Pengembangan Sistem Transformasi dan Konversi Data Berbasis Web Menggunakan Arsitektur RESTful API


Authors

  • Deborah Kurniawati Universitas Teknologi Digital Indonesia, Yogyakarta, Indonesia
  • Adi Kusjani Universitas Teknologi Digital Indonesia, Yogyakarta, Indonesia
  • Robby Cokro Buwono Universitas Teknologi Digital Indonesia, Yogyakarta, Indonesia
  • Muhammad Aldo Ridhoni Universitas Teknologi Digital Indonesia, Yogyakarta, Indonesia

DOI:

https://doi.org/10.47065/bulletincsr.v5i6.818

Keywords:

Data Transformation; Frontend; Go; Mithril.js; RESTful Architecture

Abstract

Heterogeneous data management often faces challenges such as format inconsistency, high latency, and lack of automation, leading to inefficiencies and errors in data transformation. This research aims to develop a web-based system to automate data transformation and conversion across formats using a Representational State Transfer (RESTful) Application Programming Interface (API) architecture, with a Mithril.js frontend and Go backend. An experimental and system development approach was employed, comprising three stages: client-server architecture design, implementation, and testing. The system provides 11 primary API endpoints, such as /api/tasks and /api/transformations, to manage tasks and data transformations. The Single Page Application frontend offers intuitive navigation with menus for task management, data sources, and activity logs. Functional testing on Comma-Separated Values, JavaScript Object Notation, and SQLite formats yielded accurate transformations, including text prepending, data type conversion, and lowercase normalization. Performance evaluation using Google Lighthouse recorded a median score of 85, indicating high performance. The system enhances efficiency and accuracy compared to manual methods, supporting cross-platform interoperability. However, limitations include support for only simple tabular formats and lack of security features. This research offers a lightweight solution for data transformation, with potential applications in organizational data integration and business analytics.

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References

S. Karlsson, R. Jongeling, A. ?auševi?, and D. Sundmark, Exploring behaviours of RESTful APIs in an industrial setting, vol. 32, no. 3. Springer US, 2024. doi: 10.1007/s11219-024-09686-0.

A. Aldoseri, K. N. Al-Khalifa, and A. M. Hamouda, “Methodological Approach to Assessing the Current State of Organizations for AI-Based Digital Transformation,” Applied System Innovation, vol. 7, no. 1, 2024, doi: 10.3390/asi7010014.

G. A. Mutiara, Periyadi, M. R. Alfarisi, M. A. Rifqi Zain, M. G. Rijali, and F. N. Rochim, “Design and implementation of a REST API-based client-server architecture for multi-sensor IoT monitoring,” International Journal of Advanced Technology and Engineering Exploration, vol. 12, no. 124, pp. 426–449, 2025, doi: 10.19101/IJATEE.2024.111101934.

A. Ehsan, M. A. M. E. Abuhaliqa, C. Catal, and D. Mishra, “RESTful API Testing Methodologies: Rationale, Challenges, and Solution Directions,” Applied Sciences (Switzerland), vol. 12, no. 9, 2022, doi: 10.3390/app12094369.

R. Simbulan and J. Aryanto, “Implementasi REST API Web Service pada Aplikasi Sumber Daya Manusia,” Jurnal Indonesia: Manajemen Informatika dan Komunikasi, vol. 5, no. 1, pp. 552–560, 2024, doi: 10.35870/jimik.v5i1.511.

R. Putra Fhonna, Y. Afrillia, V. Ilhadi, A. H. Arif, and R. A. Selian, “Performance Analysis of API Protocol Models as Recommendations for Developers in Application Development,” JINAV: Journal of Information and Visualization, vol. 5, no. 2, pp. 2746–1440, 2024, [Online]. Available: https://doi.org/10.35877/454RI.jinav3041

K. Habib, M. H. M. Saad, A. Hussain, M. R. Sarker, and K. A. Alagbari, “An Aggregated Data Integration Approach to the Web and Cloud Platforms through a Modular REST-Based OPC UA Middleware,” Sensors, vol. 22, no. 5, pp. 1–39, 2022, doi: 10.3390/s22051952.

F. Tanveer, F. Iradat, W. Iqbal, and A. Ahmad, “Towards Secure APIs: A Survey on RESTful API Vulnerability Detection,” Computers, Materials and Continua, vol. 84, no. 3, pp. 4223–4257, 2025, doi: 10.32604/cmc.2025.067536.

J. Bogner, S. Kotstein, and T. Pfaff, Do RESTful API design rules have an impact on the understandability of Web APIs?, vol. 28, no. 6. 2023. doi: 10.1007/s10664-023-10367-y.

A. A. Alahmad, A. H. Mohd Aman, F. Qamar, and W. Mardini, “Efficient Caching Strategies in NDN-Enabled IoT Networks: Strategies, Constraints, and Future Directions,” Sensors, vol. 25, no. 16, pp. 1–59, 2025, doi: 10.3390/s25165203.

R. Miñón, J. Diaz-De-arcaya, A. I. Torre-Bastida, and P. Hartlieb, “Pangea: An MLOps Tool for Automatically Generating Infrastructure and Deploying Analytic Pipelines in Edge, Fog and Cloud Layers,” Sensors, vol. 22, no. 12, pp. 1–29, 2022, doi: 10.3390/s22124425.

B. Nascimento, R. Santos, J. Henriques, M. V. Bernardo, and F. Caldeira, “Availability, Scalability, and Security in the Migration from Container-Based to Cloud-Native Applications,” Computers, vol. 13, no. 8, pp. 1–13, 2024, doi: 10.3390/computers13080192.

M. Coblenz, W. Guo, K. Voozhian, and J. S. Foster, “A Qualitative Study of REST API Design and Specification Practices,” Proceedings of IEEE Symposium on Visual Languages and Human-Centric Computing, VL/HCC, pp. 148–156, 2023, doi: 10.1109/VL-HCC57772.2023.00025.

A. Lercher, J. Glock, C. Macho, and M. Pinzger, “Microservice API Evolution in Practice: A Study on Strategies and Challenges,” Journal of Systems and Software, vol. 215, no. May, p. 112110, 2024, doi: 10.1016/j.jss.2024.112110.

M. Muntean, C. Brânda?, and T. Cîrstea, “Framework for a symmetric integration approach,” Symmetry (Basel), vol. 11, no. 2, 2019, doi: 10.3390/sym11020224.

G. P. Tiwary, E. Stroulia, and A. Srivastava, “Compression of XML and JSON API Responses,” IEEE Access, vol. 9, pp. 57426–57439, 2021, doi: 10.1109/ACCESS.2021.3073041.

A. Gama Garcia, J. M. Alcaraz Calero, H. Mora Mora, and Q. Wang, “ServiceNet: resource-efficient architecture for topology discovery in large-scale multi-tenant clouds,” Cluster Comput, vol. 27, no. 7, pp. 8965–8982, 2024, doi: 10.1007/s10586-024-04344-3.

S.-P. Ma, M.-J. Hsu, H.-J. Chen, and C.-J. Lin, “RESTful API Analysis, Recommendation, and Client Code Retrieval,” Electronics (Switzerland), vol. 12, no. 5, pp. 1–17, 2023, doi: 10.3390/electronics12051252.

P. Kannisto, D. Hästbacka, T. Gutiérrez, O. Suominen, M. Vilkko, and P. Craamer, “Plant-wide interoperability and decoupled, data-driven process control with message bus communication,” J Ind Inf Integr, vol. 26, no. August 2021, p. 100253, 2022, doi: 10.1016/j.jii.2021.100253.

A. da Silva and A. J. Marques Cardoso, “Designing the future of coopetition: An IIoT approach for empowering SME networks,” International Journal of Advanced Manufacturing Technology, vol. 135, no. 1–2, pp. 747–762, 2024, doi: 10.1007/s00170-024-14528-1.

I. Nikolaou and L. Anthopoulos, “REST API Access Control - an OPTIONS Based Approach,” WWW Companion 2025 - Companion Proceedings of the ACM Web Conference 2025, vol. 2025, no. January, pp. 1719–1723, 2025, doi: 10.1145/3701716.3718327.

N. Chen, X. Lin, H. Jian, and Y. An, “Automated Building Information Modeling Compliance Check and Ontology,” Buildings, vol. 14, no. 7, pp. 1–28, 2024, doi: 10.3390/buildings14071983.

R. N. Muzaki and A. Salam, “Reducing Under-Fetching and Over-Fetching in Rest Api With Graphql for Web-Based Software Development,” Jurnal Teknik Informatika (Jutif), vol. 5, no. 2, pp. 447–453, 2024, doi: 10.52436/1.jutif.2024.5.2.1725.

R. Jin, R. Cordingly, D. Zhao, and W. Lloyd, “GraphQL vs. REST: A Performance and Cost Investigation for Serverless Applications,” WoSC10 ’24: Proceedings of the 10th International Workshop on Serverless Computing, no. January, pp. 37–42, 2024, doi: 10.1145/3702634.3702956.

R. Ala-Laurinaho, J. Mattila, J. Autiosalo, J. Hietala, H. Laaki, and K. Tammi, “Comparison of REST and GraphQL Interfaces for OPC UA,” Computers, vol. 11, no. 5, pp. 1–17, 2022, doi: 10.3390/computers11050065.

Irfan Ahmed Khan, Harsh Mishra, and Khushboo Choubey, “A Comparative Analysis of REST and GraphQL APIs: Performance, Efficiency, and Developer Experience,” International Journal of Advanced Multidisciplinary Scientific Research, vol. 8, no. 4, pp. 29–39, 2025, doi: ijamsr.2025.8.4.8212.

J. Yandi and M. Muchlis, “Penggunaan GraphQL Sebagai Alternatif Rest API: Studi Kasus Pada Pengembangan Website,” Jurnal Nasional Ilmu Komputer, vol. 6, no. 1, pp. 1–5, 2025, doi: 10.47747/jurnalnik.v6i1.2384.

Moch. Z. Ain, Rizka Ardiansyah, Septiano Anggun Pratama, Muhammad Akbar, and Nouval Trezandy Lapatta, “Comparative Performance Analysis of GRPC and Rest API Under Various Traffic Conditions and Data Sizes Using a Quantitative Approach,” Journal of Applied Informatics and Computing, vol. 9, no. 2, pp. 450–457, 2025, doi: 10.30871/jaic.v9i2.9276.

L. Theodorakopoulos, A. Karras, A. Theodoropoulou, and G. Kampiotis, “Benchmarking Big Data Systems: Performance and Decision-Making Implications in Emerging Technologies,” Technologies (Basel), vol. 12, no. 11, pp. 1–30, 2024, doi: 10.3390/technologies12110217.


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Published: 2025-10-31

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How to Cite

Kurniawati, D., Kusjani, A., Robby Cokro Buwono, & Muhammad Aldo Ridhoni. (2025). Pengembangan Sistem Transformasi dan Konversi Data Berbasis Web Menggunakan Arsitektur RESTful API. Bulletin of Computer Science Research, 5(6), 1395-1402. https://doi.org/10.47065/bulletincsr.v5i6.818

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