East Java open-data portal can hinder the analysis of regional disparities due to limited spatial visualization capabilities. This study aims to develop an open-data analytics website that utilizes the K-Means Clustering algorithm to automatically group the characteristics of 38 regencies and cities. The system development follows the Waterfall methodology, incorporating Unified Modeling Language (UML) for modeling. Data collection involved extracting regional indicator data from the East Java Open Data portal. Clustering was performed using the K-Means algorithm; the optimal number of clusters was determined via the Davies-Bouldin Index (DBI) and Silhouette Score, with regions grouped based on centroid values. Model evaluation yielded a Davies-Bouldin Index (DBI) of 0,350 and a Silhouette Score of 0,709 at k=2, indicating high-quality cluster separation. The system is presented as an interactive website featuring map visualizations and evaluation charts. Functional testing confirmed the system is error-free, while a user experience assessment using the System Usability Scale (SUS) with 10 respondents resulted in a score of 77.50 (categorized as "Acceptable," Grade Scale C, and Adjective Rating "Good"). This system offers a potential alternative tool to facilitate regional mapping and the visual presentation of statistical data.

Item Type:	Thesis/Skripsi/Tugas Akhir (S1)
Kata Kunci:	Open-Data Analytics; K-Means Clustering; Website; Waterfall Method; System Usability Scale (SUS)
Subjects:	Q Science > QA Mathematics T Technology > T Technology (General)
Divisions:	Fakultas Teknik > Teknik Informatika
Depositing User:	REZA PURWIASRI AYU
Date Deposited:	14 Oct 2026 05:44
Last Modified:	14 Oct 2026 05:44
URI:	http://eprint.unipma.ac.id/id/eprint/10134

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