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

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

Автор: Ni Komang Yanti Suartini, Dewa Gede Hendra Divayana, Luh Joni Erawati Dewi

Журнал: International Journal of Modern Education and Computer Science @ijmecs

Статья в выпуске: 1 vol.15, 2023 года.

Бесплатный доступ

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.

Еще

AHP, SAW, TOPSIS, WP, Private Tutor

Короткий адрес: https://sciup.org/15019102

IDR: 15019102   |   DOI: 10.5815/ijmecs.2023.01.03

Список литературы Comparison Analysis of AHP-SAW, AHP-WP, AHP-TOPSIS Methods in Private Tutor Selection

  • N. K. Y. Suartini, I. M. A. Wirawan, and D. G. H. Divayana, “DSS for ‘E-Private’ Using a Combination of AHP and SAW Methods,” IJCCS (Indonesian Journal of Computing and Cybernetics Systems), Vol. 13, No. 3, pp. 251–262, 2019.
  • M. R. Ahsan, W. Setiyaningsih, and M. Susilowati, “Selecting Multiple Intelligences on Children with Weighted Product, Analytical Hierarchy Process, Simple Additive Weighting, and TOPSIS,” Journal of Physics: Conference Series, Vol. 1402, No.7, pp. 1–6, 2019.
  • S. K. Mangle, Sustainable Procurement in Supply Chain Operations. New York: CRC Press, 2019.
  • M. Marbun, “Analysis of Application of the SAW, WP, and TOPSIS Methods in Decision Support System Determining Scholarship Recipients at Univers,” ICoCSIM, Vol. 6, No. 3, pp. 1–13, 2021.
  • H. Pratiwi, Decision Support System. Yogyakarta: Deepublish, 2018.
  • E. Ardiyanto, “Comparison of AHP-TOPSIS and AHP-WP Methods for a Decision Support System for Feasibility of Applying for PMW Fund Loans at UNSEC,” UNNES, Vol. 8, No. 3, pp. 96–107, 2017.
  • S. Borra, Intelligent Decision Support Systems. Berlin: Walter de Gruyter GmbH & Co KG, 2019.
  • M. R. Ridho, Hairani, K. A. Latif, and R. Hammad, “Combination of AHP and TOPSIS Methods for Recommendation for Vocational Scholarship Recipients Based on Decision Support Systems,” Tekno Journal, Vol. 15, No. 1, pp. 26–36, 2021.
  • A. Andoyo, Decision Support System (Concept, Implementation & Development). Indramayu: Adab, 2021.
  • J. Mantas, Decision Support Systems and Education. Amsterdam: IOS Press, 2018.
  • M. H. Al Hazza, A. Abdelwahed, M. Y. Ali, and A. B. A. Sidek, “An Integrated Approach for Supplier Evaluation and Selection using the Delphi Method and Analytic Hierarchy Process (AHP): A New Framework,” International Journal of Technology, Vol. 13, No. 1, pp. 16–25, 2022.
  • N. Sael, T. Hamim, and F. Benabbou, “Implementation of the Analytic Hierarchy Process for Student Profile Analysis,” International Journal of Emerging Technologies in Learning (iJET), Vol. 14, No. 15, pp. 78–93, 2019.
  • P. Z. Razi, N. I. Ramli, M. I. Ali, and P. J. Ramadhansyah, “Selection of Best Consultant by Using Analytical Hierarchy Process (AHP),” IOP Conference Series: Materials Science and Engineering, Vol. 712, pp. 1–9, 2020.
  • A. Aditya, and F. E. Purwiantono, “The Application of Fuzzy-Analytical Hierarchy Process Method for Majors Selection at Public Universities,” JITE (Journal of Informatics and Telecommunication Engineering, Vol. 3, No. 2, pp. 240–251, 2020.
  • V. H. Valentino, H. S. Setiawan, A. Saputra, Y. Haryanto, and A. S. Putra, “Decision Support System for Thesis Session Pass Recommendation Using AHP (Analytic Hierarchy Process) Method,” International Journal of Educational Research & Social Sciences, Vol. 2, No. 1, pp. 215–221, 2021.
  • E. Terzi, “Analytic Hierarchy Process (AHP) to Solve Complex Decision Problems,” Southeast Europe Journal of Soft Computing, Vol. 8, No. 1, pp. 5–12, 2019.
  • H. Hanim, and J. Rahmadoni, “Determination of Lecturer Reception Using Analytical Hierarchy Process (AHP),” Journal of Applied Engineering and Technological Science (JAETS), Vol. 1, No. 2, pp. 136–141, 2020.
  • S. A. Totalia, T. Martono, K. B. Sangka, W. Swastike, S. Wahyudi, and Suhadi, “The Development of Analytical Hierarchy Process (AHP) Model for Optimization of School Operational Assistance (BOS),” Budapest International Research and Critics in Linguistics and Education (BirLE) Journal, Vol. 4, No. 4, pp. 1351–1363, 2021.
  • F. J. Abdullayeva, and S. S. Ojagverdiyeva, “Multicriteria Decision Making using Analytic Hierarchy Process for Child Protection from Malicious Content on the Internet,” International Journal of Computer Network and Information Security (IJCNIS), Vol. 13, No.3, pp.52–61, 2021.
  • F. Lotfi, K. Fatehi, and N. Badie, “An Analysis of Key Factors to Mobile Health Adoption using Fuzzy AHP,” International Journal of Information Technology and Computer Science (IJITCS), Vol. 12, No. 2, pp.1–17, 2020.
  • Y. V. Singh, B. Kumar, and S. Chand, “A Hybrid Approach for Requirements Prioritization Using LFPP and ANN,” International Journal of Intelligent Systems and Applications (IJISA), Vol. 11, No.1, pp.13–23, 2019.
  • A. Kunjir, J. Shah, N. Singh, and T. Wadiwala, “Big Data Analytics and Visualization for Hospital Recommendation using HCAHPS Standardized Patient Survey,” International Journal of Information Technology and Computer Science (IJITCS), Vol. 11, No. 3, pp.1–9, 2019.
  • M. Annisa, D. Supriyadi, and A. Wijayanto, “Comparison of SAW and TOPSIS Methods for the Best Employee Selection Decision Support System,” Proceedings on Conference on Electrical Engineering, Telematics, Industrial Technology, and Creative Media, Vol. 436, No. 5, pp. 141–145, 2018.
  • R. Meri, “Simple Additive Weighting (SAW) Method on the Selection of New Teacher Candidates at Integrated Islamic Elementary School,” IJISTECH (International Journal of Information System and Technology), Vol. 4, No. 1, pp. 428–435, 2020.
  • N. Aminudin, M. Huda, A. Kilani, W.H.W. Embong, A.M. Mohamed, B. Basiron, S.S. Ihwani, S.S.M. Noor, K.A. Jasmi, J. Safar, N.L. Ivanova, A. Maseleno, A. Triono, and Nungsiati, “Higher Education Selection using Simple Additive Weighting,” International Journal of Engineering & Technology, Vol. 7, No.2, pp. 211–217, 2018.
  • B. Daniawan, “Evaluation of Lecturer Teaching Performance Using AHP and SAW Methods,” Bit-Tech, Vol. 1, No.2, pp. 30–39, 2018.
  • B. Saputra, “Decision Support System for Determining the Level of Employee Salary Increase at PT. Srikandi Inti Lestari Medan by Using the Simple Additive Weighting (SAW) Method,” International Journal of Basic and Applied Science, Vol. 9, No. 3, pp. 64–70, 2020.
  • A. Ibrahim, and R. A. Surya, “The Implementation of Simple Additive Weighting (SAW) Method in Decision Support System for the Best School Selection in Jambi,” Journal of Physics: Conference Series, Vol. 1338, pp. 1–7, 2019.
  • H. L. H. S. Warnars, A. Fahrudin, and W. H. Utomo, “Student Performance Prediction Using Simple Additive Weighting Method,” IAES International Journal of Artificial Intelligence (IJ-AI), Vol. 9, No. 4, pp. 630–637, 2020.
  • D. Meidelfi, Yulherniwati, F. Sukma, D. Chandra, and A. H. S. Jones, “The Implementation of SAW and BORDA Method to Determine the Eligibility of Students’ Final Project Topic,” International Journal on Informatics Visualization, Vol. 5, No. 2, pp. 144–149, 2021.
  • I. P. W. Ariawan, W. Simatupang, A. M. Ishak, A. A. G. Agung, Suratmin, A. Adiarta, and D. G. H. Divayana, “Development of ANEKA Evaluation Model Based on TOPSIS in Searching the Dominant Aspects of Computer Learning Quality Determinants,” Journal of Theoretical and Applied Information Technology, Vol. 96, No. 19, pp. 6580–6596, 2018.
  • V. D. Iswari, F. Y. Arini, and M. A. Muslim, “Decision Support System for the Selection of Outstanding Students Using the AHP-TOPSIS Combination Method,” Lontar Komputer: Jurnal Ilmiah Teknologi Informasi, Vol. 10, No. 1, pp. 40–48, 2019.
  • D. G. H. Divayana, and P. W. A. Suyasa, “Simulation of TOPSIS calculation in Discrepancy-Tat Twam Asi evaluation model,” Register: Jurnal Ilmiah Teknologi Sistem Informasi, Vol. 7, No. 2, pp. 136–148, 2021.
  • E. W. Emasopangidoan, “Implementation of Topsis Method for Supervisor Selection Decision Making System at District 10 Restaurant and Bar,” Data Mining, Image Processing and Artificial Intelligence, Vol. 9, No. 2, pp. 467–477, 2021.
  • D. B. T. Wijaya, T. Wahyono, and A. N. S. Hapsari, “TOPSIS Method Implementation for Employee Performance Information System,” International Journal of Information Technology and Business, Vol. 2, No. 1, pp. 21–26, 2019.
  • M. Kumar, R. Tonk, R. Yadav, and V. Sharma, “MCDM Technique-Topsis With Case Study,” International Journal of Advanced Science and Technology, Vol. 29, No. 10s, pp. 5715–5720, 2020.
  • Sumanto, K. Indriani, L. S. Marita, and A. Christian, “Supplier Selection Very Small Aperture Terminal using AHP-TOPSIS Framework,” Journal of Intelligent Computing and Health Informatics, Vol. 1, No. 2, pp. 39–45, 2020.
  • Jasri, D. Siregar, and R. Rahim, “Decision Support System Best Employee Assessments with Technique for Order of Preference by Similarity to Ideal Solution,” International Journal of Recent Trends in Engineering & Research, Vol. 3, No. 3, pp. 6–17, 2017.
  • E. Baran, “An Innovative Fuzzy TOPSIS Method to Determine the Location of A New Hospital,” International Journal of Engineering Science and Application, Vol. 2, No. 4, pp. 133–136, 2018.
  • P. Bagga, R. Hans, and A. Joshi, “QoS based Web Service Selection and Multi-Criteria Decision Making Methods,” International Journal of Interactive Multimedia and Artificial Intelligence, Vol. 5, pp. 113–121, 2019.
  • S. S. Goswami, and D. K. Behera, “An Analysis for Selecting Best Smartphone Model by AHP-TOPSIS Decision-Making Methodology,” International Journal of Service Science, Management, Engineering, and Technology, Vol. 12, No. 3, pp. 116–137, 2021.
  • D. G. H. Divayana, A. Adiarta, and P. W. A. Suyasa, “Design of Tat Twam Asi-Discrepancy Evaluation Model Based on TOPSIS in Determining the Improvement Priority Aspect,” Emerging Science Journal, Vol. 5, No. 3, pp. 392–404, 2021.
  • V. Listyaningsih, and E. Utami, “Decision Support System Performance-Based Evaluation of Village Government using AHP and TOPSIS Methods: Secang Sub-district of Magelang Regency as a Case Study,” International Journal of Intelligent Systems and Applications (IJISA), Vol. 10, No. 4, pp.18–28, 2018.
  • P. G. S. C. Nugraha and G. S. Mahendra, “Comparison of AHP-SAW and AHP-WP Methods on DSS to Determine the Best E-Commerce in Indonesia,” JUSTIN, Vol. 8, No. 4, pp. 346–356, 2020.
  • E. Ardiyanto, “Comparison of AHP-TOPSIS and AHP-WP Methods for a Decision Support System for Feasibility of Applying for PMW Fund Loans at UNSEC,” UNNES, Vol. 8, No. 3, pp. 96–107, 2017.
  • D. Supiyan, “Comparison of SAW, WP, and TOPSIS Methods in Determining El-Raushan BMT Financing,” UNPAM Journal, Vol. 4, No. 2, pp. 88–94, 2019.
  • W. Hadikurniawati, E. Winarno, T. D. Cahyono, and D. Abdullah, “Comparison of AHP-TOPSIS Hybrid Methods, WP and SAW for Multi-Attribute Decision-Making to Select the Best Electrical Expert,” Journal of Physics: Conference Series Paper, Vol. 5, No. 2, pp. 1–12, 2018.
  • I. P. W. Ariawan, M. K. W. Giri, and D. G. H. Divayana, “The CIPP-SAW Evaluation Model Design in Measurement the Effectiveness of E-Learning at Health Universities in Bali,” Journal of Theoretical and Applied Information Technology, Vol. 97, No. 21, pp. 2922–2934, 2019.
  • D. G. H. Divayana, I. P. W. Ariawan, A. Adiarta, D. P. Parmiti, I. W. E. Mahendra, and N. N. Parmithi, “Development of ANEKA-Based Countenance Model Integrated with Tri Hita Karana-SAW in Evaluating Student’s Character and Quality of Computer Learning in Bali,” Journal of Engineering and Applied Sciences, Vol. 13, No. 15, pp. 6303–6315, 2018.
  • I. N. Jampel, I. W. Lasmawan, I. M. Ardana, I. P. W. Ariawan, I. M. Sugiarta, and D. G. H. Divayana, “Evaluation of Learning Programs and Computer Certification at Course Institute in Bali Using CSE-UCLA Based on SAW Simulation Model,” Journal of Theoretical and Applied Information Technology, Vol. 95, No. 24, pp. 6934–6949, 2017.
  • N. Aminudin, E. Sundari, K. Shankar, P. Deepalakshmi, Fauzi, R. Irviani, and A. Maseleno, “Weighted Product and Its Application to Measure Employee Performance,” International Journal of Engineering & Technology, Vol. 7, No. 2.26, pp. 102–108, 2018.
  • D. G. H. Divayana, “Development of ANEKA-Weighted Product Evaluation Model Based on Tri Kaya Parisudha in Computer Learning on Vocational School,” Cogent Engineering, Vol. 5, pp. 1–33, 2018.
  • M. Ahsan, and N. Indawati, “Implementation Weighted Product Method to Determine Multiple Intelligence Child,” Journal of Physics: Conference Series, Vol. 1375, pp. 1–7, 2019.
  • A. P. Sembiring, Tulus, R. W. Sembiring, and H. Maulana. “Rule Model with Fuzzy Simple Additive Weighting Approach and Weighted Product on Determination of Position in High Education Institution,” International Journal of Latest Trends in Engineering and Technology, Vol. 10, No. 1, pp. 54–62, 2018.
  • B. Sahoo, R. N. Behera, and P. K. Pattnaik, “A Comparative Analysis of Multi-Criteria Decision Making Techniques for Ranking of Attributes for e-Governance in India,” International Journal of Advanced Computer Science and Applications, Vol. 13, No. 3, pp. 65–70, 2022.
Еще
Статья научная
QR-код для установки приложения SciUp Наведите камеру и скачайте бесплатное приложение SciUp