Hendra Perdana
Department of Mathematics, Mathematics and Natural Science Faculty, Universitas Tanjungpura, Indonesia

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CONSTRUCTING AN OPTIMAL PORTFOLIO USING CLUSTERING LARGE APPLICATION AND VALUE AT RISK ANALYSIS FOR IDX80 STOCKS Sania Pujianti; Hendra Perdana; Neva Satyahadewi
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 20 No 3 (2026): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol20iss3pp1855-1868

Abstract

Investment is a way to manage wealth and achieve financial goals in the future. Stocks are an attractive investment instrument due to their high potential returns, although they also carry significant risks. These risks can be minimized through portfolio diversification. Diversification is carried out by selecting representative stocks from the clustering results. This study aims to construct an optimal portfolio using the Clustering Large Application (CLARA) method and conduct portfolio risk analysis using Value at Risk (VaR). The data used includes IDX80 stock closing prices from November 1, 2024, to January 31, 2025, the financial ratios of IDX80 stocks on December 2024, and the Bank Indonesia (BI-Rate) interest rate from November 2024 to January 2025. The CLARA method produces four stock clusters with a silhouette coefficient of 0.18226. This value indicates a low level of separation between clusters, as there might be overlapping features among the clusters. Representative stocks from each cluster are selected based on the highest Sharpe ratio: SCMA, JPFA, GOTO, and BRIS. The portfolio weights based on MVEP are 15.002% (SCMA), 29.786% (JPFA), 1.858% (GOTO), and 53.354% (BRIS). The VaR calculation shows a potential maximum loss of Rp137,139 in one day, with a 99% confidence level, from an initial investment of Rp10,000,000.
STRUCTURAL EQUATION MODELING ANALYSIS ON POVERTY IN WEST KALIMANTAN WITH FINITE MIXTURE IN PARTIAL LEAST SQUARE APPROACH Muhammad Fauzan; Hendra Perdana; Neva Satyahadewi
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 20 No 1 (2026): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol20iss1pp0001-0016

Abstract

Poverty occurs when individuals or groups lack the necessary resources to fulfill their basic needs. In Indonesia, including West Kalimantan, poverty remains a significant issue influenced by various socio-economic factors. This study aims to identify valid and reliable indicators of poverty and classify regencies/cities in West Kalimantan using the 2023 data from the Central Statistics Agency of West Kalimantan and Indonesia. The analysis applies the Structural Equation Modeling approach with Finite Mixture in Partial Least Squares (FIMIX-PLS). From 19 observed indicators, only 12 were found valid and reliable based on measurement and structural model evaluation. The structural model reveals three significant relationships: the Economy significantly influences Poverty, Health influences Education, and Education influences the Economy. Based on the FIMIX-PLS results, the regencies/cities are segmented into four groups with distinct structural characteristics. Segment 1 reflects the influence of Health on Education, Segment 2 reflects the influence of Health on the Economy, Segment 3 highlights the influence of Economy on Poverty, and Segment 4 captures the influence of Education on the Economy. Detailed interpretations of each segment and their policy implications are presented in the conclusion. The results support the importance of tailored poverty alleviation strategies based on latent regional characteristics and validated model findings.