Skripsi
KLASIFIKASI KEPUTUSAN PEMBELIAN ASURANSI PERJALANAN MENGGUNAKAN MODEL NAIVE BAYES DAN FUZZY NAIVE BAYES
Insurance is a form of risk management carried out by many parties to deal with uncertainty in the future and the possibility of risks that cause losses. One type of insurance that is included in general insurance is travel insurance. This insurance is a type of insurance that provides protection for someone while traveling from unexpected events. This makes travel insurance needed in order to provide a sense of security and protection while traveling, but there are a number of factors that can influence someone who travels to buy or not a travel insurance product. Therefore, it is necessary to classify the decision to purchase travel insurance. The purpose of this research is to classify a person's decision to buy or not buy travel insurance using the Naïve Bayes and Fuzzy Naïve Bayes models. The results showed that both using the Naïve Bayes model and the Fuzzy Naïve Bayes model, of the 8 predictor variables after variable selection with the Chi Square Test, only 6 variables were significant, namely Age, Employment Type, Annual Income, Family Members, Frequent Flyer, Ever Traveled Abroad. In this study, the results of the Naïve Bayes model were obtained, namely accuracy, precision, recall, and fscore of 75.81%, 73.95%, 50% and 59.66%, respectively. While the results using the Naïve Bayes model with the Chi Square test, namely accuracy of 76.07%, precision of 74.73%, recall of 50%, and fscore of 59.91%. The results of using the Fuzzy Naïve Bayes model, namely accuracy, precision, recall, and fscore were 77.07%, 74.75%, 54.22 and 62.85%, respectively. While the results of using the Fuzzy Naïve Bayes model with the Chi Square test obtained accuracy of 76.82%, precision of 74.5%, recall of 53.52%, and fscore of 62.29%.
Inventory Code | Barcode | Call Number | Location | Status |
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2307005445 | T125912 | T1259122023 | Central Library (Referens) | Available but not for loan - Not for Loan |
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