Skripsi

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

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Penilaian

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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%

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2407000810	T137871	T1378712023	Central Library (Referens)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T1378712023

Publisher

Inderalaya : Prodi Sistem Komputer, Fakultas Ilmu Komputer Uniersitas Sriwijaya., 2023

Collation

xiii, 76 hlm.; Ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

005.120 7

Content Type

Text

Media Type

unmediated

Carrier Type

-

Edition

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Subject(s)

Sistem Analisa Dan Desain Perangkat Lunak
Prodi Sistem Komputer

Specific Detail Info

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Statement of Responsibility

SEPTA

Other version/related

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