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INDONESIA
Jurnal Sains dan Teknologi Informasi
Published by Forum Kerjasama Pendidikan TInggi
ISSN : -     EISSN : 2809610X     DOI : https://doi.org/10.47065/jussi.v3i2.4883
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering
Bidang kajian dari Jurnal Sains dan Teknologi Informasi, yaitu: Teknik Informatika, Manajemen Informatika, Sistem Informasi, Teknik Komputer, Kecerdasan Buatan, dan Computer Science.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 72 Documents
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Penerapan Metode Analytic Network Process Pada Pendukung Keputusan Pengangkatan Guru Tetap Nurlela, Siti; Fania, Liza; Ananda, Aditya; Juanda, Muhammad; Sembiring, David JM
Jurnal Sains dan Teknologi Informasi Vol 4 No 4 (2025): September 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jussi.v4i4.8469

Abstract

The process of appointing honorary teachers as permanent teachers still faces various challenges, particularly concerning objectivity and transparency in decision-making. Many educational institutions continue to rely on manual evaluation methods to assess teacher eligibility, which are often subjective and lack measurable analytical foundations. Consequently, the appointment process does not always reflect the actual competence and performance of honorary teachers. Based on these issues, this study aims to develop a Decision Support System (DSS) based on the Analytical Network Process (ANP) method to assist schools and educational authorities in objectively, systematically, and accurately determining which honorary teachers are eligible for permanent appointment. The ANP method was chosen because it can map the interdependence among criteria and sub-criteria in the selection process. Data were collected through observation, interviews, and literature review, then processed using a pairwise comparison matrix to generate the priority weights of each criterion and alternative. The findings indicate that the ANP-based decision support system effectively improves speed, efficiency, and fairness in the teacher appointment process. The results show that the alternative Dwi Rokita achieved the highest score of 2.531439, making her the most eligible candidate for permanent appointment. Therefore, the application of the ANP method proves to be effective in supporting objective and accountable decision-making in the appointment of honorary teachers, while simultaneously contributing to the improvement of human resource quality in the education sector.
Pendukung Keputusan Dengan Perbandingan Metode WASPAS dan Metode MAUT pada Pemilihan Karyawan Baru Ilham, Safarul
Jurnal Sains dan Teknologi Informasi Vol 4 No 4 (2025): September 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jussi.v4i4.8470

Abstract

In searching for employee candidates who meet the desired criteria, a solution is needed to select prospective employees. The solution that can be done is to create a decision support system to simplify the process of selecting employee files that have been received. Decision Support Systems (DSS) that can help companies to select prospective employees who register using the comparison of the Weight Aggregated Sum Product Assessment (WASPAS) method is a combination of the WP and SAW methods, where the WP method is a method that uses multiplication in connecting the value of each attribute that must previously be raised to the power of the attribute's weighted value, while the SAW method is generally known as a weighted sum that focuses on calculating the sum of the weighted values ​​of alternative criteria, with the Multi-Utility Attribute Theory (MAUT) method being a quantitative method that is used as a basis for decision making through systematic procedures that identify and analyze several variables. In its application, the decision support system, comparing the WASPAS and MAUT methods in selecting prospective employees according to the given criteria, yielded alternative A5, but with different scores. The WASPAS method scored alternative A5 at 0.890, while the MAUT method scored 0.875.

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