Analysis of House Price Using K-Means and Naïve Bayes Methods Analisis Harga Rumah Dengan Metode K-Means Dan Naïve Bayes

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Published Aug 31, 2024
DOI https://doi.org/10.33050/sensi.v10i2.3480

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Arman Prasojo Sugiyarto
University of Raharja
Nur Hayati
Universitas Nasional Jakarta
Eri Mardiani
Universitas Nasional Jakarta

Abstract

This study aims to compare the performance of the K-Means and Naïve Bayes algorithms in analyzing house prices. The dataset used is a house price dataset obtained from observational results. The study was conducted for approximately 2 months, focusing on the implementation of the K-Means and Naïve Bayes algorithms. The data was processed and analyzed using Orange software, and the results were presented in tables and graphs. The analysis results showed that the K-Means algorithm outperformed the Naïve Bayes algorithm with an accuracy value of 30% for the variable y distance to public facilities and 22% for the variable y land area and 82% with Naïve Bayes calculation. Therefore, it can be concluded that the K-Means method is a more effective method for analyzing house prices.

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How to Cite
Sugiyarto, A., Hayati, N., & Mardiani, E. (2024). Analysis of House Price Using K-Means and Naïve Bayes Methods. Journal Sensi: Strategic of Education in Information System, 10(2), 222-231. https://doi.org/https://doi.org/10.33050/sensi.v10i2.3480
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Vol 10 No 2 (2024): Journal Sensi
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Articles

References

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