<![CDATA[The selection of the right laboratory assistant is very important to support the smooth running of the practicum process in the academic environment. However, conventional selection methods still have weaknesses, such as subjectivity in assessment and time-consuming processes. Therefore, this study develops a decision model based on Tsukamoto fuzzy logic to improve the objectivity and efficiency of laboratory assistant selection. This model uses five main criteria in the assessment, namely academic grades, expertise, ethics, programming tests, and communication skills. The results of the study indicate that the Tsukamoto fuzzy method can produce more transparent and accurate decisions compared to conventional methods. Trials with several candidates show that this model is able to categorize candidates based on the level of eligibility with high accuracy and a margin of error of 0%. Thus, the implementation of this method is expected to improve the effectiveness of the laboratory assistant selection process more fairly and efficiently.]]>
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