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All Journal Konfrontasi: Jurnal Kultural, Ekonomi dan Perubahan Sosial Budapest International Research and Critics in Linguistics and Education Journal (Birle Journal) Budapest International Research and Critics Institute-Journal (BIRCI-Journal): Humanities and Social Sciences Britain International of Humanities and Social Sciences (BIoHS) Journal Britain International of Exact Sciences Journal (BIoEx Journal) Britain International for Linguistics, Arts and Education Journal (BIoLAE Journal)
Belay Sitotaw Goshu
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Religion Arts Humanities Biochemistry, Genetics & Molecular Biology Chemistry Economics, Econometrics & Finance Education Environmental Science Languange, Linguistic, Communication & Media Mathematics Medicine & Pharmacology Physics Social Sciences Other

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Issues related to the quality of secondary education: the Case of Dire Dawa, Ethiopia Belay Sitotaw Goshu; Melaku Masresha Woldeamanueal; Muhammad Ridwan
Budapest International Research and Critics Institute-Journal (BIRCI-Journal) Vol 7, No 4 (2024): Budapest International Research and Critics Institute November
Publisher : Budapest International Research and Critics University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33258/birci.v7i4.7977

Abstract

This study aimed to examine concerns regarding the quality of education in secondary schools in Dire Dawa City. It reflects the views of teachers and educational administrators on educational quality, issues, and recommendations for improving quality. A descriptive survey was conducted for this purpose. In this study, 235 city teachers were randomly selected. Despite access improvements, data shows slow progress in improving quality education in Ethiopia. Government officials, teachers, parents, teachers, students, and others expressed concern about the quality of education in general education schools in Dire Dawa City. The results revealed that schools should also provide an educational environment suitable for teaching and learning activities. In-service training or professional development is one of the key factors in quality education. However, the result revealed that 43% of the survey respondents had not attended in-service training in the past two years. Furthermore, 91.9 percent of the respondents believed cheating was a crucial problem for quality education. The local government should work with the university to address most of the issues raised in this study.
Machine Learning-Enhanced Prediction of Lunar Crescent Visibility for Unified Hijri Calendar Determination: A Global and Regional Framework Belay Sitotaw Goshu; Muhammad Ridwan
Budapest International Research and Critics Institute-Journal (BIRCI-Journal) Vol 9, No 2 (2026): Budapest International Research and Critics Institute May
Publisher : Budapest International Research and Critics University

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Abstract

The lunar Hijri calendar governs religious observances for approximately 1.9 billion Muslims worldwide, yet disunity in crescent sighting criteria leads to inconsistent Ramadan and Eid dates across regions. Traditional visibility criteria (Yallop, Odeh) rely on simplified parametric approximations that inadequately capture complex atmospheric and geographical interactions. This study develops and validates a machine learning-enhanced framework for predicting lunar crescent visibility to support unified Hijri calendar determination through global and regionally-adapted models. A comprehensive dataset of 7,488 observations spanning 13 years (2013–2025) across 24 countries and five geographical regions was compiled. Feature engineering created 15 predictive parameters including interaction terms and composite indices. Eight supervised learning algorithms were evaluated with hyperparameter optimization using randomized search, genetic algorithms, and particle swarm optimization. Ensemble methods including voting, stacking, and hybrid configurations were developed and validated using 5-fold cross-validation. Findings: The hybrid ensemble model achieved superior performance (AUC 0.906, F1-score 0.888), outperforming traditional criteria by 17–19%. Engineered interaction features (elongation × altitude, lag time × altitude) demonstrated highest predictive importance. Regional analysis revealed visibility rate variations from 97.7% (Oceania) to 98.7% (Asia), supporting geographically-calibrated models. Long-term Ramadan predictions (2027–2075) confirmed the 33-year lunar cycle with mean interval of 354.37 days. Conclusion: Machine learning provides robust, evidence-based crescent visibility prediction that exceeds traditional criteria accuracy while capturing complex parameter interactions. The framework supports both global unification and region-specific applications. Recommendation: Religious authorities should adopt probabilistic, multi-model ensemble predictions with confidence scoring for calendar determination, supported by continuous validation against global observational networks.
Co-Authors Abel Berhanu Sitotaw Ashenafi Taye Negewo Bikila Merga Deresa Kirubel Molla M. Yoserizal Saragih Melaku Masresha Woldeamanueal Melaku Masresha Woldemariam Muhammad Ridwan Muhammad Ridwan Syarifuddin Yonas Tadesse Alemu