The MOORA method for selecting software App: price-quality ratio approach
DOI:
10.33395/sinkron.v5i2.10789Abstract
Seeing the rapid progress of software app. in today's destructive era, the need for software app. is very reliable for industrial progress in the era of the 4.0 generation. Especially in object-oriented software app. The main objective of this research is to measure the technical capabilities of object-based software app. and to find out the process of selecting the best number of app.software in terms of the appropriate price. Many techniques can be developed in object-based software app. such as class implementation, Inheritance, Encapsulation, Polymorphic, Constructor, Accessor, Mutator, Visibility, Overwrite and Overload. This technique is an advantage of object-based software app. Taking advantage of these advantages causes difficulty in selecting and evaluating software. Indeed, it is very difficult to evaluate software products, because they are qualitative. In order for the assessment to be objective, it requires good method collaboration, thus an objective method is needed in the assessment of the selection of a number of program app. The test was carried out with the Multi Objective Optimization by Ratio Analysis (MOORA) method collaborated with the Price-Quality Ration approach. The results obtained are the selection of object-based software app. that can be done optimally and provide efficiency in the benefits and costs incurred.
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Aytaç Adalı, E., & Tuş Işık, A. (2017). The multi-objective decision making methods based on MULTIMOORA and MOOSRA for the laptop selection problem. Journal of Industrial Engineering International, 13(2), 229–237. https://doi.org/10.1007/s40092-016-0175-5
Ayubi, A., Muqtadiroh, F. A., & Nisafani, A. S. (2015). Quality Measurement Of Object Oriented Code Using Chidamber And Kemerer Metric In Tthe Perspective Of Maintainabality, Efficiency, Understadability And Replaceability (Case Studies Software Accounting XYZ).
Brauers, W. K., & Zavadskas, E. K. (2009). Robustness of the multi-objective moora method with a test for the facilities sector. Technological and Economic Development of Economy, 15(2), 352–375. https://doi.org/10.3846/1392-8619.2009.15.352-375
Gadakh, V. (2011). Application of MOORA method for parametric optimization of milling process. International Journal of Applied Engineering Research, 1(4), 743–758.
Hidayatulloh, I., & Naf’an, M. Z. (2018). Integrasi Sentiment Analysis SentiWordNet pada Metode MOORA untuk Rekomendasi Pemilihan Smartphone. Jurnal Nasional Teknik Elektro Dan Teknologi Informasi (JNTETI), 7(1), 21–26. https://doi.org/10.22146/jnteti.v7i1.396
Ijadi Maghsoodi, A., Abouhamzeh, G., Khalilzadeh, M., & Zavadskas, E. K. (2018). Ranking and selecting the best performance appraisal method using the MULTIMOORA approach integrated Shannon’s entropy. Frontiers of Business Research in China, 12(1), 1–21. https://doi.org/10.1186/s11782-017-0022-6
Kamila, I., & Helma, S. S. (2019). Implementation of MOORA Method for Determining Prospective Smart Indonesia Program Funds Recipients. International Journal of Engineering and Advanced Technology, 9(2), 1920–1925. https://doi.org/10.35940/ijeat.b2860.129219
Kundakci, N. (2016). Combined Multi-Criteria Decision Making Approach Based On Macbeth And Multi-MOORA Methods. Alphanumeric Journal, 4(1). https://doi.org/10.17093/aj.2016.4.1.5000178402
Mill, R. B. (2011). Validity of the Ahp / Anp : Comparing Apples and. International Journal of the Analitical Hierachy Process, 3(1), 2–27.
Pérez-Domínguez, L., Sánchez Mojica, K. Y., Ovalles Pabón, L. C., & Cordero Diáz, M. C. (2018). Application of the MOORA method for the evaluation of the industrial maintenance system. Journal of Physics: Conference Series, 1126(1), 1–6. https://doi.org/10.1088/1742-6596/1126/1/012018
Prasetyo, H., & Sutopo, W. (2018). Industri 4.0: Telaah Klasifikasi Aspek Dan Arah Perkembangan Riset. J@ti Undip : Jurnal Teknik Industri, 13(1), 17. https://doi.org/10.14710/jati.13.1.17-26
Saaty, T. L. (2010). The Eigenvector In Lay Language 2 . What we learn when we have measurement. 2(2), 163–169.
Sarkar, A., Panja, S. C., Das, D., & Sarkar, B. (2015). Developing an efficient decision support system for non-traditional machine selection: an application of MOORA and MOOSRA. Production and Manufacturing Research, 3(1), 324–342. https://doi.org/10.1080/21693277.2014.895688
Siahaan, A. P. U., Rahim, R., & Mesran, M. (2017). Student Admission Assesment using Multi-Objective Optimization on the Basis of Ratio Analysis. International Seminar IRSTC 2017, Irstc. https://doi.org/10.31219/osf.io/cwfpu
Stanujkic, D., Magdalinovic, N., Stojanovic, S., & Jovanovic, R. (2012). Extension of ratio system part of MOORA method for solving decision-making problems with interval data. Informatica, 23(1), 141–154. https://doi.org/10.15388/informatica.2012.353
Tian, Z. peng, Wang, J., Wang, J. qiang, & Zhang, H. yu. (2017). An improved MULTIMOORA approach for multi-criteria decision-making based on interdependent inputs of simplified neutrosophic linguistic information. Neural Computing and Applications, 28, 585–597. https://doi.org/10.1007/s00521-016-2378-5
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Copyright (c) 2021 Akmaludin Akmaludin, Erene Gernaria Sihombing , Linda Sari Dewi, Rinawati Rinawati , Ester Arisawati
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