Kabale University Institutional Digital Repository (KAB-IDR)
KAB-IDR is a digital service that collects, preserves, and distributes digital material. Repositories are important tools for preserving Kabale University's legacy; they facilitate digital preservation and scholarly communication.
Communities in KAB-IDR
Select a community to browse its collections.
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Household Water Treatment Technologies for Microbial Removal in Kabale District, Southwestern Uganda
(OMMEGA Publishers, 2016-04)Health problems associated with the consumption of untreated drinking water is one of the greatest concerns in Kabale District in spite of government’s efforts to provide safe drinking water to the people. The objective ... -
FINANCIAL INCLUSION AND WOMEN EMPOWERMENT IN UGANDA A CASE OF LANGO SUB REGION, NORTHERN UGANDA
(Economics, Commerce and Trade Management: An International Journal, 2018)Women empowerment has taken a center stage in the present development agenda. The study examines the role of financial inclusion in supporting women empowerment in Lango sub region, Northern Uganda. Using both purposive ... -
Developing Countries and Blockchain Technology: Uganda’s Perspective
(International Journal of Latest Research in Engineering and Technology, 2018-08)Blockchain is receiving ever-growing attention from research and industry and is considered a breakthrough technology. This paper presents an overview of Blockchain Technology and its potential applications in developing ... -
Crime Prediction Using Decision Tree (J48) Classification Algorithm.
(International Journal of Computer and Information Technology, 2017-05)There had been an enormous increase in the crime in the recent past. Crimes are a common social problem affecting the quality of life and the economic growth of a society. With the increase of crimes, law enforcement ... -
A Performance Analysis of Business Intelligence Techniques on Crime Prediction
(International Journal of Computer and Information Technology, 2017-03)Law Enforcement agencies are faced with a problem of effectively predicting the likelihood of crime happening given the past crime data which would otherwise help them to do so. There is a need to identify the most efficient ...
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