ANALISIS KLASIFIKASI KUALITAS TOKO DARING MENGGUNAKAN ALGORITMA NAÃVE BAYES
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Institusion
Institut Teknologi Telkom Purwokerto
Author
CEISAR, NOVA NUR RAHMAH
Subject
T Technology (General)
Datestamp
2021-04-23 07:08:21
Abstract :
ABSTRACT Many applications provide online buying and selling services where buyers are facilitated in buying and selling transactions. However, in the use of online stores there are several things that make users less satisfied with the online store. This is because the user cannot see the item directly so there are many cases, such as the goods sent and do not match what is in the picture. In this study the authors used the Naive Bayes method to classify the comments that exist in the "X" store that were divided into satisfied and unsatisfied labels. Naive Bayes itself is used in this study because Naive Bayes has simplicity in its computation and according to some previous studies this method is effective for text classification. The author tests the accuracy and classification of comments that exist in online stores with 174 data taken where 100 data are used as training data and 74 data are used as test data. Based on the results of trials with the distribution of datasets, the accuracy obtained was 87.84%. This accuracy is quite large proving that this algorithm works well with given datasets, the Naïve Bayes algorithm is also suitable for similar datasets. Keywords: Accuracy, Algorithm, Dataset, Online, Naïve Bayes
ABSTRACT Many applications provide online buying and selling services where buyers are facilitated in buying and selling transactions. However, in the use of online stores there are several things that make users less satisfied with the online store. This is because the user cannot see the item directly so there are many cases, such as the goods sent and do not match what is in the picture. In this study the authors used the Naive Bayes method to classify the comments that exist in the "X" store that were divided into satisfied and unsatisfied labels. Naive Bayes itself is used in this study because Naive Bayes has simplicity in its computation and according to some previous studies this method is effective for text classification. The author tests the accuracy and classification of comments that exist in online stores with 174 data taken where 100 data are used as training data and 74 data are used as test data. Based on the results of trials with the distribution of datasets, the accuracy obtained was 87.84%. This accuracy is quite large proving that this algorithm works well with given datasets, the Naïve Bayes algorithm is also suitable for similar datasets. Keywords: Accuracy, Algorithm, Dataset, Online, Naïve Bayes
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