SISTEM PREDIKSI HUJAN MENGGUNAKAN NAÏVE BAYES
Keywords:
naive bayes, rain prediction, classificationAbstract
Rain prediction is a technique of estimating a condition at a certain time which is expressed by the value of features such as air temperature, evaporation, wind speed, humidity and other attributes as the main attributes. The output of rain predictions influences human work activities in the fields of sea and air transportation, agriculture, sports, and many more. The rain prediction system design was built using the Naive Bayes method based on reference data to determine whether it will rain or not rain tomorrow. The test results show that the results of rain prediction classification using Naive Bayes obtained an accuracy value of 92.09% with a precision value of 99.91% and a recall value of 90.1%
References
C. Kunjumon,S.S. Nair, Deepa Rajan ,2018, Survey on Weather Forecasting Using Data Mining, Proc. IEEE Conference on Emerging Devices and Smart Systems (ICEDSS 2018), India
Patil, T.R., Sherekar, M.S., Performance Analysis of Naive Bayes and J48 Classification Algorithm for Data Classification, International Journal of Computer Science and Applications, Vol. 6, No. 2, Hal 256 - 261.
Yu, L., dan H Liu. 2003. Feature Selection for High Dimensional Data: A Fast Correlation-Based Filter Solution. www.hpl.hp.com/conferences/icml2003/papers/144.pdf.
A. Indriani, “Klasifikasi Data Forum dengan menggunakan Metode Naïve Bayes Classifier,” p. 6, 2014.
J. Han, M. Kamber dan J. Pei, Data Mining Concepts and Techniques, Waltham:Morgan Kaufmann, 2012.
D. T. Wahyuni, T. Sutojo dan A. Luthfiarta, “Prediksi Hasil Pemilu Legislatif Dki Jakarta Menggunakan Naive Bayes dengan Algoritma Genetika Sebagai Fitur Seleksi,” 2014.
