Heavy Equipment Rental Apps Using Ionic Framework

Authors

  • Neec Chander Tobias PT. Gajah Unggul Internasional

DOI:

https://doi.org/10.70356/josapen.v2i1.21

Keywords:

Android-based application, Ionic Framework, Mobile Application Development, Heavy equipment rental

Abstract

The study delves into the development of an Android-based heavy equipment rental application for PT. Gajah Unggul Internasional. The article underscores the significance of information systems in the heavy equipment rental business, introducing the specific context of PT. Gajah Unggul Internasional, a company providing various construction and industrial equipment. Recognizing the need for an efficient system to expedite processes such as borrowing, repaying, and restocking heavy equipment, the author proposes an Android application utilizing the Ionic Framework, a powerful open-source SDK. The methodology section outlines a meticulous five-stage research design, encompassing data collection, inception, elaboration, construction, and transition. The results and discussion section provides a detailed analysis of the application, including use case diagrams, activity diagrams, sequence diagrams, class diagrams, and the system interface. Black box testing validates the functionality and effectiveness of the proposed system, demonstrating successful outcomes in various aspects such as login, registration, equipment data viewing, and rental history tracking. In conclusion, the study showcases the successful integration of the Ionic Framework to enhance the efficiency and effectiveness of heavy equipment rental processes for PT. Gajah Unggul Internasional. The developed application offers a user-friendly interface catering to diverse stakeholders, emphasizing its practicality and functionality. Overall, the article contributes valuable insights into leveraging technology to streamline and optimize business operations in the heavy equipment rental industry.

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References

W. Zhu, T. Zhang, Z. Ying, Z. Liao, X. Luan, and L. Meng, “Real-time high-speed train rescheduling based on a Human-Computer Interaction framework,” High-speed Railw., vol. 1, no. 2, pp. 130–140, 2023, doi: 10.1016/j.hspr.2023.06.001.

I. Baumann et al., “First experiences with a surgery supporting computer system in regard to education, efficiency and complications,” Surg. Open Sci., vol. 16, no. November, pp. 228–234, 2023, doi: 10.1016/j.sopen.2023.11.005.

C. Ramonell, R. Chacón, and H. Posada, “Knowledge graph-based data integration system for digital twins of built assets,” Autom. Constr., vol. 156, no. May, 2023, doi: 10.1016/j.autcon.2023.105109.

T. Zhu, X. Yang, S. Haugen, and Y. Liu, “A multi-dimensional approach for analyzing risk-related decision problems to enhance decision making and prevent accidents,” J. Loss Prev. Process Ind., vol. 87, no. November 2023, p. 105235, 2024, doi: 10.1016/j.jlp.2023.105235.

A. González-Pérez, M. Matey-Sanz, C. Granell, L. Díaz-Sanahuja, J. Bretón-López, and S. Casteleyn, “AwarNS: A framework for developing context-aware reactive mobile applications for health and mental health,” J. Biomed. Inform., vol. 141, no. October 2022, p. 104359, 2023, doi: 10.1016/j.jbi.2023.104359.

L. Corral, I. Fronza, and T. Mikkonen, “User Interface Matters: Analysing the Complexity of Mobile Applications from a Visual Perspective,” Procedia Comput. Sci., vol. 191, pp. 9–16, 2021, doi: 10.1016/j.procs.2021.07.039.

A. I. Khan, A. Al-Badi, and M. Al-Kindi, “Progressive web application assessment using AHP,” Procedia Comput. Sci., vol. 155, pp. 289–294, 2019, doi: 10.1016/j.procs.2019.08.041.

L. S. Jr, F. Ruiz, and L. Fagiano, “A Set Membership approach to black-box optimization for time-varying problems,” IFAC-PapersOnLine, vol. 56, no. 2, pp. 3966–3971, 2023, doi: 10.1016/j.ifacol.2023.10.1343.

A. Alsaedi, A. Alhuzali, and O. Bamasag, “Effective and scalable black-box fuzzing approach for modern web applications,” J. King Saud Univ. - Comput. Inf. Sci., vol. 34, no. 10, pp. 10068–10078, 2022, doi: 10.1016/j.jksuci.2022.10.006.

Z. Daw and R. Cleaveland, “Comparing model checkers for timed UML activity diagrams,” Sci. Comput. Program., vol. 111, no. P2, pp. 277–299, 2015, doi: 10.1016/j.scico.2015.05.008.

F. Chen, L. Zhang, X. Lian, and N. Niu, “Automatically recognizing the semantic elements from UML class diagram images,” J. Syst. Softw., vol. 193, p. 111431, 2022, doi: 10.1016/j.jss.2022.111431.

D. Felicio, J. Simao, and N. Datia, “Rapitest: Continuous black-box testing of restful web apis,” Procedia Comput. Sci., vol. 219, no. 2022, pp. 537–545, 2023, doi: 10.1016/j.procs.2023.01.322.

H. Bostani and V. Moonsamy, “EvadeDroid: A Practical Evasion Attack on Machine Learning for Black-box Android Malware Detection,” Comput. Secur., p. 103676, 2021, doi: 10.1016/j.cose.2023.103676.

F. Pagano, A. Romdhana, D. Caputo, L. Verderame, and A. Merlo, “SEBASTiAn: A static and extensible black-box application security testing tool for iOS and Android applications,” SoftwareX, vol. 23, p. 101448, 2023, doi: 10.1016/j.softx.2023.101448.

C. Cronley et al., “Designing and evaluating a smartphone app to increase underserved communities’ data representation in transportation policy and planning,” Transp. Res. Interdiscip. Perspect., vol. 18, no. January, p. 100763, 2023, doi: 10.1016/j.trip.2023.100763.

Published

2024-01-28

How to Cite

Tobias, N. C. (2024). Heavy Equipment Rental Apps Using Ionic Framework. Journal of Computer Science Application and Engineering (JOSAPEN), 2(1), 1–5. https://doi.org/10.70356/josapen.v2i1.21