iosr-jmr   Volume-2 ~ Issue-5 ~ Sep. – Oct. 2025

ABSTRACT: School dropout represents a critical barrier to achieving Sustainable Development Goal 4 (Quality Education), particularly in Northern Nigeria, where 78% of the nation's 10.5 million out-of-school children reside. This study addresses this challenge by developing an integrated ensemble machine learning framework utilizing a large-scale attendance dataset comprising 1,048,576 records from the Better Education Service Delivery for All (BESDA) Attendance Monitoring Information System (BAMIS) across thirteen Northern Nigerian states. The research employs.......

Keywords: Machine Learning, School Dropout Prediction, Random Forest, SHAP Explainability, Absenteeism, Northern Nigeria, Educational Data Mining, Imbalanced Classification

[1] UNICEF, "The State of Global Learning Poverty: 2022 Update," UNICEF Regional Office for West and Central Africa, Abuja, 2022.
[2] World Bank, "Ending Learning Poverty: What will it take?" World Bank Education Global Practice, Washington, DC, 2021.
[3] R. S. Baker et al., "Educational Data Mining and Learning Analytics," in Handbook of Learning Analytics and Educational Data Mining, Springer, 2020.
[4] K. Ameri et al., "Predicting Student Dropout in Developing Contexts: A Systematic Review," Education and Information Technologies, vol. 22, no. 4, pp. 1-28, 2023.
[5] D. Contreras et al., "Negative teacher-student relationships and school dropout: Evidence from Chile," International Journal of Educational Development, vol. 91, p. 102576, 2022.

ABSTRACT: Biosorption of Methylene Blue (MB) from aqueous solution using macadamia seed husks (MSH) biomass obtained from dumpsite of the Jungle industry in Thika. The isotherm data fitted Freundlich mathematical models with maximum dye adsorption of 3.7171mg g-1. Evaluation of the outcome of batch experiments indicated that the sorption process was greatly depended on the time of contact, initial concentration of the dye solution, temperature of the aqueous solution, adsorbent dosage and MSH particle size. The kinetics of the adsorption studies perfectly....

Keywords Macadamia Seed Husks, Methylene Blue dye, Biosorption, Kinetics, equilibrium

[1] S. H. I. Hanchang, “Industrial wastewater-types, amounts and effects,” Point Sources Pollut. Local Eff. Their Control-Vol. II, p. 191, 2009.
[2] B. Ramaraju, P. Manoj Kumar Reddy, and C. Subrahmanyam, “Low cost adsorbents from agricultural waste for removal of dyes,” Environ. Prog. Sustain. Energy, vol. 33, no. 1, pp. 38–46, Apr. 2014, doi: 10.1002/ep.11742.
[3] W. C. Wanyonyi, J. M. Onyari, P. M. Shiundu, and F. J. Mulaa, “Effective biotransformation of Reactive Black 5 Dye Using Crude Protease from Bacillus Cereus Strain KM201428,” Energy Procedia, vol. 157, pp. 815–824, Jan. 2019, doi: 10.1016/j.egypro.2018.11.247.
[4] H. A. Al-Husseiny, “Adsorption of methylene blue dye using low cost adsorbent of sawdust: Batch and continues studies,” J. Babylon Univ. Sci., vol. 22, no. 2, 2014.