Penerapan Data Mining Untuk Prediksi Perkiraan Hujan dengan Menggunakan Algoritma K-Nearest Neighbor
-
Nursobah Nursobah
*
STMIK Widya Cipta Dharma, Samarinda,
Indonesia
- Siti Lailiyah STMIK Widya Cipta Dharma, Samarinda, Indonesia
- Bartolomius Harpad STMIK Widya Cipta Dharma, Samarinda, Indonesia
- Muhammad Fahmi STMIK Widya Cipta Dharma, Samarinda, Indonesia (*) Corresponding Author
Abstract
Rain is a condition where water droplets fall from clouds to the earth. In life, the presence of rain is highly anticipated, rain can help people who have a profession as farmers. Rain that occurs on a large scale will really provide obstacles for the community, in addition to hampering activities or activities especially those carried out on outdoor rain can also cause disaster for the community in the form of flooding. Estimating rain for the community is very important, knowing whether it will rain or not can make it easier for the community to anticipate the possibilities that may occur due to rain. However, in the process of delivering forecasts, there is often an uneven distribution of information and delays in conveying information to the public regarding whether or not rain will occur. The community should be able to independently predict whether or not rain will occur. Data processing should be done properly and correctly. Data mining is a way that can be done to assist in data processing. In this study, the settlement process will be carried out using the K-Nearest Neighbor (K-NN) algorithm. The results obtained show that the data testing decision is NO. In other words, data mining and the K-Nearest Neighbor algorithm can help the problem solving process
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