Modelling effectivenes of IS learning methodology with AHP method

  • Authors

    • Elisabet Yunaeti Anggraeni Faculty of Information Technology, Applied Science Private University
    • Pardimin . Faculty of Information Technology, Applied Science Private University
    • Ihsan Dacholfany Faculty of Information Technology, Applied Science Private University
    • Akla .
    • Miftachul Huda
    • Kamarul Shukri Mat Teh
    • Aminudin Hehsan
    • Juhazren Junaidi
    • Farahwahida Mohd Yusof
    • Hafiza Abas
    • Mohd Fauzi Abu Husin
    • Dina Apriani
    • Aliza Abdul Latif
    • Andino Maseleno
    https://doi.org/10.14419/ijet.v7i4.18482

    Received date: August 28, 2018

    Accepted date: September 8, 2018

    Published date: November 13, 2018

  • Decision Support System, MPSI, Analytic Hierarchy Process (AHP).

  • Abstract

    Information system research methodology, Bahasa: Metodologi Penelitian Sistem Informasi (MPSI), is a mandatory course that must be attended by information system and management student at STMIK Pringsewu. MPSI learning must be conducted effectively to achieve the expected goal. The problem is how to determine MPSI learning effectiveness at STMIK Pringsewu. This problem must be done by Analytical Hierarchy Process method. AHP method can help solving complex problem by structuring a hierarchy criteria, party who has interest, result and by attract some consideration to develop weight and priority. The results of this research was a decision support system which adapts related party in determining learning effectiveness of MPSI at STMIK Pringewu. From this research result obtained a conclusion that is MPSI learning at STMIK Pringsewu is very effective with score of 2.138.

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    82. 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.
    83. 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.
    84. 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.
    85. 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.
    86. 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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    Yunaeti Anggraeni, E., ., P., Dacholfany, I., ., A., Huda, M., Shukri Mat Teh, K., Hehsan, A., Junaidi, J., Mohd Yusof, F., Abas, H., Fauzi Abu Husin, M., Apriani, D., Abdul Latif, A., & Maseleno, A. (2018). Modelling effectivenes of IS learning methodology with AHP method. International Journal of Engineering and Technology, 7(4), 4708-4714. https://doi.org/10.14419/ijet.v7i4.18482