Systematic Literature Review: Analisa Sentimen Masyarakat terhadap Penerapan Peraturan ETLE
This study examines the efforts to develop a model for analyzing public sentiment regarding applying ETLE (Electronic Traffic Law Enforcement) regulations. The method used is the systematic literature review. A systematic literature review (SLR) consists of three stages: planning, conducting, and r...
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| Format: | Article |
| Language: | Indonesian |
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Indonesian Society of Applied Science (ISAS)
2023-07-01
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| Series: | Journal of Applied Computer Science and Technology |
| Subjects: | |
| Online Access: | https://journal.isas.or.id/index.php/JACOST/article/view/493 |
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| _version_ | 1849240274502418432 |
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| author | Syafrial Fachri Pane Muhammad Syiarul Amrullah |
| author_facet | Syafrial Fachri Pane Muhammad Syiarul Amrullah |
| author_sort | Syafrial Fachri Pane |
| collection | DOAJ |
| description |
This study examines the efforts to develop a model for analyzing public sentiment regarding applying ETLE (Electronic Traffic Law Enforcement) regulations. The method used is the systematic literature review. A systematic literature review (SLR) consists of three stages: planning, conducting, and reporting. The planning stage is the determination of the SLR procedure. This stage includes preparing topics, research questions, article search criteria & inclusion and exclusion criteria. The conducting stage, namely the implementation, includes searching for articles and filtering articles. The reporting stage is the final stage of SLR. This stage includes writing the SLR results according to the article format. The explanation follows: First, hybrid is the most widely used method in developing sentiment analysis models. Apart from hybrid, several methods are used to develop sentiment analysis models, including multi-task, deep, and machine learning. Each has its advantages and disadvantages in the development of sentiment analysis models. Second, this study shows the development of a model with superior performance, namely using XGBoost as a sentiment analysis model, and the stages it goes through are preprocessing data, handling imbalanced data, and optimizing the model. Therefore, the model for analyzing public sentiment regarding the application of ETLE regulations can be an option for hybrid methods, multi-task learning, deep learning, machine learning, and the XGBoost model to obtain superior performance with preprocessing data stages, handling imbalanced data and optimization models.
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| format | Article |
| id | doaj-art-11d0321f14174f7c9d23a467df3dd0b7 |
| institution | Kabale University |
| issn | 2723-1453 |
| language | Indonesian |
| publishDate | 2023-07-01 |
| publisher | Indonesian Society of Applied Science (ISAS) |
| record_format | Article |
| series | Journal of Applied Computer Science and Technology |
| spelling | doaj-art-11d0321f14174f7c9d23a467df3dd0b72025-08-20T04:00:40ZindIndonesian Society of Applied Science (ISAS)Journal of Applied Computer Science and Technology2723-14532023-07-014110.52158/jacost.v4i1.493493Systematic Literature Review: Analisa Sentimen Masyarakat terhadap Penerapan Peraturan ETLESyafrial Fachri Pane0Muhammad Syiarul Amrullah1Universitas Logistik dan Bisnis Internasional - ULBIUniversitas Logisitik dan Bisnis Internasional This study examines the efforts to develop a model for analyzing public sentiment regarding applying ETLE (Electronic Traffic Law Enforcement) regulations. The method used is the systematic literature review. A systematic literature review (SLR) consists of three stages: planning, conducting, and reporting. The planning stage is the determination of the SLR procedure. This stage includes preparing topics, research questions, article search criteria & inclusion and exclusion criteria. The conducting stage, namely the implementation, includes searching for articles and filtering articles. The reporting stage is the final stage of SLR. This stage includes writing the SLR results according to the article format. The explanation follows: First, hybrid is the most widely used method in developing sentiment analysis models. Apart from hybrid, several methods are used to develop sentiment analysis models, including multi-task, deep, and machine learning. Each has its advantages and disadvantages in the development of sentiment analysis models. Second, this study shows the development of a model with superior performance, namely using XGBoost as a sentiment analysis model, and the stages it goes through are preprocessing data, handling imbalanced data, and optimizing the model. Therefore, the model for analyzing public sentiment regarding the application of ETLE regulations can be an option for hybrid methods, multi-task learning, deep learning, machine learning, and the XGBoost model to obtain superior performance with preprocessing data stages, handling imbalanced data and optimization models. https://journal.isas.or.id/index.php/JACOST/article/view/493sentiment analysisSystematic Literature ReviewMachine LearningSocial MediaNatural Language Processing |
| spellingShingle | Syafrial Fachri Pane Muhammad Syiarul Amrullah Systematic Literature Review: Analisa Sentimen Masyarakat terhadap Penerapan Peraturan ETLE Journal of Applied Computer Science and Technology sentiment analysis Systematic Literature Review Machine Learning Social Media Natural Language Processing |
| title | Systematic Literature Review: Analisa Sentimen Masyarakat terhadap Penerapan Peraturan ETLE |
| title_full | Systematic Literature Review: Analisa Sentimen Masyarakat terhadap Penerapan Peraturan ETLE |
| title_fullStr | Systematic Literature Review: Analisa Sentimen Masyarakat terhadap Penerapan Peraturan ETLE |
| title_full_unstemmed | Systematic Literature Review: Analisa Sentimen Masyarakat terhadap Penerapan Peraturan ETLE |
| title_short | Systematic Literature Review: Analisa Sentimen Masyarakat terhadap Penerapan Peraturan ETLE |
| title_sort | systematic literature review analisa sentimen masyarakat terhadap penerapan peraturan etle |
| topic | sentiment analysis Systematic Literature Review Machine Learning Social Media Natural Language Processing |
| url | https://journal.isas.or.id/index.php/JACOST/article/view/493 |
| work_keys_str_mv | AT syafrialfachripane systematicliteraturereviewanalisasentimenmasyarakatterhadappenerapanperaturanetle AT muhammadsyiarulamrullah systematicliteraturereviewanalisasentimenmasyarakatterhadappenerapanperaturanetle |