Sistem Klasifikasi Pengaduan Masyarakat Berdasarkan OPD (Organisasi Perangkat Daerah) Menggunakan Pendekatan Ensemble Naive Bayes (Studi Kasus: Dinas Komunikasi, Informatika Dan Statistik Kota Denpasar): English - Ade Yudys Triawan; Satrio Agung Wicaksono; Welly Purnomo (Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya, 2019)
Abstract Pro Denpasar+ is a public complaint managed by the Denpasar City Communication, Information and Statistics Office (CISO) in the form of a forum. Complaints made by the community will then be replied to by the admin or personnel from the designated Regional Device Organization (RDO). However, the admin at CISO as the verifier who examined each complaint felt confused choosing the RDO because of the similarity between complaints. In this case CISO requires a system that can classify complaints that can help the verifier in determining the destination RDO. The method used is text mining. One of the uses of text mining is classification using Ensemble Naive Bayes. Naive Bayes is a statistical classification that uses probability calculations to predict class membership in tuple data into a particular class. Ensemble technique is a technique of combining the results of various specific models to produce the best model. The results of the functional requirements of the system are 6 functional requirements and the design produces 6 use cases and 15 classes. The implementation uses the JAVA programming language with the WEKA library on classification and MYSQL on the database. Validation testing produces a value of 100% with the results of Confusion Matrix using a 90:10 ratio resulting in an accuracy value of 91.8182% while the value of area under ROC produces a value of 0.982825. In addition, the value of User Acceptance Testing produces a value of 97.5%.