Employee performance appraisal is an important process in human resource management that aims to evaluate individual work achievements based on certain criteria set by the organization. This process not only serves to assess the extent to which an employee meets work standards, but also serves as a basis for strategic decision-making, such as job promotions, bonus awards, and career development planning. However, in practice, CV. Surya Perkasa Makassar faces serious obstacles in the form of subjectivity in the assessment process, because the benchmarks used still tend to be based on the likes or dislikes of superiors. This causes the evaluation results to be less objective, inconsistent, and potentially reduce employee work motivation. To overcome these problems, this study aims to develop a decision support system for employee performance appraisal using the Tsukamoto Fuzzy Logic method. This method was chosen because it is able to accommodate uncertainty in the assessment, resulting in more objective, measurable, and consistent decisions. This study uses a Research and Development (R&D) approach with a Black Box Testing method to ensure system functionality. The assessment criteria used include five main aspects, namely work quality, work quantity, discipline, responsibility, and cooperation. Data from these criteria is processed through fuzzification, inference, and defuzzification stages to obtain the final employee performance score. Test results indicate that all system features function as expected. The system is able to prevent data duplication, validate input, and produce accurate final performance scores. The implementation of the Tsukamoto Fuzzy Logic method has proven effective in reducing the level of subjectivity that typically occurs in manual assessments. Therefore, this system can be used as a reliable tool in managerial decision-making, both regarding promotions, bonus awards, and planning employee future career development.