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All Journal Journal of Innovation and Applied Technology BAREKENG: Jurnal Ilmu Matematika dan Terapan
Heni Kusdarwati
brawijaya university
Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Energy Engineering Mathematics Mechanical Engineering Physics Transportation

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Technical Guidance for Improving Information from Deterministic and Stochastic Modeling for Sectoral Data of Diskominfo Malang Regency Kusdarwati, Heni; Pramoedyo, Henny; Amaliana, Luthfatul
Journal of Innovation and Applied Technology Vol 9, No 1 (2023)
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.jiat.2023.009.01.4

Abstract

Data on the number of people with diabetes mellitus in Kanjuruan Hospital and monthly rainfall in Malang are used as examples for extracting information with inferential statistics. The statistic models used are linear and harmonic regression deterministic models and ARIMA and SARIMA stochastic models. The purpose of community service activities is to provide technical guidance on understanding sectoral time series data analysis for Malang Regency Communication and Information Technology employees. Each participant is given a theoretical module, modeling steps and RStudio script. There is an increase in information from the number of people with diabetes mellitus in Kanjuruan Hospital and the monthly rainfall associated with increasing time becomes related to the value of the data itself at the previous time. Descriptively there is an increase in the understanding value of the ARIMA and SARIMA models between before and after technical guidance.
CLUSTERING DISTRICTS/CITIES IN EAST JAVA PROVINCE BASED ON HIV CASES USING K-MEANS, AGNES, AND ENSEMBLE Lusia, Dwi Ayu; Salsabila, Imelda; Kusdarwati, Heni; Astutik, Suci
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 1 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss1pp63-72

Abstract

Cluster analysis is a method of grouping data into certain groups based on similar characteristics. This research aims to group districts/cities in East Java Province in 2021 based on HIV cases using hierarchical cluster analysis (AGNES), non-hierarchical cluster analysis (K-means), and ensemble clustering. The study found that the ensemble clustering solution forms four clusters, consistent with the results of AGNES clustering. This suggests that ensemble clustering improves the quality of cluster solutions by leveraging both hierarchical and non-hierarchical methods. The grouping of districts/cities based on HIV cases provides a clear distribution pattern for more targeted interventions. The study is limited to HIV cases in East Java Province and may not be generalizable to other regions with different epidemic characteristics. Additionally, the study focuses on clustering methods without investigating temporal changes in HIV case distribution. This research is one of the few studies that applies ensemble clustering to HIV cases in East Java Province. It combines hierarchical and non-hierarchical methods to improve the clustering process and provides a practical approach for regional HIV control planning.
Co-Authors Henny Pramoedyo Lusia, Dwi Ayu Luthfatul Amaliana, Luthfatul Salsabila, Imelda Suci Astutik