skip to main content

Students Major Determination Decision Support Systems using Profile Matching Method with SMS Gateway Implementation

Lilis Sopianti  -  Informatics Department, Faculty of Sciences and Mathematics, Diponegoro University, Indonesia
*Nurdin Bahtiar  -  Informatics Department, Faculty of Sciences and Mathematics, Diponegoro University, Indonesia

Citation Format:

In the implementation of curriculum 2013 at high school level, the majoring for students was started from the level of class 10. The available major options are Math and Natural Sciences (MIA), Social Sciences (IIS), and Linguistics and Cultures (IBB). The process of determining the major was conducted by the counseling teacher through a careful selection based on several criteria including grades, graduation test scores, record of accomplishment, student's selected major, and psychological test results. During the process of determining the major, the school often has to deal with several constraints associated with the standard acceptance rules from each major department. To deal with these constraints and minimize the occurrence of human errors, it needs a Decision Support System to carry out the process. In this study, the system is made to apply the Profile Matching method. Profile Matching method calculated the competence of each individual based on given criteria. The implementation of Profile Matching method is optimized by placing core and secondary factor dynamically on each majoring department in order to obtain an ideal results from the majoring selection process. In order to provide added value to the system, an SMS Gateway feature has been installed to help broadcasting the majoring selection results to the participating students.

Fulltext View|Download

Last update:

No citation recorded.

Last update: 2024-05-18 11:33:56

  1. Generic decision support model for determining the best marketer

    Utama D.N.. Advances in Science, Technology and Engineering Systems, 5 (4), 2020. doi: 10.25046/AJ050498
  2. Generic model of fuzzy profile matching for determining the best marketer

    Oktafiani S.. International Journal of Advanced Trends in Computer Science and Engineering, 9 (1), 2020. doi: 10.30534/ijatcse/2020/123912020
  3. Predicting high school graduates using Naive Bayes in State University Entrance Selections

    Muladi . 4th International Conference on Vocational Education and Training, ICOVET 2020, 2020. doi: 10.1109/ICOVET50258.2020.9230336
  4. Optimation economic order quantity method for a support system reorder point stock

    Wanti L.P.. International Journal of Electrical and Computer Engineering, 10 (5), 2020. doi: 10.11591/ijece.v10i5.pp4992-5000
  5. Profile matching for students specialization in industrial engineering major

    Awaliyah M.M.. IOP Conference Series: Materials Science and Engineering, 127 (3), 2020. doi: 10.1088/1757-899X/830/3/032063
  6. The gap values in the profile matching method by fuzzy logic

    Sitepu S.. Journal of Physics: Conference Series, 127 (1), 2018. doi: 10.1088/1742-6596/978/1/012061