Generally, the selection of outstanding students in every school still uses the report value as the reference and it is done manually. It is required a system that may select the outstanding students accordance with the criteria and done automatically. In this study, it was developed an automatic system for selecting outstanding students by using Simple Additive Weighting (SAW) concept. The criteria set by the school in the selection of outstanding students are the average of the first and the second semester score, the achievements on district, city, and national level, liveliness in the organization and extracurricular, and credit point of attitude. Method of investigation used in this study is R & D, including introduction study, the development of system consisting of the application of SAW method and designing waterfall method, and testing of system which done by testing the comparison of the result and respond of users. The result of black box testing showed that all functionality in the system run well and appropriate; while for the white box showed that all paths run in accordance with SAW method. For the result of the comparison testing showed that the validation level was 100%. The result of the users respond revealed that the average of teacher responds was 90% and the students respond was 80, 34%. Therefore it can be concluded that decision support system by using SAW method can determine the outstading students.
Semarang State University, Education and Professional Development Institute (LP3) is a public service institution integrated with the Semarang State University Institute (UNNES). As a public service institution, LP3 is bound by regulations related to service satisfaction and service statistics as part of public accountability. In fact, as a public service institution overseeing services in the fields of PPL, PPG, MKU / MKDK, Career and Counselling, as well as Language and Training services, LP3 does not yet have a qualified DSS. An outline of the research method used in detail was explained as follows: Retrieve Data; Development System; Operation. Based on the results and discussion, it can be seen that building a LPS DSS requires quite a long time. The data in LP3 comes from inhomogeneous forms and varied sources. We conclude that the DSS of LP3 UNNES was going well. The website of data.lp3.unnes.ac.id can be utilized by the community as a decision support system.
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