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All Journal Jurnal Syntax Fusion : Jurnal Nasional Indonesia
Usman Pagalay
Universitas Islam Negeri Maulana Malik Ibrahim
Education Engineering Languange, Linguistic, Communication & Media Social Sciences

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Journal : Jurnal Syntax Fusion : Jurnal Nasional Indonesia

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Analisis Perbandingan Metode K-Nn Dan Decision Tree Dalam Klasifikasi Kenyamanan Thermal Bangunan Ilham Yusuf Akbar; Muhammad Faisal; Usman Pagalay
Jurnal Syntax Fusion Vol 2 No 06 (2022): Jurnal Syntax Fusion: Jurnal Nasional Indonesia
Publisher : Rifa' Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54543/fusion.v2i06.197

Abstract

Thermal comfort and good air quality can have a positive influence on a person's health and activities. Human knowledge will determine the right quality for a building or room that can only be used at a minimum first if it is based on the value of temperature and humidity standard measuring instruments that display raw data so that a system is needed that makes it easy for humans to determine thermal building comfort. Most systems that discuss thermal comfort revolve around temperature and humidity monitoring still do not use a machine learning model to maximize data analysis. In this study, a comparison of machine learning models is designed that is able to provide a classification to predict the category or label given to a data set consisting of the thermal comfort variable. The output produced in this comparison is the result of labeling predictions from 3 temperature comfort levels by testing 30% praise data and 70% training data. From the results of the segmentation accuracy level using K-Nearest Neighbor, the accuracy reaches 100% with the highest accuracy at a value of K = 1, while the Decision tree comparison method also gets an accuracy value that reaches 100%, this shows that thermal comfort can be applied in the classification machine learning method
Co-Authors Ilham Yusuf Akbar Muhammad Faisal