Development of decision support system for distribution of social assistance services in municipalities

Unemployment, poverty and similar problems that have come to fore with the increase in population in our country have caused the municipalities to take charge in the field of social assistance and social services. For this purpose, it is very important that the municipalities that undertake social assistance and social service tasks are able to use the present data quickly during distribution of social assistance and make the right decisions in the related commissions. In this thesis study, it is aimed to develop a decision support system for distributing social welfare services through the example of Malatya Yeşilyurt Municipality. In this direction, firstly data were obtained from Yeşilyurt Municipality and the results obtained was compared by applying classification algorithms which are data mining methods. As a result of comparison, ID3, C4.5, J48, K-Nearest Neighbor, Naive Bayes Classifier, Bootstrap Aggregating, Random Forest Algorithms, Sequential Minimal Optimization and Local Weighted Learning algorithms have been determined as algorithms that give the best results. A web-based decision support system on the Yeşilyurt Municipality case was carried out within the scope of the thesis, using the results and rules of three different classification algorithms giving the best result. Keywords: Social Assistance, Social Services, Data Mining, Classification, Decision Support System