KLASIFIKASI KUALITAS AIR MINUM DENGAN METODE LOGISTIC REGRESSION BERBASIS GRID SEARCH OPTIMIZATION

PERMANA, TZALVANO SYAHPUTRA and Zarkasi, Ahmad (2023) KLASIFIKASI KUALITAS AIR MINUM DENGAN METODE LOGISTIC REGRESSION BERBASIS GRID SEARCH OPTIMIZATION. Undergraduate thesis, Sriwijaya University.

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Abstract

Clean water is a vital factor for human survival. The concept of adequate drinking water emphasizes water quality that meets health standards and can be consumed directly. Monitoring and managing water sources is key in maintaining water availability. These efforts are necessary to ensure the quality and continuity of water sources that meet the health standards required for human consumption. This research aims to improve the accuracy of drinking water quality classification through the implementation of a Logistic Regression model based on Grid-Search Optimization. This research uses a dataset from Kaggle and involves program simulations in Python. Model performance evaluation includes accuracy, sensitivity, and specificity. The main features used are pH, conductivity, total dissolved solids, and turbidity level. The results of this research are that the system performance in classifying drinking water shows a very good recall rate, reaching 98%. The best model performance was obtained with a combination of C parameters 0.001, solver liblinear, and max_iter 100, with an average Recall value of 98.70%, Precision 55.77%, Specificity 70.30%, Accuracy 78.11%, Error 21.89 %, And F1-Score 71.27%

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Logistic Regression, Grid-Search Optimization, Klasifikasi, Air Minum
Subjects:	T Technology > TD Environmental technology. Sanitary engineering > TD201-500 Water supply for domestic and industrial purposes
Divisions:	09-Faculty of Computer Science > 56201-Computer Systems (S1)
Depositing User:	tzalvano Syahputra Permana
Date Deposited:	11 Jan 2024 05:58
Last Modified:	11 Jan 2024 05:58
URI:	http://repository.unsri.ac.id/id/eprint/137871

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