PERMANA, TZALVANO SYAHPUTRA and Zarkasi, Ahmad (2023) KLASIFIKASI KUALITAS AIR MINUM DENGAN METODE LOGISTIC REGRESSION BERBASIS GRID SEARCH OPTIMIZATION. Undergraduate thesis, Sriwijaya University.
Text
RAMA_56201_09011181924014.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (5MB) | Request a copy |
|
Text
RAMA_56201_09011181924014 _TURNITIN.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (8MB) | Request a copy |
|
Text
RAMA_56201_09011181924014_0225087902_01_front_ref .pdf - Accepted Version Available under License Creative Commons Public Domain Dedication. Download (1MB) |
|
Text
RAMA_56201_09011181924014_0225087902_02.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (786kB) | Request a copy |
|
Text
RAMA_56201_09011181924014_0225087902_03.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (553kB) | Request a copy |
|
Text
RAMA_56201_09011181924014_0225087902_04.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (272kB) | Request a copy |
|
Text
RAMA_56201_09011181924014_0225087902_05.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (7kB) | Request a copy |
|
Text
RAMA_56201_09011181924014_0225087902_06_ref.pdf - Bibliography Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (84kB) | Request a copy |
|
Text
RAMA_56201_09011181924014_0225087902_07_lamp.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (837kB) | Request a copy |
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 |
Actions (login required)
View Item |