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Design and Implementation of a Web Service-Based Middleware Application for PDDIKTI Reporting at XYZ University Harkat Christian Zamasi
Engineering, MAthematics and Computer Science Journal (EMACS) Vol. 8 No. 1 (2026): EMACS
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/emacsjournal.v8i1.15355

Abstract

Reporting of academic data to the Higher Education Database (PDDIKTI) is an obligation for every university in Indonesia that must be done accurately and timely in accordance with government regulations. However, in practice, the reporting process is still largely manual via the Neo Feeder application. This causes problems in efficiency, data consistency and possible delays in reporting, particularly in universities with large volumes of academic data. Although PDDIKTI has provided web services facilities, their utilization as part of the Extract, Transform, and Load (ETL) middleware architecture has not been optimally implemented. However, the integration of internal academic information system with PDDIKTI still has problems related to the difference of data structure, business rules and technology platform used and the absence of a generally replicable middleware model. This study aims to design and implement the ETL middleware architecture model based on web services Neo Feeder as a solution for the automation of PDDIKTI data reporting. The research method used is applied research (applied research) with an approach to information systems engineering, which consists of the stages of needs analysis, design of system architecture, implementation and evaluation of prototypes in a case study of XYZ University. The results of this study indicate that the proposed ETL middleware architecture model can integrate internal academic information systems with PDDIKTI in an automatic, structured and controlled manner, thus increasing the efficiency and timeliness of academic data reporting. The resulting architecture model and prototype are generic and can be replicated by other universities as a reference for implementing integrated PDDIKTI data reporting in line with the One Data Higher Education policy.
Model Arsitektur Sistem Informasi Terintegrasi AI untuk Pemantauan dan Intervensi Anak dengan Autism Spectrum Disorder Harkat Christian Zamasi; Arden Sagiterry Setiawan
JITSI : Jurnal Ilmiah Teknologi Sistem Informasi Vol 7 No 2 (2026)
Publisher : SOTVI - Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/jitsi.7.2.616

Abstract

The increasing number of children with Autism Spectrum Disorder (ASD) in Indonesia shows a continuing upward trend; however, it is still confronted with various fundamental challenges, such as the low level of parental understanding regarding early detection, the limited availability of medical professionals and therapists, and the absence of an integrated information system and data center. These conditions result in diagnosis, therapy, and developmental data of children with ASD being scattered and not continuously documented. On the other hand, the advancement of information technology, particularly Artificial Intelligence (AI), offers significant potential in supporting early detection, behavioral analysis, and the provision of personalized and data-driven intervention recommendations. This study aims to design an abstract information system architecture model integrated with AI to support monitoring and intervention processes for children with ASD. The method used is the Design Science Research (DSR) approach, which includes stages of problem identification, model design, conceptual artifact development, and validation through use case scenarios. The study results in an integrated information system architecture model comprising user applications, a data integration layer, AI analytics modules, and a human-in-the-loop mechanism. The contribution of this study is an AI-based integrated conceptual information system framework designed to address the limitations of existing systems, which are generally fragmented and isolated and serves as a foundation for the development of ASD monitoring and intervention systems in Indonesia.