{"title":"Development of Multiple Linear Regression Model to Predict COD Concentration based on West Tarum Canal Surface Water Quality Data","authors":"J. David, R. Hakiki","doi":"10.33021/JENV.V6I1.1416","DOIUrl":null,"url":null,"abstract":"<strong><span style=\"font-size: 10.0pt; font-family: 'Calibri Light',sans-serif; mso-fareast-font-family: 'Times New Roman'; mso-bidi-font-family: Arial; mso-ansi-language: EN-US; mso-fareast-language: AR-SA; mso-bidi-language: AR-SA;\" lang=\"EN-US\">Abstract. </span></strong><span style=\"font-size: 10.0pt; font-family: 'Calibri Light',sans-serif; mso-fareast-font-family: 'Times New Roman'; mso-bidi-font-family: Arial; mso-ansi-language: EN-US; mso-fareast-language: AR-SA; mso-bidi-language: AR-SA; mso-bidi-font-weight: bold;\" lang=\"EN-US\">COD level indicates the organic matter pollution in water. A predictive analysis, such as Multiple Linear Regression, could be an option to make the COD measurement more effective. <strong>Objectives:</strong></span><span style=\"font-size: 10.0pt; font-family: 'Calibri Light',sans-serif; mso-fareast-font-family: 'Times New Roman'; mso-bidi-font-family: Arial; mso-ansi-language: EN-US; mso-fareast-language: AR-SA; mso-bidi-language: AR-SA; mso-bidi-font-weight: bold;\" lang=\"EN-US\">This research aims to determine the parameter that can predict COD concentration using correlation analysis and develop a Multiple Linear Regression Model for predictive analysis on COD level in the West Tarum Canal surface water. <strong>Method and results:</strong> The correlation analysis is done in Microsoft Excel using the Pearson Product Moment Correlation Analysis. The water quality dataset is inputted to the R Studio and made the MLR model. The model is validated using t-Test. The result showed that all models in all intake points are not showing good prediction results, and the predictors showed no effect on the COD level. <strong>Conclusion:</strong> The Multiple Linear Regression is not a fit tool for predicting the COD in the West Tarum Canal surface water. </span><a style=\"mso-comment-reference: rh_1; mso-comment-date: 20201202T0302; mso-comment-done: yes;\"><strong style=\"mso-bidi-font-weight: normal;\"><span style=\"font-size: 10.0pt; font-family: 'Calibri Light',sans-serif; mso-fareast-font-family: 'Times New Roman'; mso-bidi-font-family: Arial; mso-ansi-language: EN-US; mso-fareast-language: AR-SA; mso-bidi-language: AR-SA;\" lang=\"EN-US\">Abstract</span></strong></a><span class=\"MsoCommentReference\"><span style=\"font-size: 8.0pt; font-family: 'New York',serif; mso-fareast-font-family: 'Times New Roman'; mso-bidi-font-family: 'New York'; mso-ansi-language: EN-US; mso-fareast-language: AR-SA; mso-bidi-language: AR-SA;\" lang=\"EN-US\"><!--[if !supportAnnotations]--><a id=\"_anchor_1\" class=\"msocomanchor\" name=\"_msoanchor_1\" href=\"file:///J:/THESIS/THESIS%20DOCUMENTS/JOURNAL%20SEMINAR/SUBMIT%20JENV/Julio%20Putra%20David_Development%20of%20Multiple%20Linear%20Regression%20Model%20to%20Predict%20COD%20Concentration%20based%20on%20West%20Tarum%20Canal%20Surface%20Water%20Quality%20Data.docx#_msocom_1\"></a>[rh1]<!--[endif]--><span style=\"mso-special-character: comment;\"> </span></span></span><strong style=\"mso-bidi-font-weight: normal;\"><span style=\"font-size: 10.0pt; font-family: 'Calibri Light',sans-serif; mso-fareast-font-family: 'Times New Roman'; mso-bidi-font-family: Arial; mso-ansi-language: EN-US; mso-fareast-language: AR-SA; mso-bidi-language: AR-SA;\" lang=\"EN-US\">. </span></strong><span style=\"font-size: 10.0pt; font-family: 'Calibri Light',sans-serif; mso-fareast-font-family: 'Times New Roman'; mso-bidi-font-family: Arial; mso-ansi-language: EN-US; mso-fareast-language: AR-SA; mso-bidi-language: AR-SA; mso-bidi-font-weight: bold;\" lang=\"EN-US\">COD level indicates the organic matter pollution in water. A predictive analysis, such as Multiple Linear Regression, could be an option to make the COD measurement more effective. <span style=\"mso-spacerun: yes;\"> </span><a style=\"mso-comment-reference: rh_2; mso-comment-date: 20201202T0249; mso-comment-done: yes;\"><strong>Objectives</strong></a></span><span class=\"MsoCommentReference\"><span style=\"font-size: 8.0pt; font-family: 'New York',serif; mso-fareast-font-family: 'Times New Roman'; mso-bidi-font-family: 'New York'; mso-ansi-language: EN-US; mso-fareast-language: AR-SA; mso-bidi-language: AR-SA;\" lang=\"EN-US\"><!--[if !supportAnnotations]--><a id=\"_anchor_2\" class=\"msocomanchor\" name=\"_msoanchor_2\" href=\"file:///J:/THESIS/THESIS%20DOCUMENTS/JOURNAL%20SEMINAR/SUBMIT%20JENV/Julio%20Putra%20David_Development%20of%20Multiple%20Linear%20Regression%20Model%20to%20Predict%20COD%20Concentration%20based%20on%20West%20Tarum%20Canal%20Surface%20Water%20Quality%20Data.docx#_msocom_2\"></a>[rh2]<!--[endif]--><span style=\"mso-special-character: comment;\"> </span></span></span><strong><span style=\"font-size: 10.0pt; font-family: 'Calibri Light',sans-serif; mso-fareast-font-family: 'Times New Roman'; mso-bidi-font-family: Arial; mso-ansi-language: EN-US; mso-fareast-language: AR-SA; mso-bidi-language: AR-SA;\" lang=\"EN-US\">:</span></strong><span style=\"font-size: 10.0pt; font-family: 'Calibri Light',sans-serif; mso-fareast-font-family: 'Times New Roman'; mso-bidi-font-family: Arial; mso-ansi-language: EN-US; mso-fareast-language: AR-SA; mso-bidi-language: AR-SA; mso-bidi-font-weight: bold;\" lang=\"EN-US\">This research aims to determine the parameter that can predict COD concentration using correlation analysis and develop a Multiple Linear Regression Model for predictive analysis on COD level in the West Tarum Canal surface water. <a style=\"mso-comment-reference: rh_3; mso-comment-date: 20201202T0301; mso-comment-done: yes;\"><strong>Method and results</strong></a></span><span class=\"MsoCommentReference\"><span style=\"font-size: 8.0pt; font-family: 'New York',serif; mso-fareast-font-family: 'Times New Roman'; mso-bidi-font-family: 'New York'; mso-ansi-language: EN-US; mso-fareast-language: AR-SA; mso-bidi-language: AR-SA;\" lang=\"EN-US\"><!--[if !supportAnnotations]--><a id=\"_anchor_3\" class=\"msocomanchor\" name=\"_msoanchor_3\" href=\"file:///J:/THESIS/THESIS%20DOCUMENTS/JOURNAL%20SEMINAR/SUBMIT%20JENV/Julio%20Putra%20David_Development%20of%20Multiple%20Linear%20Regression%20Model%20to%20Predict%20COD%20Concentration%20based%20on%20West%20Tarum%20Canal%20Surface%20Water%20Quality%20Data.docx#_msocom_3\"></a>[rh3]<!--[endif]--><span style=\"mso-special-character: comment;\"> </span></span></span><strong><span style=\"font-size: 10.0pt; font-family: 'Calibri Light',sans-serif; mso-fareast-font-family: 'Times New Roman'; mso-bidi-font-family: Arial; mso-ansi-language: EN-US; mso-fareast-language: AR-SA; mso-bidi-language: AR-SA;\" lang=\"EN-US\">:</span></strong><span style=\"font-size: 10.0pt; font-family: 'Calibri Light',sans-serif; mso-fareast-font-family: 'Times New Roman'; mso-bidi-font-family: Arial; mso-ansi-language: EN-US; mso-fareast-language: AR-SA; mso-bidi-language: AR-SA; mso-bidi-font-weight: bold;\" lang=\"EN-US\"> The correlation analysis is done in Microsoft Excel using the Pearson Product Moment Correlation Analysis. The water quality dataset is inputted to the R Studio and made the MLR model. The model is validated using t-Test. The result showed that all models in all intake points are not showing good prediction results, and the predictors showed no effect on the COD level. <a style=\"mso-comment-reference: rh_4; mso-comment-date: 20201202T0301; mso-comment-done: yes;\"><strong>Conclusion</strong></a></span><span class=\"MsoCommentReference\"><span style=\"font-size: 8.0pt; font-family: 'New York',serif; mso-fareast-font-family: 'Times New Roman'; mso-bidi-font-family: 'New York'; mso-ansi-language: EN-US; mso-fareast-language: AR-SA; mso-bidi-language: AR-SA;\" lang=\"EN-US\"><!--[if !supportAnnotations]--><a id=\"_anchor_4\" class=\"msocomanchor\" name=\"_msoanchor_4\" href=\"file:///J:/THESIS/THESIS%20DOCUMENTS/JOURNAL%20SEMINAR/SUBMIT%20JENV/Julio%20Putra%20David_Development%20of%20Multiple%20Linear%20Regression%20Model%20to%20Predict%20COD%20Concentration%20based%20on%20West%20Tarum%20Canal%20Surface%20Water%20Quality%20Data.docx#_msocom_4\"></a>[rh4]<!--[endif]--><span style=\"mso-special-character: comment;\"> </span></span></span><strong><span style=\"font-size: 10.0pt; font-family: 'Calibri Light',sans-serif; mso-fareast-font-family: 'Times New Roman'; mso-bidi-font-family: Arial; mso-ansi-language: EN-US; mso-fareast-language: AR-SA; mso-bidi-language: AR-SA;\" lang=\"EN-US\">:</span></strong><span style=\"font-size: 10.0pt; font-family: 'Calibri Light',sans-serif; mso-fareast-font-family: 'Times New Roman'; mso-bidi-font-family: Arial; mso-ansi-language: EN-US; mso-fareast-language: AR-SA; mso-bidi-language: AR-SA; mso-bidi-font-weight: bold;\" lang=\"EN-US\"> The Multiple Linear Regression is not a fit tool for predicting the COD in the West Tarum Canal surface water. </span><div style=\"mso-element: comment-list;\"><!--[if !supportAnnotations]--><hr class=\"msocomoff\" align=\"left\" size=\"1\" width=\"33%\" /><!--[endif]--><div style=\"mso-element: comment;\"><!--[if !supportAnnotations]--><div id=\"_com_1\" class=\"msocomtxt\"><!--[endif]--><span style=\"mso-comment-author: rhakiki;\"><!--[if !supportAnnotations]--></span><p class=\"MsoCommentText\"> </p></div></div><div style=\"mso-element: comment;\"><div id=\"_com_4\" class=\"msocomtxt\"><!--[if !supportAnnotations]--></div><!--[endif]--></div></div>","PeriodicalId":371727,"journal":{"name":"Journal of Environmental Engineering and Waste Management","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Environmental Engineering and Waste Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.33021/JENV.V6I1.1416","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract. COD level indicates the organic matter pollution in water. A predictive analysis, such as Multiple Linear Regression, could be an option to make the COD measurement more effective. Objectives:This research aims to determine the parameter that can predict COD concentration using correlation analysis and develop a Multiple Linear Regression Model for predictive analysis on COD level in the West Tarum Canal surface water. Method and results: The correlation analysis is done in Microsoft Excel using the Pearson Product Moment Correlation Analysis. The water quality dataset is inputted to the R Studio and made the MLR model. The model is validated using t-Test. The result showed that all models in all intake points are not showing good prediction results, and the predictors showed no effect on the COD level. Conclusion: The Multiple Linear Regression is not a fit tool for predicting the COD in the West Tarum Canal surface water. Abstract[rh1]. COD level indicates the organic matter pollution in water. A predictive analysis, such as Multiple Linear Regression, could be an option to make the COD measurement more effective. Objectives[rh2]:This research aims to determine the parameter that can predict COD concentration using correlation analysis and develop a Multiple Linear Regression Model for predictive analysis on COD level in the West Tarum Canal surface water. Method and results[rh3]: The correlation analysis is done in Microsoft Excel using the Pearson Product Moment Correlation Analysis. The water quality dataset is inputted to the R Studio and made the MLR model. The model is validated using t-Test. The result showed that all models in all intake points are not showing good prediction results, and the predictors showed no effect on the COD level. Conclusion[rh4]: The Multiple Linear Regression is not a fit tool for predicting the COD in the West Tarum Canal surface water.
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