FMADM for determining superior commodity at agroindustry area

 
 
 
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  • Abstract


    Indonesia has many excellent commodities that are spread throughout Indonesia, especially in Lampung province. Lampung Province has excellent commodities, among others: coffee, rubber, oil palm, cocoa and coconut. To determine the superior commodity in Lampung province, a decision support model is needed to determine the superior commodities in the agroindustry. This study aimed to create a decision support model that can facilitate in determining the suitable and feasible priority of superior in agroindustry. The commodity is to be developed. The research was carried out by designing application that was developed by using computer programming language and applying the principle of system development by applying the best alternative decision-making method from certain criteria, namely Fuzzy Multiple Attribute Decision Making (FMADM). Fuzzy MADM is a method used to find optimal alternatives from a number of alternatives with certain criteria. This method was chosen because this method determines the weight for each attribute, followed by an alternative rating that will determine the superior commodity for agroindustry in Lampung Province based on the calculated weight using fuzzy formula to get more accurate results about the superior commodity in Lampung province.

     

     

     

     

     

     

     


  • Keywords


    Agroindustry; Decision Support System; Fuzzy Multiple Attribute Decision Making; Lampung Province.

  • References


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      [88] Fauzi, Huda, M., Teh, K.S.M., Haron, Z., Ripin, M.N., Hehsan, A., Abas, H., Rafiq, M., Irawan, J., Abadi, S., Maseleno, A., The Design of Fuzzy Expert System Implementation for Analyzing Transmissible Disease of Human, International Journal of Pharmaceutical Research, Vol. 10, Issue 4, 2018.

      [89] Elhoseny, M., Shankar, K., Lakshmanaprabu, S.K., Maseleno, A., Arunkumar, N., Hybrid Optimization with Cryptography Encryption for Medical Image Security in Internet of Things, Neural Computing and Applications, Springer, October 2018, pp. 1-15.

      [90] Lydia, E. L., Kumar, P.K., Shankar, K., Lakshmanaprabu, S.K., Vidhyavathi, R.M., Maseleno, A., Charismatic Document Clustering through Novel K-Means Non-negative Matrix Factorization (KNMF) Algorithm using Key Phrase Extraction, International Journal of Parallel Programming, Springer, 2018, pp. 1-19.

      [91] Shankar, K., Lakshmanaprabu, S.K., Gupta, D., Maseleno, A., De Albuquerque, V.H.C., Optimal feature-basedmulti-kernel SVM approach for thyroid disease classification, The Journal of Supercomputing, Springer, Vol. 74, no. 259, 2018, pp. 1-16.

      [92] Amin, M.M., Sutrisman, A., Stiawan, D., Maseleno, A., Design Restful WebService of National Population Database for supporting E-health interoperability service, Journal of Theoretical and Applied Information Technology, vol. 96, issue 15, 2018.

      [93] Surendar, A., Akhmetov, L.G., Ilyashenko, L.K., Maseleno, A., Samavatian, V., Effect of thermal cycle loadings on mechanical properties and thermal conductivity of a porous lead-free solder joint, IEEE Transactions on Components, Packaging, and Manufacturing Technology, 2018, pp. 1769-1776.

      [94] Surendar, A., Samavatian, V., Maseleno, A., Ibatova, A.Z., Samavatian, M., Effect of solder layer thickness of thermo-mechanical reliability of a power electronic system, Journal of Material Science: Materials in Electronics, Springer, September 2018, Volume 29, Issue 17, pp. 15249-15258.

      [95] Samavatian, M., Ilyashenko, L.K., Surendar, A., Maseleno, A., Samavatian, V., Effect of System Design on Fatigue Life of Solder Joints in BGA Packages Under Vibration at Random Frequencies, Journal of Electronic Materials, November 2018, Volume 47, Issue 11, pp. 6781-6790.

      [96] Javanshir, I., Maseleno, A., Tasoujian, S., Oveisi, M., Optimization of suspension system of heavy off-road vehicle for stability enhancement using integrated anti-roll bar and coiling spring mechanism, Journal of Central South University, September 2018, Volume 25, Issue 9, pp 2289–2298.

      [97] Surendar, A., Bozorgian, A., Maseleno, A., Ilyashenko, L.K., Najafi, M., Oxidation of Toxic Gases via Ge-B36N36 and Ge-C72 Nanocages as Potential Calaysts, Inorganic Chemistry Communications, Elsevier, Vol. 96, October 2018, pp. 206-210.

      [98] Namdarian, A., Tabrizi, A.G., Maseleno, A., Mohammadi, A., Mossavifard, S.E., One step synthesis of rGO-Ni3S2 nano-cubes composite for high-performance supercapacitor electrodes, International Journal of Hydrogen Energy, Elsevier, vol. 43, Issue 37, 13 September 2018, pp.17780-17787.

      [99] Zhou, L., Kamyab, H., Surendar, A., Maseleno, A., Ibatova, A.G., Chelliapan, S., Karachi, N., Parsaee, Z., Novel Z-scheme composite Ag2CrO4/NG/polyimides as high performance nano catalyst for photoreduction of CO2: Design, fabrication, characterization and mechanism, Journal of Photochemistry and Photobiology A: Chemistry, Elsevier, Volume 368, 1 January 2019, pp 30-40.

      [100] Motlagh, A.H., Klyuev, S.V., Surendar, A., Ibatova, A.Z., Maseleno, A., Catalytic Gasification of Oil Sludge with Calcined Dolomite, Petroleum Science and Technology, Taylor and Francis, pp. 1-5, 2018.


 

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Article ID: 13380
 
DOI: 10.14419/ijet.v7i4.13380




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