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A Survey of Machine Learning Approaches and Techniques for Student Dropout Prediction
(Data Science Journal, 2019-04-17)
School dropout is absenteeism from school for no good reason for a continuous number of days. Addressing this challenge requires a thorough understanding of the underlying issues and effective planning for interventions. ...
Machine learning approach for reducing students dropout rates
(International Journal of Advanced Computer Research, 2019-05-06)
serious issue in developing countries. On the other hand, machine learning techniques have gained much attention on addressing this problem. This paper, presents a thorough analysis of four supervised learning classifiers ...
An integrated mobile application for enhancing management of nutrition information in Tanzania
(NM-AIST, 2016-04)
Malnutrition contributes to over one half of the deaths of children under age of five years in developing countries and is the single greatest cause of child mortality in Tanzania. Studies reveal that, the issue of ...
Data driven approach for predicting student dropout in secondary schools
(NM-AIST, 2020-06)
Student dropout is among the challenges that face most schools in developing countries
particularly in Africa. In Tanzania alone, student dropout in secondary schools is pronounced
to be around 36%. In addressing the ...
Development of the RFID Based Library Management and Anti-Theft System:A Case of East African Community (EAC) Region
(International Journal of Advances in Scientific Research and Engineering, 2021-05)
Radio Frequency Identification (RFID) Systems are becoming very useful in our daily life due to its advantages such as reduction of human error, theft prevention, time consuming reduction, the auto identification ...
An Integrated Deep Learning-based Lane Departure Warning and Blind Spot Detection System: A Case Study for the Kayoola Buses
(IEEE, 2023-11-16)
Deep learning-based driver assistance systems (ADAS) have attracted interest from researchers due to their impact on improving vehicle safety and reducing road traffic accidents. In Uganda, road accidents have continued ...
Data Synthesis Technique for Categorical Pestes Des Petits Ruminants (PPR) Data Using CTGAN Model
(Pre prints,org, 2023-05-11)
Data scarcity is a significant challenge in the field of Machine Learning (ML), as data
collection can be expensive, time‐consuming, and difficult, particularly in developing countries.
This challenge is exaggerated on ...
Mobile-Based convolutional neural network model for the early identification of banana diseases
(Elsevier, 2024-02-29)
This study aimed to deploy a deep learning model in a mobile application for the early identification of Fusarium
Wilt and Black Sigatoka in bananas. In this paper, a Convolutional Neural Network (CNN) model for the ...
Feature Selection Approach to Improve Malaria Prediction Model’s Performance for High- and Low-Endemic Areas of Tanzania
(Springer Link, 2024-06)
Malaria remains a significant cause of death, especially in sub-Saharan Africa, with about 228
million malaria cases worldwide. Parasitological tests, like microscopic and rapid diagnostic
tests (RDT), are the recommended ...
Predicting customer subscription in bank telemarketing campaigns using ensemble learning models
(Elsevier, 2025-03)
This study investigates the use of ensemble learning models bagging, boosting, and stacking to enhance the accuracy and reliability of predicting customer subscriptions in bank telemarketing campaigns. Recognizing the ...