Rizqi Nur Robby
Universitas Binaniaga Indonesia

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Penerapan Metode Simple Additive Weighting (SAW) untukRekomendasi Wali Kelas Ideal Tingkat Sekolah Dasar Rizqi Nur Robby; Adiat Pariddudin; Binanda Wicaksana
Jurnal SAINTEKOM (Sains dan Teknologi Komputasi) Vol 2 No 3 (2026): September 2026
Publisher : Lembaga Penelitian, Pengembangan, dan Pengabdian Kepada Masyarakat (LP3M) – Universitas Binaniaga Indonesia (UNBIN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36350/jskom.v2i3.128

Abstract

In the research conducted at SDN Cibalagung 3 in the previous business process, generally every determination of the ideal homeroom teacher was not effective and not right because it still used the standard method which calculated it only by adding all the criteria and averaging it, and the objectives of this study are: 1) Getting a more effective process in determining the homeroom teacher because of the recommendation of the ideal homeroom teacher, 2) Getting accuracy in determining the homeroom teacher because of the recommendation of the ideal homeroom teacher, 3) Developing a prototype of the ideal homeroom teacher recommendation application, 4) Measuring the level of accuracy and effectiveness of the application of the Simple Additive Weighting (SAW) method for the recommendation of the ideal homeroom teacher. The implementation of this development uses the Prototype method, the steps are: 1) Collecting and analyzing needs, 2) Carrying out rapid design, 3) Building a prototype, 4) Evaluation is carried out by users on the prototype, 5) Changes to the design of the prototype, 6) If the prototype does not match what the user expects, repeat step 5, and 7) If the user is satisfied with the prototype, the development of product engineering can begin. Data collection in this study uses documentation. The results of the development show that: 1) The application created can produce optimal solutions by getting ideal homeroom teacher recommendations, 2) The application is able to help StakeHolders in making decisions, 3) The application is able to print recommendation reports, and 4) the application developed is categorized as "Very Eligible" because a 100% eligibility percentage was obtained based on testing on system experts and material experts. Meanwhile, based on the results of testing on users, the results were 82.2% and included in the "Very Eligible" category, and the correlation/suitability coefficient value that has been obtained with a value of 0.57 is included in the high category referring to the Spearman rank table.