Classification of LPG Gas Usage Satisfaction Level Using The Naïve Bayes Algorithm

Angelia Melani Adrian, Bella Alisia Patras, Junaidy B. Sanger
DOI: https://doi.org/10.33650/jeecom.v7i1.11064



Abstract

LPG gas is a very important energy source in everyday life for cooking activities. Although the importance of LPG gas in supporting everyday life has been widely recognized, satisfaction with the use of LPG gas is an issue that should not be ignored. Often products or services that do not meet customer expectations can cause dissatisfaction. This can be caused by low quality, prices that do not match the quality received, or not in accordance with user expectations.

This study aims to classify the level of satisfaction of LPG gas usage using the Naïve Bayes algorithm. The data obtained from the survey results are 250 data using 5 attributes, namely meeting needs, good quality, affordable prices, repurchasing, and recommending products. And using 2 classes, namely satisfied and dissatisfied.

The model achieved an accuracy of 89.3% with a 70:30 training-to-test data split, 91.2% with an 80:20 split, and 94.0% with a 60:40 split, indicating that performance varied based on the proportion of training and test data used.


Keywords

Classification; Data Mining; LPG Gas; Satisfaction Level; Naïve Bayes Algorithm

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10.33650/jeecom.v7i1.11064


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Creative Commons License
 
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

Journal of Electrical Engineering and Computer (JEECOM)
Published by LP3M Nurul Jadid University, Indonesia, Probolinggo, East Java, Indonesia.