Designing and quality testing of “Digichip” virtual simulation software of Android platform for mobile-virtual learning supporting vocational mechatronics engineering

Titih Rejyasmito Hadi; Eko Marpanaji

doi:10.21831/jpv.v9i2.23570

Designing and quality testing of “Digichip” virtual simulation software of Android platform for mobile-virtual learning supporting vocational mechatronics engineering

Titih Rejyasmito Hadi, Universitas Negeri Yogyakarta, Indonesia
Eko Marpanaji, Universitas Negeri Yogyakarta, Indonesia

10.21831/jpv.v9i2.23570

Abstract

Technology enhancement in any life aspects is undeniably crucial to face the globalization era. A strategic approach to touch any life aspect is gained through education. Supporting this educational long-term goal, this study aims to: (1) produce learning media in the form of a virtual-learning simulation software, which is capable of operation on mobile devices to facilitate mobile, portable, effective, economical, and operationally-safe learning; (2) test the developed software quality in terms of the functional aspects of suitability, maintainability, portability, and usability (ISO/IEC 25010). The subjects of this Research and Development (R&D) study were class XI students of Mechatronics Engineering at SMTI Yogyakarta. The process of designing and testing software uses the V-model type Software Development Life Cycle (SDLC). Unit testing was done through the white-box technique with the base-path test, flowgraph, and independent path. The testing for integration, system, and acceptance used Black-box techniques. The study shows that: (1) V-models were used to design the "DigiChip" virtual simulation software to support virtual learning and mobile learning through the software development stage; (2) The software quality testing based on ISO/IEC 25010 shows that in the functional aspects suitability, all features function properly (very decent), its maintainability is of MI 84 (easy maintenance), it gains 100% portability, or can be operated on all Android OS kernels (very feasible), and its usability is 86.18% (very feasible) with Cronbach's Alpha 0.841 (good). Ninety percent of media experts and 100% of material experts consider that the developed software is very feasible.

Keywords

simulation; virtual learning; mobile learning; mechatronics

Full Text:

FULLTEXT PDF

References

Arikunto, S. (2013). Prosedur penelitian: Suatu pendekatan praktik. Jakarta: Rineka Cipta.

Chemuturi, M. (2011). Mastering software quality assurance: Best practices, tools and techniques for software developers. Plantation, FL: J. Ross.

George, D., & Mallery, P. (2016). IBM SPSS statistics 23 step by step: A simple guide and reference (14th ed.). Oxon: Routledge.

Heitlager, I., Kuipers, T., & Visser, J. (2007). A practical model for measuring maintainability. In 6th International Conference on the Quality of Information and Communications Technology. Lisbon, Portugal: IEEE Explore. https://doi.org/10.1109/QUATIC.2007.8

Koyya, P., Lee, Y., & Yang, J. (2013). Feedback for programming assignments using software-metrics and reference code. International Scholarly Research Notices (ISRN) Software Engineering, 2013, 1–8. https://doi.org/10.1155/2013/805963

Laplante, P. A. (2007). What every engineer should know about software engineering (1st ed.). Boca Raton, FL: CRC Press.

Lund, A. M. (2001). Measuring usability with the USE Questionnaire. Retrieved May 12, 2016, from https://www.researchgate.net/publication/230786746/

McCabe, T. J. (1976). A complexity measure. IEEE Transactions on Software Engineering, SE-2(4), 308–320. https://doi.org/10.1109/TSE.1976.233837

Microsoft Developer. (2007). Maintainability index range and meaning – Code analysis team blog. Retrieved May 9, 2017, from https://blogs.msdn.microsoft.com/codeanalysis/2007/11/20/maintainability-index-range-and-meaning/

Najadat, H., Alsmadi, I., & Shboul, Y. (2012). Predicting software projects cost estimation based on mining historical data. International Scholarly Research Notices (ISRN) Software Engineering, 2012, 1–8. https://doi.org/10.5402/2012/823437

Pachler, N., Bachmair, B., & Cook, J. (2010). Mobile learning: Structures, agency, practices. (G. R. Kress, Ed.). London: Springer.

Pressman, R. S. (2010). Software engineering: A practitioner’s approach (7th ed.). New York, NY: McGraw-Hill.

Riduwan. (2013). Skala pengukuran variabel: Variabel penelitian. Bandung: Alfabeta.

Tamrin, A. G., Slamet, S., & Soenarto, S. (2018). The link and match of the demand and supply for productive vocational school teachers with regard to spectrum of vocational skills in the perspective of education decentralization. Jurnal Pendidikan Vokasi, 8(1), 40–52. https://doi.org/10.21831/jpv.v8i1.15135

Tullis, T., & Albert, B. (2013). Measuring the user experience: Collecting, analyzing, and presenting usability metrics (2nd ed.). Waltham, MA: Elsevier.

Watkins, J., & Mills, S. (2011). Testing IT: An off-the-shelf software testing process (2nd ed.). Cambridge: Cambridge University Press. https://doi.org/10.1017/CBO9780511997310

Williams, L. (2006). Testing overview and black-box testing techniques. Retrieved May 12, 2016, from http://agile.csc.ncsu.edu/SEMaterials/BlackBox.pdf.

DOI: https://doi.org/10.21831/jpv.v9i2.23570