A comparison of multiple linear regression and random forest for community concern of youth and young adults survey
The youth and young adults are an essential part of a community’s development. Therefore, an assessment of their concerns and related factors could help reflect the overall situation in the community. In this study, the community problems of concern to youth and young adults in three districts of...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Prince of Songkla University
2022-04-01
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| Series: | Songklanakarin Journal of Science and Technology (SJST) |
| Subjects: | |
| Online Access: | https://rdo.psu.ac.th/sjst/journal/44-2/26.pdf |
| _version_ | 1811242936286838784 |
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| author | Nurin Dureh Attachai Ueranantasan Mayuening Eso |
| author_facet | Nurin Dureh Attachai Ueranantasan Mayuening Eso |
| author_sort | Nurin Dureh |
| collection | DOAJ |
| description | The youth and young adults are an essential part of a community’s development. Therefore, an assessment of their
concerns and related factors could help reflect the overall situation in the community. In this study, the community problems of
concern to youth and young adults in three districts of Pattani province are addressed. The data were collected using a
questionnaire consisting of 31 items for the problems of concern, and targeting 460 youth and young adults in the focus area.
This study aimed to compare the performances of two methods to explore the related factors in the survey data. Those two
methods are multiple linear regression (MLR), representing a conventional statistical method, and random forest (RF),
representing a machine learning approach. In the results, the random forest regression models seemed superior to the multiple
linear regression models in predictive performance and errors. The findings indicate that using RF for data analysis of survey
results can be an alternative to a conventional approach in social sciences research. |
| first_indexed | 2024-04-12T13:59:22Z |
| format | Article |
| id | doaj.art-0e814001999b4d8b97e8df99a0a622a9 |
| institution | Directory Open Access Journal |
| issn | 0125-3395 |
| language | English |
| last_indexed | 2024-04-12T13:59:22Z |
| publishDate | 2022-04-01 |
| publisher | Prince of Songkla University |
| record_format | Article |
| series | Songklanakarin Journal of Science and Technology (SJST) |
| spelling | doaj.art-0e814001999b4d8b97e8df99a0a622a92022-12-22T03:30:15ZengPrince of Songkla UniversitySongklanakarin Journal of Science and Technology (SJST)0125-33952022-04-0144248148710.14456/sjst-psu.2022.66A comparison of multiple linear regression and random forest for community concern of youth and young adults surveyNurin Dureh0Attachai Ueranantasan1Mayuening Eso2Department of Mathematics and Computer Sciences, Faculty of Sciences and Technology, Prince of Songkla University, Pattani Campus, Mueang, Pattani, 94000 ThailandDepartment of Mathematics and Computer Sciences, Faculty of Sciences and Technology, Prince of Songkla University, Pattani Campus, Mueang, Pattani, 94000 ThailandDepartment of Mathematics and Computer Sciences, Faculty of Sciences and Technology, Prince of Songkla University, Pattani Campus, Mueang, Pattani, 94000 ThailandThe youth and young adults are an essential part of a community’s development. Therefore, an assessment of their concerns and related factors could help reflect the overall situation in the community. In this study, the community problems of concern to youth and young adults in three districts of Pattani province are addressed. The data were collected using a questionnaire consisting of 31 items for the problems of concern, and targeting 460 youth and young adults in the focus area. This study aimed to compare the performances of two methods to explore the related factors in the survey data. Those two methods are multiple linear regression (MLR), representing a conventional statistical method, and random forest (RF), representing a machine learning approach. In the results, the random forest regression models seemed superior to the multiple linear regression models in predictive performance and errors. The findings indicate that using RF for data analysis of survey results can be an alternative to a conventional approach in social sciences research.https://rdo.psu.ac.th/sjst/journal/44-2/26.pdfmodelingapplied social sciencemultiple linear regressionrandom forestsurvey |
| spellingShingle | Nurin Dureh Attachai Ueranantasan Mayuening Eso A comparison of multiple linear regression and random forest for community concern of youth and young adults survey Songklanakarin Journal of Science and Technology (SJST) modeling applied social science multiple linear regression random forest survey |
| title | A comparison of multiple linear regression and random forest for community concern of youth and young adults survey |
| title_full | A comparison of multiple linear regression and random forest for community concern of youth and young adults survey |
| title_fullStr | A comparison of multiple linear regression and random forest for community concern of youth and young adults survey |
| title_full_unstemmed | A comparison of multiple linear regression and random forest for community concern of youth and young adults survey |
| title_short | A comparison of multiple linear regression and random forest for community concern of youth and young adults survey |
| title_sort | comparison of multiple linear regression and random forest for community concern of youth and young adults survey |
| topic | modeling applied social science multiple linear regression random forest survey |
| url | https://rdo.psu.ac.th/sjst/journal/44-2/26.pdf |
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