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Vol. 7, No. 3, August 2022

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Fuzzy Type-2 Trapezoid Methods for Decision Making Salt Farmer Mapping

https://doi.org/10.22219/kinetik.v7i3.1454
Yeni Kustiyahningsih
Urunojoyo University
Eza Rahmanita
Universitas Trunojoyo Madura
Purbandini Purbandini
Universitas Airlangga
Jaka Purnama
Universitas 17 Agustus 1945 Surabaya

Corresponding Author(s) : Yeni Kustiyahningsih

ykustiyahningsih@trunojoyo.ac.id

Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control, Vol. 7, No. 3, August 2022

Abstract

The need for domestic salt every year has increased, both for consumption and industrial salt. Some of the fisheries service programs include providing assistance to people's businesses, providing geomembrane, and online marketing training. A large number of salt farmers and official work programs have caused the implementation of the program to be less than optimal, resulting in low salt production. This study uses a type-2 fuzzy method by integrating two methods, namely type-2 Fuzzy Analytical Hierarchy Process AHP (FAHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Fuzzy type-2 has higher accuracy than fuzzy type-1 and is more efficient and more flexible in determining the linguistic scale for criteria. The Fuzzy Analytical Hierarchy Process AHP (FAHP) interval is used to determine the weight of the salt farmer mapping criteria. Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS), used to determine. The findings of this study are that the indicators that most influence the mapping of salt farmers are land area, marketing, and market. The results of the mapping of salt farmers are the classification of salt farmer class groups and recommendations for improvement for each salt farmer. Hybrid type-2 Fuzzy Analytical Hierarchy Process AHP (FAHP) method and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), can be used for mapping salt farmers based on the consistency ratio value below 10 percent, 37 percent enter high class, 28 percent enter the middle class and 35 percent enter low class

Keywords

Fuzzy Type-2 TOPSIS AHP Salt Farmer Interval Mapping
Kustiyahningsih, Y., Rahmanita, E., Purbandini, P., & Purnama, J. (2022). Fuzzy Type-2 Trapezoid Methods for Decision Making Salt Farmer Mapping . Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control, 7(3), 231-242. https://doi.org/10.22219/kinetik.v7i3.1454
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References
  1. U. Hanik and M. Mutmainah, “Analisis Kinerja Dan Kebutuhan Petani Garam Di Kabupaten Pamekasan Sebagai Dasar Pengembangan Desain Model Social Learning,” J. Sos. Ekon. Kelaut. dan Perikan., vol. 15, no. 2, p. 237, 2020. http://dx.doi.org/10.15578/jsekp.v15i2.7842
  2. Y. Kustiyahningsih, E. Rahmanita, Purbandini, and N. Kholifah, “Salt Farmer measurement performance system facing Covid-19 pandemic used interval type-2 FAHP Method,” J. Phys. Conf. Ser., vol. 2193, no. 1, 2022. https://doi.org/10.1088/1742-6596/2193/1/012012
  3. R. Dai et al., “The impact of COVID-19 on small and medium-sized enterprises (SMEs): Evidence from two-wave phone surveys in China,” China Econ. Rev., vol. 67, no. February, p. 101607, 2021. https://doi.org/10.1016/j.chieco.2021.101607
  4. S. O. Caballero-Morales, “Innovation as recovery strategy for SMEs in emerging economies during the COVID-19 pandemic,” Res. Int. Bus. Financ., vol. 57, no. May 2020, p. 101396, 2021. https://doi.org/10.1016/j.ribaf.2021.101396
  5. M. Holis and I. P. Endahuluan, “Strategi Peningkatan Optimalisasi Aktivitas Petani Garam Pamekasan dengan Aalytical Hierarchy,” Semin. Nas. Hum. Dan Apl. Teknol. Informasi), vol. 5, no. (!), pp. 129–238, 2019.
  6. M. N. Mokhtarian, “A note on ‘extension of fuzzy TOPSIS method based on interval-valued fuzzy sets,’” Appl. Soft Comput. J., vol. 26, pp. 513–514, 2015. https://doi.org/10.1016/j.asoc.2014.10.013
  7. E. Celik and E. Akyuz, “An interval type-2 fuzzy AHP and TOPSIS methods for decision-making problems in maritime transportation engineering: The case of ship loader,” Ocean Eng., vol. 155, no. July 2016, pp. 371–381, 2018. https://doi.org/10.1016/j.oceaneng.2018.01.039
  8. Y. Kustiyahningsih, “Integration interval type-2 fahp-ftopsis group decision- making problems for salt farmer recommendation,” pp. 1–25, 2021.
  9. Q. Wu, L. Zhou, Y. Chen, and H. Chen, “An integrated approach to green supplier selection based on the interval type-2 fuzzy best-worst and extended VIKOR methods,” Inf. Sci. (Ny)., vol. 502, pp. 394–417, 2019. https://doi.org/10.1016/j.ins.2019.06.049
  10. M. Amiri, M. Hashemi-Tabatabaei, M. Ghahremanloo, M. Keshavarz-Ghorabaee, E. K. Zavadskas, and J. Antucheviciene, “A new fuzzy approach based on BWM and fuzzy preference programming for hospital performance evaluation: A case study,” Appl. Soft Comput. J., vol. 92, p. 106279, 2020. https://doi.org/10.1016/j.asoc.2020.106279
  11. C. Kahraman, B. Öztayşi, I. Uçal Sari, and E. Turanoǧlu, “Fuzzy analytic hierarchy process with interval type-2 fuzzy sets,” Knowledge-Based Syst., vol. 59, pp. 48–57, 2014. https://doi.org/10.1016/j.knosys.2014.02.001
  12. K. Kiracı and E. Akan, “Aircraft selection by applying AHP and TOPSIS in interval type-2 fuzzy sets,” J. Air Transp. Manag., vol. 89, no. September 2020, 2020. https://doi.org/10.1016/j.jairtraman.2020.101924
  13. R. Aggarwal, S. Singh, and A. C. Ahp, “AHP and Extent Fuzzy AHP Approach for Prioritization of Performance Measurement Attributes,” Eng. Technol., vol. 7, no. 1, pp. 160–165, 2013. https://doi.org/10.5281/zenodo.1082718
  14. E. Rahmanita, V. T. Widyaningrum, Y. Kustiyahningsih, and J. Purnama, “Model Multi Criteria Decision Making with Fuzzy ANP Method for Performance Measurement Small Medium Enterprise (SME),” IOP Conf. Ser. Mater. Sci. Eng., vol. 336, no. 1, 2018. https://doi.org/10.1088/1757-899X/336/1/012023
  15. B. Ashtiani, F. Haghighirad, A. Makui, and G. ali Montazer, “Extension of fuzzy TOPSIS method based on interval-valued fuzzy sets,” Appl. Soft Comput. J., vol. 9, no. 2, pp. 457–461, 2009. https://doi.org/10.1016/j.asoc.2008.05.005
  16. K. Karuppiah, B. Sankaranarayanan, S. M. Ali, P. Chowdhury, and S. K. Paul, “An integrated approach to modeling the barriers in implementing green manufacturing practices in SMEs,” J. Clean. Prod., vol. 265, p. 121737, 2020. https://doi.org/10.1016/j.jclepro.2020.121737
  17. A. P. Wibawa, J. A. Fauzi, S. Isbiyantoro, R. Irsyada, Dhaniyar, and L. Hernández, “VIKOR multi-criteria decision making with AHP reliable weighting for article acceptance recommendation,” Int. J. Adv. Intell. Informatics, vol. 5, no. 2, pp. 160–168, 2019. https://doi.org/10.26555/ijain.v5i2.172
  18. S. Avikal, R. Jain, and P. K. Mishra, “A Kano model, AHP and M-TOPSIS method-based technique for disassembly line balancing under fuzzy environment,” Appl. Soft Comput. J., vol. 25, pp. 519–529, 2014. https://doi.org/10.1016/j.asoc.2014.08.002
  19. M. Mathew, R. K. Chakrabortty, and M. J. Ryan, “A novel approach integrating AHP and TOPSIS under spherical fuzzy sets for advanced manufacturing system selection,” Eng. Appl. Artif. Intell., vol. 96, no. June, p. 103988, 2020. https://doi.org/10.1016/j.engappai.2020.103988
  20. F. Zhou, X. Wang, M. K. Lim, Y. He, and L. Li, “Sustainable recycling partner selection using fuzzy DEMATEL-AEW-FVIKOR: A case study in small-and-medium enterprises (SMEs),” J. Clean. Prod., vol. 196, pp. 489–504, 2018. https://doi.org/10.1016/j.jclepro.2018.05.247
  21. S. Senturk, Y. Binici, and N. Erginel, “The theoretical structure of Fuzzy Analytic Network Process (FANP) with Interval Type-2 Fuzzy Sets,” IFAC-PapersOnLine, vol. 49, no. 12, pp. 1318–1322, 2016. https://doi.org/10.1016/j.ifacol.2016.07.706
  22. I. Ihsannudin, S. Pinujib, S. Subejo, and B. Sumada Bangko, “Strategi Pemberdayaan Ekonomi Petani Garam Melalui Pendayagunaan Aset Tanah Pegaraman,” Econ. Dev. Anal. J., vol. 5, no. 4, pp. 395–409, 2018. https://doi.org/10.15294/edaj.v5i4.22177
  23. Y. Kustiyahningsih and I. Q. H. Aini, “Integration of FAHP and COPRAS Method for New Student Admission Decision Making,” Proceeding - 2020 3rd Int. Conf. Vocat. Educ. Electr. Eng. Strength. Framew. Soc. 5.0 through Innov. Educ. Electr. Eng. Informatics Eng. ICVEE 2020, 2020. https://doi.org/10.1109/ICVEE50212.2020.9243260
  24. B. Meni̇z, “An advanced TOPSIS method with new fuzzy metric based on interval type-2 fuzzy sets,” Expert Syst. Appl., vol. 186, no. August, 2021. https://doi.org/10.1016/j.eswa.2021.115770
  25. M. A. Elleuch, M. Anane, J. Euchi, and A. Frikha, “Hybrid fuzzy multi-criteria decision making to solve the irrigation water allocation problem in the Tunisian case,” Agric. Syst., vol. 176, no. January, p. 102644, 2019. https://doi.org/10.1016/j.agsy.2019.102644
  26. S. O. Ogundoyin and I. A. Kamil, “A Fuzzy-AHP based prioritization of trust criteria in fog computing services,” Appl. Soft Comput. J., vol. 97, p. 106789, 2020. https://doi.org/10.1016/j.asoc.2020.106789
  27. D. Caroline, G. Luiz, and D. O. Serra, “Interval type-2 fuzzy computational model for real time Kalman filtering and forecasting of the dynamic spreading behavior of novel Coronavirus 2019,” ISA Trans., vol. 124, pp. 57–68, 2022. https://doi.org/10.1016/j.isatra.2022.03.031
  28. A. Bhadran, D. Girishbai, N. P. Jesiya, G. Gopinath, R. G. Krishnan, and V. K. Vijesh, “Geosystems and Geoenvironment A GIS based Fuzzy-AHP for delineating groundwater potential zones in tropical river basin , southern part of India,” Geosystems and Geoenvironment, vol. 1, no. 4, p. 100093, 2022. https://doi.org/10.1016/j.geogeo.2022.100093
  29. K. Velmurugan, S. Saravanasankar, P. Venkumar, R. Sudhakarapandian, and G. Di Bona, “Hybrid fuzzy AHP-TOPSIS framework on human error factor analysis : Implications to developing optimal maintenance management system in the SMEs,” Sustain. Futur., vol. 4, no. June, p. 100087, 2022. https://doi.org/10.1016/j.sftr.2022.100087
  30. M. Rajak and K. Shaw, “Evaluation and selection of mobile health (mHealth) applications using AHP and fuzzy TOPSIS,” Technol. Soc., vol. 59, no. July, p. 101186, 2019. https://doi.org/10.1016/j.techsoc.2019.101186
  31. T. Wu, X. Liu, J. Qin, and F. Herrera, “An interval type-2 fuzzy Kano-prospect-TOPSIS based QFD model: Application to Chinese e-commerce service design,” Appl. Soft Comput., vol. 111, p. 107665, 2021. https://doi.org/10.1016/j.asoc.2021.107665
  32. Zadeh L. A., “The concept of a linguistic variable and its application to approximate reasoning-III,” Inf. Sci. (Ny)., vol. 9, no. 1, pp. 43–80, 1975,. https://doi.org/10.1016/0020-0255(75)90017-1
  33. Z. Gong and S. Hai, “The interval-valued trapezoidal approximation of interval-valued fuzzy numbers and its application in fuzzy risk analysis,” J. Appl. Math., vol. 2014, 2014. https://doi.org/10.1155/2014/254853
  34. Y. Kustiyahningsih, Fatmawati, and H. Suprajitno, “Adaptive Interval Trapezoid Fuzzy Number for Recommendation Systems E-Learning,” J. Phys. Conf. Ser., vol. 1569, no. 4, 2020. https://doi.org/10.1088/1742-6596/1569/4/042073
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