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Abstract

Waqf is a donation activity of an own property for charity and the general welfare under sharia. The productive waqf empowerment in perspective economic changes the use of waqf from consumptive to productive. Lands are one form of waqf, and they are strategic assets for productive waqf empowerment. This research aims to build a classifier to predict waqf lands as productive or not productive assets for business prospects. The classification used Naïve Bayes with attributes summarised from administrative data of waqf lands. A new method was proposed to improving the classification accuracy using a modified Apriori algorithm. A threshold value defined based on a mean value from the classification process by the Naïve Bayes was used to select classification results with a deviation of posterior value, and the value which was below to be reclassified using the Apriori algorithm. The proposed method used can improve prediction accuracy better than using only one Naïve Bayes classifier.

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How to Cite
Fahmi, A., Sugiarto, E., & Winarno, A. (2022). Business Prospects Prediction for Waqf Lands Using Naïve Bayes And Apriori Algorithm. Journal of Information Technology and Computer Science, 7(1), 9–21. https://doi.org/10.25126/jitecs.202271351