Algoritma Naive Bayes Dalam Klasifikasi Lokasi Pembangunan Sumber Air
Tia Imandasari, Eka Irawan, Agus Perdana Windarto, Anjar Wanto · Prosiding Seminar Nasional Riset Information Science (SENARIS) · 2019
The purpose of this study can predict the feasibility of the location of the development of clean water sources in the Tirta Lihou PDAM using the Naive Bayes algorithm. With the increasing number of MBR (Low-Income Communities) that enter each year in each region, the Tirta Lihou PDAM plans to find alternative springs solutions for several production units so that they can meet the needs of the community. In determining the appropriate alternative sources of clean water in several production units, the datamining method is used. By using data mining techniques specifically classification using the Naive Bayes algorithm, predictions can be made on the feasibility of the location of the construction of clean water sources based on existing data. Naive bayes is a simple probabilistic prediction technique based on the Bayes theorem with a strong assumption of independence (dependence). Based on the results of calculations using algoritma naive bayes, the clasification results from 19 alternatives used, where there are 8 feasible classes and 11 classes are not feasible with the number of accuracy obtained at 78,95%. From the results obtained, it is expected that this research can help the PDAM Tirta Lihou in determining the location that is feasible to develop water sources so that it can meet the needs of the community. This research is also expected to be a reference for further researchers relating to the user algorithm used.