PENGGUNAAN METODE SIMPLE ADDITIVE WEIGHTING (SAW) PADA SISTEM PENUNJANG KEPUTUSAN DALAM PENENTUAN JURUSAN SMK

Authors

  • Susliansyah Susliansyah Manajemen Informatika AMIK BSI Bekasi
  • Rizqyana Pangestu Sistem Informasi STMIK Nusa Mandiri Jakarta

DOI:

https://doi.org/10.33480/pilar.v14i2.32

Keywords:

SMK, Simple Additive Weighting, Determination of Departments, SAW

Abstract

Most students graduating from junior high school want to continue their desires, especially to vocational schools, this can be proven by the number of junior high school students who take the entrance examination to the vocational high school. What is unfortunate is the lack of maturity they choose the department in the targeted vocational school. This kind of situation has an impact on the cost of education that has already been spent, both on the parents of students and the government who subsidize the school to be not useful because the student does not have adequate skills for the chosen department, other negative consequences are students who drop out. Vocational schools prioritize the formation of students who are ready to enter the workforce and develop professional attitudes consisting of various majors. The number of majors at the vocational level makes it difficult for prospective students to determine the right majors according to their abilities, therefore a decision support system is needed that can determine the majors according to the values, interests and abilities of prospective students. This research applies fuzzy logic with Simple Additive Weighting (SAW) method to facilitate the determination of vocational high school majors.

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References

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Published

2018-09-15

How to Cite

Susliansyah, S., & Pangestu, R. (2018). PENGGUNAAN METODE SIMPLE ADDITIVE WEIGHTING (SAW) PADA SISTEM PENUNJANG KEPUTUSAN DALAM PENENTUAN JURUSAN SMK. Jurnal Pilar Nusa Mandiri, 14(2), 151–156. https://doi.org/10.33480/pilar.v14i2.32

Issue

Vol. 14 No. 2 (2018): Pilar Nusa Mandiri : Journal of Computing and Information System Periode September 2018

Section

Articles

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