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@article{J.Gauss33383, author = {Navioer Rizal and Mohamat Fatekurohman and Dian Anggraeni}, title = {KLASIFIKASI PENENTUAN LOKASI STRATEGIS OUTLET BANK SYARIAH INDONESIA DENGAN METODE NAÏVE BAYES CLASSIFIER}, journal = {Jurnal Gaussian}, volume = {12}, number = {4}, year = {2024}, keywords = {Classification; Locations; Naïve Bayes Classifier; Outlet; Strategic}, abstract = {Today, the development of the banking sector occurs in the conventional banking sector and the Islamic banking sector, one of which is developing Bank Syariah Indonesia. Bank Syariah Indonesia strives to develop a strategic new office network or branch outlet location that has not been optimal. This research aims to know and analyze the model and determination of variable importance and its effect on the strategic location classification of Bank Syariah Indonesia outlets using the Naïve Bayes Classifier method. The classification model of strategic location determination of offices or outlets obtained from the analysis results in calculating prior probability values and conditional probabilities. The results of the model evaluation test indicator for the Naïve Bayes Classifier method showed an accuracy value of 94,12% and an AUC score of 0,9808. The model was able to classify 16 of the 17 data. The model produces the results of variables importance 6 recommendations variables of the 7 variables used in the study it is location in office area, location in industrial area, populations density of the area, moslem populations of the area, distance from the security office, and distance from the market. The variable importance can be a consideration of Bank Syariah Indonesia optimizing indicators of the office location selection.}, issn = {2339-2541}, pages = {477--486} doi = {10.14710/j.gauss.12.4.477-486}, url = {https://ejournal3.undip.ac.id/index.php/gaussian/article/view/33383} }
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