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Zalika Riswan Dini
Universitas Pembangunan Panca Budi
Computer Science & IT

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Implementation Of The Naive Bayes Method To Classification Good Air Quality Zalika Riswan Dini; Dedi Purwanto; Nova Mayasari
INFOKUM Vol. 10 No. 1 (2021): Desember, Data Mining, Image Processing, and artificial intelligence
Publisher : Sean Institute

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Abstract

Naïve Bayesisa- method- of doing statistical classification based on the probability value of the members in the class on a data. This research was conducted by finding several stages of the process carried out, namely the process of sharing training data and test data. Then the-classification-process-is-carried-out by-finding the-accuracy-value-of-the-Naïve-Bayes method. The success of increasing the-accuracy-of-the-dataset-using-the-weighting-of-the Naïve Bayes algorithm which greatly affects all attributes, so that it greatly affects the-accuracy-of-the-data. -In-the-data classification-process-using the Naïve Bayes algorithm that uses the Air Quality dataset, the accuracy results are 39.97%. The author hopes that there will be development of the Naïve Bayes method by comparing it to other weighting methods in order to get various kinds of analysis results so as to get a higher accuracy value and use more datasets.
Co-Authors Dedi Purwanto Nova Mayasari