Aiman Daw Ghanim, Zakaria Suliman Zubi



Data Mining Methods in Municipality Social Data System (DMSDS)

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The wide technical evolution of the use of data mining technology in dealing with huge electronic datasets is increasing day by day. This great and growing progress motivates us to employ this technology in dealing with the municipality's social data. The municipality is an organizational structure that includes a number of departments, offices and service localities that deal with sectors, citizens and businesses in a specific geographical area. Within the municipality there are areas affiliated to the municipality, which we called in Libya as “Al-Mahalla.” This “Mahalla” represents an administrative division belonging to the municipality. There are social data represented in a dataset about the citizens residing in Al-Mahalla, which belongs to the municipality. The dataset holds a general statistical data on the citizens residing in the municipality, as well as the "Al-Mahalla" inhabited by the citizens. In this study, we will address the municipality of Al-Khums in Libya, as one of the municipalities in Libya as a case study. In this paper, we will use classification and clustering methods to extract knowledge from social data and predict marriage rate, death rate, poverty rate and rate of increase or decrease of citizens in the municipality, which in turn helps leaders and decision makers in the municipality to make the appropriate decision. As well as it aims to discuss the impact of the municipality's social data on the current Libyan lifestyle. We used also Weka software as a data mining solution to apply classification and clustering methods on the datasets we obtained from the municipality.


Data mining, Municipality dataset, Social dataset, Classification, Clustering, KNN, K-means, Dataset


Cite this paper

Aiman Daw Ghanim, Zakaria Suliman Zubi. (2022) Data Mining Methods in Municipality Social Data System (DMSDS). International Journal of Computers, 7, 125-137


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