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STMIK Nurdin Hamzah Jambi routinely rewards lecturers with the best tridarma performance of tertiary institutions every year. Through this award every lecturer is expected to be motivated to become better and always improve the quality of performance. In carrying out this assessment, STMIK Nurdin Hamzah Jambi formed a special team. The problem faced by this team is the difficulty in determining the decision of lecturers who are chosen to be lecturers with the best tridarma performance with criteria that have subjective or uncertain nature quickly. To overcome these problems, a decision support system was designed for the assessment of lecturers with the best tridarma performance of tertiary institutions using the Weight Product Method (WP). This study aims to build a software application that can help give consideration to decision makers in the selection of lecturers with the best tridarma performance of tertiary institutions at STMIK Nurdin Hamzah Jambi using the Weight Product (WP) method. The input needs are in the form of lecturer data, assessment criteria data, sub criteria, tridarma lecturer performance data of lecturers, and criteria weight data. The criteria used cover 3 fields, namely: Education and Teaching, Research, and Community Service, which consists of Student Assessment, Peer Lecturer Assessment, Leadership/Management Assessment, Academic Qualification, Research, Journal, Training, Seminar, Community Service Society, and Academic Position. The output produced in the form of a report on the results of the selection assessment, reports in the form of graphics, and reports on the results of the performance evaluation of the three-tier lecturers of tertiary institutions. From the results of the evaluation evaluation of the performance of the tridarma of the lecturer of the Informatics Engineering Study Program in the even semester of the Academic Year 2018/2019, the highest score was obtained on behalf of Lucy Simorangkir, S.Kom, M.Kom. as a lecturer with the best Tridarma tertiary performance.