ALGORITMA KLASIFIKASI DATA MINING NAÃVE BAYES UNTUK DETEKSI SESEORANG KECANDUAN GAME ONLINE
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Institusion
Institut Teknologi Perusahaan Listrik Negara
Author
DARMAWAN, M. FAQIH ARYA
Widiyanto, Max Teja Ajie Cipta
Yudho, Satrio
Widiyanto, Max Teja Ajie Cipta
Yudho, Satrio
Subject
Teknik Informatika
Datestamp
2022-09-20 03:07:44
Abstract :
Classification algorithms are usually used to predict the possibility that will occur and improve decision making in the future based on information obtained from the past. One of the best classification methods because it has several advantages, namely, fast in the calculation process, simple algorithm and also high accuracy. Online game addiction is a mental illness that is not given much attention, so its existence is always underestimated as if it doesn't exist. In fact, this disease is quite disturbing and affects productivity. In this study, it will predict how addicted a person is to online games and also compare the accuracy results obtained with previous studies. Measurements with Naives Bayes yielded an accuracy of 84.21%.
Classification algorithms are usually used to predict the possibility that will occur and improve decision making in the future based on information obtained from the past. One of the best classification methods because it has several advantages, namely, fast in the calculation process, simple algorithm and also high accuracy. Online game addiction is a mental illness that is not given much attention, so its existence is always underestimated as if it doesn't exist. In fact, this disease is quite disturbing and affects productivity. In this study, it will predict how addicted a person is to online games and also compare the accuracy results obtained with previous studies. Measurements with Naives Bayes yielded an accuracy of 84.21%.
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