Ni Komang Yanti Suartini

Work place: Universitas Pendidikan Ganesha/Computer Science Department, Singaraja, 81116, Indonesia



Research Interests: Computer systems and computational processes, Systems Architecture, Decision Support System


Ni Komang Yanti Suartini is a master's degree student in the Computer Science Department from Universitas Pendidikan Ganesha. Her research interest area is Decision Support Systems.

Author Articles
Comparison Analysis of AHP-SAW, AHP-WP, AHP-TOPSIS Methods in Private Tutor Selection

By Ni Komang Yanti Suartini Dewa Gede Hendra Divayana Luh Joni Erawati Dewi

DOI:, Pub. Date: 8 Feb. 2023

Private tutoring was a non-formal education, it was used as an alternative by parents to help support and maximize the learning process that students get at school. Sometimes parents have difficulty in adjusting the desired and needed criteria with available alternatives or teachers. To overcome these obstacles, this research used the MADM approach in providing alternative recommendations, based on the criteria used as the basis for decision making. MADM consists of SAW, WP, TOPSIS, and AHP. The advantages of the SAW, WP, and TOPSIS methods in managing cost and benefit data were used in the ranking process. While the weaknesses of the three methods in the weighting process can be overcome by the AHP method, which was able to provide more objective weighting results. Therefore, this research aimed to analyze the comparison of the combination of AHP-SAW, AHP-WP, and AHP-TOPSIS methods in the selection of private tutors. The combination of these methods was compared based on accuracy, ranking, and preference to get the best combination of MADM methods in determining the selection of private tutors. The criteria used in this research were education, experience, cost, duration, rating, and distance. The comparison of the three combinations of methods showed the AHP-SAW method has an accuracy rate of 88.14%, AHP-WP of 68.64%, and AHP-TOPSIS of 66.95%. The average ranking showed the AHP-SAW method gave results of 91%, AHP-WP of 88%, and AHP-TOPSIS of 89%. In addition, the average preference showed the AHP-SAW method gave a value of 0.771, AHP-WP of 0.073, and AHP-TOPSIS of 0.564. Thus, it showed the AHP-SAW gave better results in the case of private tutor selection than the AHP-WP and AHP-TOPSIS.

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