Novelty Ranking Approach with Z-Score and Fuzzy Multi- Attribute Decision Making Combination

 
 
 
  • Abstract
  • Keywords
  • References
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  • Abstract


    This study aims to recommend a new approach in the ranking system by analyzing the combination of the Z-Score method and the Fuzzy Multi-Attribute Decision Making (FMADM) method. This fusion is based on the merging of the advantages of Z-Score and FMADM as a superiority method in statistical rank data processing with weighting data distribution. The lack of Z-Score in processing multi-attributes weighted data can be improved by the FMADM method. In this study, the integration of the Analytical Hierarchy Process (AHP) and Weighted Product (WP) methods was used as the FMADM method with the Z-Score statistical technique. The results of the analysis in the case study show that the integration of the Z-Score and AHP-Weighted Product (Z-WeP) methods can provide maximum results with similarities to the Z-Score results by 86%. Analysis of criterion values on alternatives also shows that Z-WeP can work better than some other of FMADM approaches.

     

     

     


  • Keywords


    Z-Score, FMADM, Z-WeP, Ranking

  • References


      [1] J. I. Marden, Analyzing and modeling rank data. Chapman and Hall/CRC, 2014.

      [2] A. R. Baswedan, “Gawat darurat pendidikan di Indonesia,” in The Emergency of Indonesian Education]. A paper delivered at the meeting between Ministry and Head of Education Offices Indonesia-wide in Jakarta, on December, 2014, vol. 1.

      [3] L. Bornmann, L. Leydesdorff, and R. Mutz, “The use of percentiles and percentile rank classes in the analysis of bibliometric data: Opportunities and limits,” J. Informetr., vol. 7, no. 1, pp. 158–165, 2013.

      [4] S. Arikunto and C. S. A. Jabar, “Evaluasi program pendidikan,” 2011.

      [5] V. Hegde and M. S. Pallavi, “Descriptive analytical approach to analyze the student performance by comparative study using Z score factor through R language,” in Computational Intelligence and Computing Research (ICCIC), 2015 IEEE International Conference on, 2015, pp. 1–4.

      [6] B. Basri and M. Assidiq, “Klasifikasi Data pada Sistem Penjurusan dengan Preferensi Standar Simple Additive Weighting (PS-SAW),” J. Nas. Tek. Elektro dan Teknol. Inf., vol. 6, no. 4, pp. 404–409, 2017.

      [7] G.-H. Tzeng and J.-J. Huang, Multiple attribute decision making: methods and applications. Chapman and Hall/CRC, 2011.

      [8] Basri, “METODE WEIGHTD PRODUCT (WP) DALAM SISTEM PENDUKUNG KEPUTUSAN PENERIMAAN BEASISWA PRESTASI,” J. INSYPRO (Information Syst. Process., vol. 2, no. 1, pp. 1–6, 2017.

      [9] R. P. Singh and H. P. Nachtnebel, “Analytical hierarchy process (AHP) application for reinforcement of hydropower strategy in Nepal,” Renew. Sustain. Energy Rev., vol. 55, pp. 43–58, 2016.

      [10] T. L. Saaty, “The modern science of multicriteria decision making and its practical applications: The AHP/ANP approach,” Oper. Res., vol. 61, no. 5, pp. 1101–1118, 2013.

      [11] A. P. Yazdanpanah, K. Faez, and R. Amirfattahi, “Multimodal biometric system using face, ear and gait biometrics,” in Information Sciences Signal Processing and their Applications (ISSPA), 2010 10th International Conference on, 2010, pp. 251–254.

      [12] H. A. Prasetyo, “SISTEM PENDUKUNG KEPUTUSAN MENENTUKAN PRODUSEN TERBAIK DALAM PEMBUATAN KERUDUNG PADA CV. HAZNA INDONESIA MENGGUNAKAN AHP (Analytical Hierarchy Process) DAN WP (Weighted Product),” SEMNASTEKNOMEDIA ONLINE, vol. 5, no. 1, pp. 3–5, 2017.

      [13] S. Ebrahimnejad, S. M. Mousavi, and H. Seyrafianpour, “Risk identification and assessment for build–operate–transfer projects: A fuzzy multi attribute decision making model,” Expert Syst. Appl., vol. 37, no. 1, pp. 575–586, 2010.

      [14] R. P. Kusumawardani and M. Agintiara, “Application of fuzzy AHP-TOPSIS method for decision making in human resource manager selection process,” Procedia Comput. Sci., vol. 72, pp. 638–646, 2015.

      [15] M. Amini, S. I. Chang, and B. Malmir, “A fuzzy MADM method for uncertain attributes using ranking distribution,” in Proceedings of the industrial and systems engineering research conference, 2016.

      [16] M.-T. Lu, G.-H. Tzeng, H. Cheng, and C.-C. Hsu, “Exploring mobile banking services for user behavior in intention adoption: using new hybrid MADM model,” Serv. Bus., vol. 9, no. 3, pp. 541–565, 2015.

      [17] N. Khalil, S. N. Kamaruzzaman, and M. R. Baharum, “Ranking the indicators of building performance and the users’ risk via Analytical Hierarchy Process (AHP): Case of Malaysia,” Ecol. Indic., vol. 71, pp. 567–576, 2016.

      [18] N. Subramanian and R. Ramanathan, “A review of applications of Analytic Hierarchy Process in operations management,” Int. J. Prod. Econ., vol. 138, no. 2, pp. 215–241, 2012.

      [19] S. Liu, Q. Zhao, M. Wen, L. Deng, S. Dong, and C. Wang, “Assessing the impact of hydroelectric project construction on the ecological integrity of the Nuozhadu Nature Reserve, southwest China,” Stoch. Environ. Res. risk Assess., vol. 27, no. 7, pp. 1709–1718, 2013.

      [20] B. Basri, S. Syarli, and F. Febryanti, “Multi-Attribute Analysis With AHP Algorithm to Optimize Student Ranking Recomendation in Educational Process,” in International Conference Research on Education, Social, Science and Technology (ICREST) 2018, 2018.

      [21] B. Basri and S. Syarli, “AHP-STANDAR SCORE: PENDEKATAN BARU DALAM SISTEM PEMERINGKATAN,” J. Keteknikan dan Sains, vol. 1, no. 1, pp. 1–6, 2018.

      [22] B. Basri, “METODE WEIGHTD PRODUCT (WP) DALAM SISTEM PENDUKUNG KEPUTUSAN PENERIMAAN BEASISWA PRESTASI,” J. INSYPRO (Information Syst. Process., vol. 2, no. 1, 2017.


 

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Article ID: 27363
 
DOI: 10.14419/ijet.v7i4.7.27363




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