Sistem Klasifikasi Pola Perilaku Bendungan Menggunakan K-Nearest Neighbor Berbasis Data Temporal Di Bendungan Djuanda

Fajar Tresnawiguna (Program Studi Teknik Informatika, Universitas Jenderal Achmad Yani)
Yulison Herry Chrisnanto (Program Studi Teknik Informatika, Universitas Jenderal Achmad Yani)
Puspita Nurul Sabrina (Program Studi Teknik Informatika, Universitas Jenderal Achmad Yani)

In Search (Informatic, Science, Entrepreneur, Applied Art, Research, Humanism)
Vol 19 No 2 (2020): In Search

Dam had a vital role in the social and economic communities, including water providers for irrigation, industry, power plant, recreation, and flood control. Besides having various benefits, Dam also holds the potential of disaster. Preventive action in disaster management was necessary. Dam behavior pattern classification with computational assistance was needed to determine the results of determining accurate, fast, and efficient behavior patterns. In this research, the system made by using a K-NN Classifier based on temporal data that formed to predict the behavior patterns of dams in the Djuanda Dam. The system test results produce the best accuracy of 88% for safe labels, 82% for standby labels and 92% for alert labels with the best k value is 8.