<![CDATA[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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