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All Journal G-Tech : Jurnal Teknologi Terapan
Syahreni, Syahreni
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Computer Science & IT Decision Sciences, Operations Research & Management Energy Engineering

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Analytic Predictive of Crescent Sighting Using Astronomical Data-Based Multinomial Logistic Regression in Indonesia Sugiharto, Tomy Ivan; Hariyadi, Mokhamad Amin; Chamidy, Totok; Santoso, Irwan Budi; Crysdian, Cahyo; Zarkoni, Ahmad; Ma'muri, Ma'muri; Syahreni, Syahreni
G-Tech: Jurnal Teknologi Terapan Vol 9 No 4 (2025): G-Tech, Vol. 9 No. 4 October 2025
Publisher : Universitas Islam Raden Rahmat, Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/g-tech.v9i4.8246

Abstract

This research aims to develop and validate a sophisticated crescent visibility classification model in Indonesia. Multinomial Logistic Regression (MLR) was chosen for its capability to provide clear model interpretation through coefficient analysis. Utilizing comprehensive observational data (2021-2025) from Indonesia's Meteorology, Climatology, and Geophysics Agency (BMKG), the study comprised 2210 data points. The model classifies visibility into three categories (Dark, Faint, and Bright) based on defined elongation thresholds. The final predictor variables used were azimuth difference, moon altitude, and elongation. Analysis of the optimal model's (Model A3) coefficients revealed azimuth difference and elongation as the most dominant predictors, marked by exceptionally large positive coefficients (12.050 and 12.018, respectively) for classifying the 'Faint' category. After data preprocessing and systematic optimization ('saga' solver, L2 penalty), the optimal model (A3, C=100) demonstrated exceptional performance with an outstanding F1-Score of 99.10%. These findings strongly validate MLR's effectiveness for elongation-based crescent visibility classification and highlight its substantial potential as a reliable foundation for objective decision-making.
Co-Authors Cahyo Crysdian Irwan Budi Santoso Ma'muri, Ma'muri Mokhamad Amin Hariyadi Sugiharto, Tomy Ivan Totok Chamidy Zarkoni, Ahmad