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Aug 7, 2025
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Oct 17, 2025
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Abstract

The purpose of this study is to use the Linear Discriminant Analysis (LDA) method to categorize districts and cities in South Sulawesi Province according to their main economic sectors. The Central Statistics Agency (BPS) of South Sulawesi provided data for the period 2019–2023. The dependent variable was classified according to GDP (GRDP) quartiles within economic sectors, while the independent variables were the Labor Force Participation Rate (LBFR), the Number of Business Units (NBE), and the Open Unemployment Rate (OUR). The findings indicate that the most important factors in group differentiation are TPA and TPT. The classification accuracy was only 37.5%, although the model met important assumptions such as normality, homogeneity of covariance, and the absence of multicollinearity. This suggests that the model should be further improved by adding more in-depth predictors or using more differentiated categorization techniques.

Keywords

: compartmentalized, iteration, interaction effect, missing data estimation, stability analysis

Article Details

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