Penerapan Metode Naïve Bayes Untuk Klasifikasi Sms Spam Menggunakan Java Rogramming


Eko Ardian Pranata Subari Subari Go Frendi Gunawan


Short Message Service (SMS) is one of the communication services for sending and receiving short messages in the form of text on cell phones (cellphones). SMS is still used every day because of its ease of use, simple, fast, and inexpensive. The increasing use of SMS is used by many parties to benefit, one of which is sending spam via SMS. The method used is a probabilistic approach in making inferences that is based on Bayes theorem in general. Training data used in the categorization process is obtained from journals and already has a previous category, namely SMS spam and not spam. Application in Indonesian-language SMS, which has a certain morphology in categorizing processing. The application performs several stages in processing including preprocessing in the form of case folding, and parsing, transformation in the form of stopword removal and stemming, frequency and probability calculation and naïve bayes calculation. The categorization produced by the application compared to manual categorization has an average precision of 24%, recall 88% and Confusion Matrix (Accuracy) of 62%.


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