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Exploring The Role of Augmented Reality in Education: Systematic Literature Review Passion Timothy Gerald Sianipar; Wilonotomo; Priati Assiroj
JUTI: Jurnal Ilmiah Teknologi Informasi Vol.23, No.2, July 2025
Publisher : Department of Informatics, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j24068535.v23i2.a1267

Abstract

    The development of digital technology drives innovation in education, one of which is through the implementation of augmented Reality (AR), which increases interactivity and understanding of abstract concepts in learning. This study employs a Systematic Literature Review (SLR) with the PRISMA method to analyze the implementation of AR in education. Of the 3,225,372 articles reviewed, 30 journals met the research criteria, with Marker-Based Tracking as the most commonly used AR method because of its stability and accuracy. The study results showed that AR increases students' interactivity, facilitates understanding of abstract concepts, increases student engagement, improves information retention and memory, facilitates simulation and practice, develops creativity and collaboration, adapts learning to individual needs, and improves cost and resource efficiency, although it still faces challenges in the infrastructure and technical skills of teachers. Therefore, further development in AR applications at various education levels is recommended to improve understanding and adaptation to scientific developments. Keywords: Augmented Reality, Learning Media, Marker-Based Tracking.
SYSTEMATIC LITERATURE REVIEW: METODOLOGI, TEKNOLOGI KEAMANAN, DAN BIDANG IMPLEMENTASI DALAM PENGEMBANGAN SISTEM INFORMASI BERBASIS WEB Andi Aslam Rasyidi Rahman; Priati Assiroj; Cakra Trinata
Pendas : Jurnal Ilmiah Pendidikan Dasar Vol. 10 No. 4 (2025): Volume 10. No4, Desember 2025.
Publisher : Program Studi Pendidikan Guru Sekolah Dasar FKIP Universitas Pasundan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23969/jp.v10i4.33374

Abstract

Web-based information systems are rapidly expanding across sectors, yet development methodologies and security practices remain inconsistent. This study aims to map trends in methodologies, security technologies, and implementation domains through a Systematic Literature Review (SLR). The review followed five stages: defining criteria, selecting sources, screening literature, collecting, and classifying data. Analysis of selected articles from 2021–2025 shows that the most common methodologies are Research and Development (R&D), Waterfall, and Rapid Application Development (RAD), while the adoption of Agile remains limited. In terms of security, most studies emphasize authentication and authorization, some apply encryption and data protection, and very few address web application security aligned with international standards. Regarding implementation, studies are concentrated in education, public service, and e-commerce, while finance and healthcare remain underexplored. These findings highlight research gaps in methodology adoption, security practices, and domain coverage, indicating the need for future studies to integrate modern approaches, apply international standards, and focus on critical sectors.
TINJAUAN SISTEMATIS PENGEMBANGAN SISTEM INFORMASI DOKUMENTASI BERBASIS WEB (2021-2025) Kadek Siva Ayu, Ni; Muhammad Fahrury, Romdendine; Priati, Assiroj
Pendas : Jurnal Ilmiah Pendidikan Dasar Vol. 11 No. 2 (2026): Volume 11 No. 02, Juni 2026.
Publisher : Program Studi Pendidikan Guru Sekolah Dasar FKIP Universitas Pasundan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23969/jp.v11i2.44933

Abstract

This study presents a systematic review of research on web application development and testing methods conducted between 2021 and 2025 using the PRISMA method. From searches across three databases, namely Garuda, Google Scholar, and Open Alex, a total of 13,642 articles were identified and subsequently filtered down to 20 selected studies. The aim of this study is to identify the development methods, testing methods, system modeling, software, and database systems used in the development of web-based documentation information systems. The findings indicate that the Waterfall method is the most widely applied (65%), followed by the Prototyping and Agile methods. Black Box testing dominates as the primary testing method, while UML serves as the standard for system modeling. PHP-based technology is the most dominant software choice, and MySQL remains the absolute most commonly used database system.
Social Media Comments As Forensic Linguistic Corpus In Cybercrime Handling: A Systematic Literature Review Mochammad Alif Risqullah; Mila Rosmaya; Priati Assiroj
MULTITEK INDONESIA Vol 20 No 1 (2026): July
Publisher : Universitas Muhammadiyah Ponorogo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24269/mtkind.v20i1.13854

Abstract

The rise in popularity of social media has increased the arena for cybercrime activities, especially with the presence of digital comments including hate speech, defamation, and information that may violate the Electronic Information and Transaction Law (UU ITE) of Indonesia. This paper presents a Systematic Literature Review (SLR), using the PRISMA 2020 approach, focusing on forensic linguistic approaches applied on social media comments as a data corpus for cybercrime. Literature reviews have been performed on four different databases, which are Google Scholar, Garuda, Scopus, and DOAJ, from the year 2015 to 2024. Out of 172 reviewed papers, only 18 of them have fulfilled the inclusion requirements. Based on synthesis results, the conclusions are that: (1) the two main approaches used in forensic linguistics are lexical semantic and speech act pragmatics; (2) Instagram is the most explored platform in terms of the corpus of data; (3) most of the papers have mapped the results with UU ITE Article 27, 28, and 45; and (4) there is still a lack in the studies related to multimodality and standardization of digital evidence extraction procedures as legally acceptable evidence.
IMPLEMENTASI APLIKASI ANTRIAN PENGAMBILAN PASPOR BERBASIS QR CODE DAN DIGITALISASI ARSIP: SYSTEMATIC LITERATURE REVIEW METODE PRISMA (2019-2025) Muhammad Andi Anugrah Melanggamasputra; Priati Assiroj; Isidorus Anung Prabadhi
Pendas : Jurnal Ilmiah Pendidikan Dasar Vol. 11 No. 2 (2026): Volume 11 No. 02, Juni 2026.
Publisher : Program Studi Pendidikan Guru Sekolah Dasar FKIP Universitas Pasundan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23969/jp.v11i2.45107

Abstract

This research aims to systematically analyze the development of a QR Code-based passport collection queue application integrated with archive digitization in the context of immigration services. This study employs the Systematic Literature Review (SLR) method with a PRISMA approach to literature published between 2019 and 2025 from the Google Scholar, Scopus, IEEE, and Crossref databases. Unlike previous research that tends to examine queue systems and archive digitization separately, this study emphasizes a comparative synthesis to identify relationships, discrepancies in approaches, and the implications of integrating both systems. The analysis results show that the dominance of conventional approaches, both in terms of development methodology and the technology used, has not yet fully addressed the needs of dynamic public service systems. Additionally, a trade-off was found between system stability and technology flexibility, as well as a significant gap in the integration of QR Code-based queue systems with digital archive management. In the context of passport collection services, this condition implies process inefficiencies, verification redundancies, and limitations in real-time data utilization. This research emphasizes that the development of future immigration service systems needs to adopt an integrated multi-technology-based approach, which combines flexibility, security, and real-time capabilities to comprehensively improve service quality.  
SYSTEMATIC LITERATURE REVIEW: PEMETAAN KARAKTERISTIK IMPLEMENTASI DATA MINING PADA BERBAGAI BIDANG Makarim, Amhar Nabil; Nursanto, Gunawan Ari; Assiroj, Priati
Pendas : Jurnal Ilmiah Pendidikan Dasar Vol. 11 No. 02 (2026): Volume 11 No. 02 Juni 2026 Press
Publisher : Program Studi Pendidikan Guru Sekolah Dasar FKIP Universitas Pasundan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23969/jp.v11i02.56859

Abstract

This study aims to map the characteristic of data mining implementation based on 37 journals reviewed systematically. The method employed was a Systematic Literature Review (SLR) with PRISMA approach, consisting of identification, screening, eligibility, and inclusion stages. The data were analyzed descriptively to identify methods, algorithms, data types, and implementation result of data mining across various domains. The findings reveal that the most dominant task was clustering, with 27 articles, while K-Means was the most frequently used algorithm, appearing in 26 studies. The most widely studied implementation domain was economics and business with 12 articles, followed by health with 7 articles, social and government with 6 articles, also tourism and education with 5 articles each. In addition to K-Means, other algorithms identified in the reviewed studies included Apriori, FP-Growth, K-NN, Decision Tree/C4.5, Naïve Bayes, K-Medoids, and U-KMeans. In terms of evaluation, classification studies commonly used accuracy, association rule studies relied on support and confidence, while clustering studies tended to use measures such as the Davies-Bouldin Index and silhouette score. This study concludes that K-Means remains the most dominant algorithm in data mining implementation. The result of this review are expected to serve as a reference for understanding trends in data mining implementation and for supporting more focused future research.
EVALUASI PERFORMA APLIKASI PENGADUAN IRONCARE MENGGUNAKAN GTMETRIX UNTUK REKOMENDASI MAINTENANCE Faiz Amrullah, Naufal; Rosmaya, Mila; Assiroj, Priati
Pendas : Jurnal Ilmiah Pendidikan Dasar Vol. 11 No. 03 (2026): Volume 11 No. 03, September 2026 Release
Publisher : Program Studi Pendidikan Guru Sekolah Dasar FKIP Universitas Pasundan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23969/jp.v11i03.59645

Abstract

Digital complaint systems require fast, stable, and efficient website performance to ensure that users can access public services without technical barriers. Ironcare, also known as Imigrasi Cirebon Care, is a digital complaint system used by the Class I Immigration Office TPI Cirebon to support complaint submission, tracking, and follow-up. This study aims to analyze the performance of the Ironcare homepage and formulate maintenance recommendations based on a GTmetrix report. The research applies a descriptive quantitative method with purposive sampling on the Ironcare homepage. The data were collected from a GTmetrix report generated on April 28, 2026, using the Seattle, WA, USA test server, Chrome 142.0.0.0, and Lighthouse 12.6.1. The test results show that Ironcare obtained GTmetrix Grade B, Performance Score 85%, Structure Score 95%, Largest Contentful Paint 1.2 seconds, Total Blocking Time 0 ms, Cumulative Layout Shift 0.02, Fully Loaded Time 1.6 seconds, Total Page Size 266 KB, and Total Page Requests 7. These findings indicate that the initial access performance of Ironcare is good and lightweight. However, the Speed Index of 5.8 seconds and several Structure Audit findings show the need for maintenance on render-blocking resources, image dimensions, static asset caching, CDN utilization, unused CSS, image formats, and a 404 faviconrequest. This study contributes to performance mapping of an immigration digital complaint system and data-based maintenance recommendations.
The performance of Naïve Bayes, support vector machine, and logistic regression on Indonesia immigration sentiment analysis Priati Assiroj; Asep Kurnia; Sirojul Alam
Bulletin of Electrical Engineering and Informatics Vol 12, No 6: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i6.5688

Abstract

In recent years various attempts have been made to automatically mine opinions and sentiments from natural language in online networking messages, news, and product review businesses. Sentiment analysis is needed as an effort to improve service performance in the organization. In this paper, we have explored the polarization of positive and negative sentiments using Twitter user reviews. Sentiment analysis is carried out using the Naïve Bayes (NB), support vector machine (SVM), and logistic regression (LR) model then compares the results of these three models. The results of the experiment showed that the accuracy of LR was better than SVM and NB, namely 77%, 76%, and 70%.