DSS for Keyboard Mechanical Selection Using AHP and Profile Matching Method
Amelia Dita Handayani(1*), Retantyo Wardoyo(2)
(1) Bachelor Program of Computer Science, FMIPA UGM, Yogyakarta
(2) Department of Computer Science and Electronics, FMIPA UGM, Yogyakarta
(*) Corresponding Author
Abstract
Mechanical keyboards are designed with various shapes, variations, and specifications that are different from other types of keyboards. The mechanical keyboard itself has an aesthetic function that allows users to customize it. There are various specifications on mechanical keyboards, causing various considerations, which can make it difficult for users to choose a mechanical keyboard that fits the desired criteria. Supported by observations in the Indonesia Mechanical Keyboard Group (IMKG), some users are still limited in their knowledge of mechanical keyboard products available in Indonesia, also, currently there is no solution that can handle this problem.
Based on these problems, in this research, an DSS is built that can help overcome these problems, by providing recommendations for a mechanical keyboard according to the wishes of the user. DSS is implemented in web form using the AHP method for the weighting process and Profile Matching for the scoring process. The criteria used are determined by conducting a survey regarding the specifications that are the priority considerations in choosing a mechanical keyboard.
At the end of the study, the DSS that was successfully built was able to provide mechanical keyboard priority recommendations according to user preferences and get an average evaluation result of 36.17 out of a total maximum value of 40.
Keywords
Full Text:
PDFReferences
[1] University, Keyboard 2020, Intro to Mechanical Keyboards, https://keyboard.university/100-courses/intro-to-mechanical-keyboards, accessed date 13 Mei 2021.
[2] Saaty, R. W. (1987) ‘The analytic hierarchy process-what it is and how it is used’, Mathematical Modelling. doi: 10.1016/0270-0255(87)90473-8.
[3] Kusrini, 2007, Konsep dan Aplikasi Sistem Pendukung Keputusan, Yogyakarta, C.V Andi Offset,.
[4] Saaty, T. and Vargas, L. (2012) Models, methods, concepts & applications of the analytic hierarchy process, … -Driven Demand and Operations Management Models. doi: 10.1007/978-1-4614-3597-6.
[5] Hartomo. (2006) Implementasi Metode Interpolasi Linier untuk Pembesaran, TEKNOIN, 11, 3, 219-232.
[6] Azwar, S. (2012) Penyusunan Skala Psikologi (ed.2), Pustaka Pelajar.
[7] International Organization for Standardization, ISO/IEC TR 9126. (2001) Part 1 : Software engineering – Product quality.
[8] Turban, E., Aronson, J.E., Liang, P.T. (2005) Decision Support System and Intelligent System, 7th Edition, Pearson Education Inc., Uper Saddle River, New Jersey,.
[9] Little, J. D. C. (1970) ‘Models and Managers: The Concept of a Decision Calculus’, Management Science. doi: 10.1287/mnsc.16.8.b466.
[10] Bonczek, R. H., Holsapple, C. W. and Whinston, A. B. (1980) ‘THE EVOLVING ROLES OF MODELS IN DECISION SUPPORT SYSTEMS’, Decision Sciences. doi: 10.1111/j.1540-5915.1980.tb01143DOI: https://doi.org/10.22146/ijccs.67813
Article Metrics
Abstract views : 2566 | views : 2130Refbacks
- There are currently no refbacks.
Copyright (c) 2021 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
View My Stats1