WEATHER CLASSIFICATION USING NAIVE BAYES CLASSIFICATION

PRATAMA, ANTONIUS ANGGA ANDRI (2018) WEATHER CLASSIFICATION USING NAIVE BAYES CLASSIFICATION. Other thesis, Unika Soegijapranata Semarang.

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Abstract

ABSTRACT The changes of the weather attract scientists to conduct research on weather classification. Some factors could influence in the change of the weather such temperature, humidity and rainfall. This project uses data mining method to classify the weather. There are many data mining methods that can be used to classify the weather. And this project will analyze one of data mining method that is naive bayes classification to do weather classification. An aspect that being reference to be analyzed in this project is finding dominant parameter that affect in weather classification. There are eight parameters to be used on this project that is temperature, air pressure, humidity, dew point, wind speed, visibility, heat index, and weather condition. Based on the implementation and testing, the order of the parameter that affect in change of weather from the most dominant is visibility, heat index, pressure, humidity, temperature, dew point, and wind speed. While the highest accuracy from system is 65,9%, with precision reached 44,776%, and recall reached 40,4% using parameter visibility and heat index. keyword: weather classification, data mining, naive bayes classification

Item Type: Thesis (Other)
Subjects: 000 Computer Science, Information and General Works > 005 Computer programming, programs & data > Information Systems
Divisions: Faculty of Computer Science > Department of Informatics Engineering
Depositing User: Mr Lucius Oentoeng
Date Deposited: 21 Jun 2018 04:28
Last Modified: 03 Jun 2021 02:05
URI: http://repository.unika.ac.id/id/eprint/16184

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