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Application of Principal Component Analysis on Factors Causing Inflation in West Kalimantan Asri Rahmawati; Yuyun Eka Pratiwi; Onelia Rochmah
Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika Vol. 22 No. 2 (2025): Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika
Publisher : Program Studi Ilmu Komputer, Universitas Pakuan

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Abstract

Inflation is an important indicator in assessing the economic stability of a region. Inflation fluctuations in West Kalimantan are influenced by various economic and structural factors. This study aims to identify the main factors causing inflation in West Kalimantan using Principal Component Analysis (PCA). Secondary data for the 2024 timeframe was obtained from West Kalimantan's Central Statistics Agency (BPS). Economic variables that are suspected of influencing inflation are analyzed using PCA to be reduced to new dominant factors. The main components obtained are then interpreted economically to understand the structure of the causes of inflation. The results of the analysis show that the cumulative proportion of the two components reaches 90%, so the two main components are sufficient to represent the main structure of the data. This means that most of the information from the original variables can be effectively reduced into two main components. Keywords: Inflation; PCA; reduction; economic factors.
EFEKTIVITAS PELATIHAN POWER BI DALAM MENINGKATKAN LITERASI DATA ADMIN SATU DATA KALIMANTAN BARAT Neva Satyahadewi; Evy Sulistianingsih; Shantika Martha; Nurfitri Imro'ah; Hendra Perdana; Wirda Andani; Ray Tamtama; Yuyun Eka Pratiwi; Muhammad Fikri; Pitriani; Annisa Auliarahmi; Nazwa Nursyifa; Yohanna Gabriel Richsita; Louis Putra Jaya; Jessica Audrey Valeria
Dianmas Bhakti: Jurnal Pengabdian pada Masyarakat Vol 3 No 1 (2026): Dianmas Bhakti: Jurnal Pengabdian pada Masyarakat
Publisher : LPPM Universitas Panca Bhakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54035/dianmas.v3i1.626

Abstract

This Community Service Program (PKM) aimed to enhance data literacy and information visualization skills among Satu Data administrators of local government agencies (OPD) through Microsoft Power BI training at the West Kalimantan Provincial Communication and Information Agency (Diskominfo). The program was implemented through preparation, face-to-face training, and evaluation stages using pre-test and post-test instruments. The training covered fundamental concepts of data analysis, data visualization techniques, and hands-on dashboard development using regional sectoral data. The results of the paired sample t-test analysis indicated a statistically significant improvement between participants’ pre-test and post-test scores, demonstrating the effectiveness of the training. Furthermore, analysis using Partial Least Squares Structural Equation Modeling (PLS-SEM) revealed that training material quality had a positive and significant effect on participants’ learning outcomes, while other supporting factors such as training duration, facilitator performance, and technical aspects did not show significant effects. These findings highlight that well-structured and relevant training materials play a critical role in improving participants’ competencies. Overall, the program contributed to strengthening analytical skills and supporting the implementation of the Satu Data Indonesia policy toward transparent and evidence-based data governance