Web Service Integration: Data Exchange among Area Sampling Framework, Paddy Sampling, and CAPI Cropping Systems
Abstract
Statistics Indonesia (BPS) is responsible for providing agriculture data. BPS collects statistics on paddy paddy production by performing a survey that involves sampling paddy plots using the Area Sampling Framework (ASF). The ASF survey is conducted monthly. The ASF System receives information from the Paddy Commodity Cropping Sampling System to prepare the sample frame and withdraw samples. This is done by the Sub-Directorate of Sample Frame Development (PKS Sub-Directorate). The existing system requires human processing of ASF results to modify the paddy observation code. This processing is carried out by the Sub-Directorate of Food Crops and the data is prepared by the Sub-Directorate of Sample Frame Development (PKS) before being uploaded into the Paddy Commodity Cropping Sampling System. The findings of sample retrieval by the Paddy Commodity Cropping Sampling System will be transmitted to the Sub-Directorate of Data Processing Integration (Sub-Directorate of IPD) and thereafter uploaded into the CAPI System for Paddy Cropping. The PKS Sub Directorate has identified many processes in the existing system that are deemed to be less efficient. The current inefficiency of the business process is caused by the manual execution of various tasks in the ASF system, such as sending data via email, modifying the paddy observation code, and sending the modified code results. Additionally, the data preparation process relies on additional applications, and sample documents from the Paddy Crop Sampling System are manually sent to the CAPI Cropping Sampling System. Hence, there is a requirement for enhancing the process flow of paddy harvesting sample. The lack of integration across systems necessitates manual execution of the process. This research proposes enhancing the Paddy Commodity Crop Sampling System by introducing new functionalities for modifying the paddy observation code and data preparation. Additionally, it suggests utilizing web services to integrate the ASF System, Paddy Commodity Crop Sampling System, and CAPI Cropping System
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References
Badan Pusat Statistik, Pedoman Pencacahan Survei Ubinan Komoditas Padi Berbasis Kerangka Sampel Area (KSA). Jakarta: Badan Pusat Statistik, 2020.
S. Indonesia, “Executive Summary 2018: Harvested Area and Rice Production in Indonesia,” Stat. Indones. Badan Pus. Stat., 2018.
G. Hendrarto, “Sampling of Square Segments by Points for Rice Production Estimate and Forecast,” 2010.
Statistics Indonesia (BPS), “Area Sampling Framework (ASF) method for paddy commodity cropping survey,” 2018.
S. Yulianto, L. Sumargana, H. Sadmono, and F. Alhasanah, “Innovation on geolocation and pattern recognition for paddy growth stages reporting in Indonesia,” in IOP Conference Series: Earth and Environmental Science, 2018, vol. 165, no. 1, p. 12001.
E. Al-Masri and Q. H. Mahmoud, “Discovering the best web service,” in Proceedings of the 16th international conference on World Wide Web, 2007, pp. 1257–1258.
C. Pautasso, O. Zimmermann, and F. Leymann, “Restful web services vs." big"’web services: making the right architectural decision,” in Proceedings of the 17th international conference on World Wide Web, 2008, pp. 805–814.
M. Mark, “REST API Design Rulebook: Designing Consistent RESTful Web Service Interfaces.".” O’Reilly Media, Inc, 2011.
R. T. Fielding, Architectural styles and the design of network-based software architectures. University of California, Irvine, 2000.
E. Kemer and R. Samli, “Performance comparison of scalable rest application programming interfaces in different platforms,” Comput. Stand. Interfaces, vol. 66, p. 103355, 2019.
H. Hamad, M. Saad, and R. Abed, “Performance Evaluation of RESTful Web Services for Mobile Devices.,” Int. Arab. J. e Technol., vol. 1, no. 3, pp. 72–78, 2010.
A. Neumann, N. Laranjeiro, and J. Bernardino, “An analysis of public REST web service APIs,” IEEE Trans. Serv. Comput., vol. 14, no. 4, pp. 957–970, 2018.
C. Rodríguez et al., “REST APIs: A large-scale analysis of compliance with principles and best practices,” in Web Engineering: 16th International Conference, ICWE 2016, Lugano, Switzerland, June 6-9, 2016. Proceedings 16, 2016, pp. 21–39.
X. Chen, Z. Ji, Y. Fan, and Y. Zhan, “Restful API architecture based on laravel framework,” in Journal of Physics: Conference Series, 2017, vol. 910, no. 1, p. 12016.
F. Petrillo, P. Merle, N. Moha, and Y.-G. Guéhéneuc, “Are REST APIs for cloud computing well-designed? An exploratory study,” in Service-Oriented Computing: 14th International Conference, ICSOC 2016, Banff, AB, Canada, October 10-13, 2016, Proceedings 14, 2016, pp. 157–170.
S. Ahmed and Q. Mahmood, “An authentication based scheme for applications using JSON web token,” in 2019 22nd international multitopic conference (INMIC), 2019, pp. 1–6.
P. Siriwardena, “Advanced API security: securing APIs with OAuth 2.0,” OpenID Connect. JWS, JWE, Apress, 2014.
A. Alshamrani and A. Bahattab, “A comparison between three SDLC models waterfall model, spiral model, and Incremental/Iterative model,” Int. J. Comput. Sci. Issues, vol. 12, no. 1, p. 106, 2015.
N. B. Ruparelia, “Software development lifecycle models,” ACM SIGSOFT Softw. Eng. Notes, vol. 35, no. 3, pp. 8–13, 2010.
G. Alonso et al., Web services. Springer, 2004.
M. P. Papazoglou and W.-J. Van Den Heuvel, “Service oriented architectures: approaches, technologies and research issues,” VLDB J., vol. 16, pp. 389–415, 2007.
R. Rizal and A. Rahmatulloh, “Restful Web Service Untuk Integrasi Sistem Akademik Dan Perpustakaan Universitas Perjuangan,” J. Ilm. Inform., vol. 7, no. 01, pp. 54–59, 2019.
M. A. Salim and H. D. Wahjono, “Integrasi Sistem Informasi Pemantauan Kualitas Lingkungan Air Dan Udara Menggunakan Rest Api Dan Web Service,” J. Rekayasa Lingkung., vol. 14, no. 2, 2021.
L. Richardson and S. Ruby, RESTful web services. “ O’Reilly Media, Inc.,” 2008.
E. Rahm and H. H. Do, “Data cleaning: Problems and current approaches,” IEEE Data Eng. Bull., vol. 23, no. 4, pp. 3–13, 2000.
K. Bittner and I. Spence, Use case modeling. Addison-Wesley Professional, 2003.
S. Nidhra, “Black Box and White Box Testing Techniques - A Literature Review,” Int. J. Embed. Syst. Appl., vol. 2, no. 2, pp. 29–50, 2012, doi: 10.5121/ijesa.2012.2204.
U.S. General Services Administration, “System Usability Scale (SUS),” 2019. https://www.usability.gov/how-to-andtools/methods/system-usability-scale.html
