cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Agus Junaidi
Contact Email
agus.asj@bsi.ac.id
Phone
+6221231170
Journal Mail Official
jurnal.reputasi@bsi.ac.id
Editorial Address
Jl. Kramat Raya No 98, Senen, Jakarta Pusat
Location
Kota adm. jakarta barat,
Dki jakarta
INDONESIA
Reputasi: Jurnal Rekayasa Perangkat Lunak
Published by Universitas Bina Sarana Informatika
ISSN : -     EISSN : 27471799     DOI : https://doi.org/10.31294/reputasi
Core Subject : Science,
Computer Science & IT
Reputasi: Jurnal Rekayasa Perangkat Lunak pertama kali publikasi tahun 2020 dengan nomor ISSN (Elektonik): 2747-1799 yang diterbitkan oleh Lembaga Ilmu Pengetahuan Indonesia (LIPI). Reputasi: Jurnal Rekayasa Perangkat Lunak adalah jurnal yang diterbitkan oleh Program Studi Rekayasa Perangkat Lunak Universitas Bina Sarana Informatika. Reputasi: Jurnal Rekayasa Perangkat Lunak diterbitkan dua kali setahun pada bulan Mei dan November dalam bentuk elektronik. Redaksi menerima naskah berupa artikel ilmiah dan penelitian pada bidang: Rekayasa Perangkat Lunak, Sistem dan Teknologi Informasi, Interaksi Manusia Komputer, Rekayasa Pengetahuan, Sistem Pendukung Keputusan, Sistem Fuzzy, dan Big Data.
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 195 Documents
 16   17   18   19   20 
Analysis of Acceptance of E-Learning Users of Universitas Bhinneka PGRI Using the UTAUT Method Renzy Praha Nandiva Renzy; Yayak Kartika Sari; Joko Iskandar
Reputasi: Jurnal Rekayasa Perangkat Lunak Vol. 7 No. 1 (2026): Mei 2026
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/reputasi.v7i1.12641

Abstract

The development of educational technology encourages the application of digital learning systems to support learning activities to take place more optimally and save time. Universitas Bhinneka PGRI has implemented the Learning Management System (LMS) as a means of supporting the digital learning system. A study of the level of user acceptance needs to be carried out to identify various influential factors so that they can be used for development according to developments based on the UTAUT method. This study aims to analyze the factors that affect LMS acceptance in users at Bhinneka PGRI Tulungagung University using the UTAUT method. This study uses a quantitative approach with a survey research type involving 95 users as a sample selected by purposive sampling technique. Data were collected through questionnaires with a likert scale of 1-5 and analyzed using the SEM-PLS method which included outer model test, inner model, and hypothesis test. This research resulted in LMS acceptance at UBHI which was quite good. This is shown by Performance Expectancy having a positive and significant influence on Behavioral Intention of 0.235. Effort Expectancy was 0.298, and Social Influence was 0.445. In addition, Behavioral Intention had a positive and significant effect on Use Behavior with a value of 0.673. Meanwhile, Facilitating Conditions had a positive but insignificant effect on Use Behavior with a coefficient value of 0.134. This study concludes that the use of LMS is influenced by the perception of benefits, ease of use, and social environmental support, compared to supporting facilities. This research contributes theoretically to the development of the UTAUT model and practically as an evaluation of improving the quality of LMS in universities. 
Mobile JKN User Experience and Quality in Karangtalun Using Heart Framework and Mars  Nurwiyati Prihandari; Yayak Kartika Sari; Joko Iskandar
Reputasi: Jurnal Rekayasa Perangkat Lunak Vol. 7 No. 1 (2026): Mei 2026
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/reputasi.v7i1.12642

Abstract

Transformasi digital melalui aplikasi Mobile JKN bertujuan untuk meningkatkan efisiensi layanan BPJS Kesehatan. Namun, penguna di Desa Karangtalun masih menghadapi berbagai kendala teknis dan kompleksitas antarmuka. Penelitian ini bertujuan untuk mengelaluasi pengalaman pengguna dan kualitas aplikasi Mobile JKN guna mengidentifikasi elemen yang memerlukan optimalisasi. Metode yang digunakan adalah HEART Framework dengan pendekatan Goals-Signals-Metrics (GSM) untuk mengukur aspek emosional dan perilaku pengguna, dan Mobile Application Rating Scale (MARS) untuk kualitas teknis secara objektif melalui nilai mean. Target keberhasilan pada dimensi HEART Framework ditetapkan sebesar 80% untuk setiap metrik utama. Hasil penelitian menunjukkan seluruh dimensi HEART Framework berhasil melampaui target dengan capaian tertinggi pada dimensi Engagement sebesar 86% dan terendah pada Adoption sebesar 81,4%. Sementara itu, hasil MARS menunjukkan kualitas aplikasi berada pada kategori sangat baik dengan total skor 4,253, di mana dimensi Functionality memperoleh nilai terendah sebesar 3,984. Temuan ini menjadi landasan strategis bagi BPJS Kesehatan dalam meningkatkan adopsi dan kepuasan layanan digital bagi masyarakat dengan tingkat literasi digital yang beragam.
Development of a Computer Vision-Based Auto-Scroll Guitar Chord Application Using Motion Detection M. Zikry Sahendra Chan; Qatrunnada Athirah Herdiyanto; Chelsea Febiola Sebayang; Debi Yandra Niska
Reputasi: Jurnal Rekayasa Perangkat Lunak Vol. 7 No. 1 (2026): Mei 2026
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/reputasi.v7i1.12681

Abstract

The development of computer vision technology enables the creation of a more natural human-computer interaction system through the use of body movements as a control medium. One of the problems often faced by users of digital guitar chord applications is the process of navigating the chord display which is still done manually so that it can interfere with guitar playing activities. This study aims to design and implement a computer vision-based AutoChord application that utilizes head movement detection as a control medium to automatically auto-scroll the guitar chord display. The research method used is the Waterfall software development method which includes the stages of system requirements analysis, system design, implementation, and system testing. The system was developed using webcam-based facial detection technology to read changes in the user's head orientation in real-time. The results of the study show that the AutoChord application is able to automatically run the chord display navigation function through the user's head movements so that it can increase the comfort and efficiency of user interaction when playing the guitar. Thus, the developed system can be an alternative solution in supporting guitar playing activities based on computer vision interaction
Optimisation of TNI Personnel Postings Using an Android-Based AHP System Syahfrizal Fakhri Irawan; ginanjar setyo permadi; Tanhella Zein Vitadiar
Reputasi: Jurnal Rekayasa Perangkat Lunak Vol. 7 No. 1 (2026): Mei 2026
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/reputasi.v7i1.12683

Abstract

Efficiency and objectivity in the placement of Indonesian National Armed Forces (TNI) personnel are crucial aspects of military human resource management. This study aims to develop an Android-based personnel placement recommendation system using the Analytic Hierarchy Process (AHP) method to support faster, more accurate, and consistent decision-making. The study population comprised 300 active TNI personnel, with a purposive sample of 120 personnel possessing complete data on rank, length of service, education, competency, and disciplinary records. Data were collected from internal documents, personnel records, performance reports, and information from the TNI Air Force Planning and Budget Staff. The results indicate that rank and length of service are the dominant criteria, while education, competency, and disciplinary records provide additional contribution. The system generates objective, consistent, and user-friendly recommendations, validated through functionality and user acceptance testing. The findings demonstrate that implementing AHP in an Android-based recommendation system enhances efficiency, transparency, and objectivity in personnel placement and has potential for adoption in other TNI units or similar military organizations
Implementation of Zero-Shot DeBERTa and IndoBERT for Aspect-Based Sentiment Analysis on Reviews of Five LLM Applications Fabriyan Fandi Dwi Imaniawan; Ragil Wijianto; Vadlya Maarif; Joko Dwi Mulyanto; Mustofa Mustofa; Aprih Widayanto
Reputasi: Jurnal Rekayasa Perangkat Lunak Vol. 7 No. 1 (2026): Mei 2026
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/reputasi.v7i1.12790

Abstract

Large Language Model (LLM) applications such as ChatGPT, Gemini, Copilot, Claude, and Perplexity have been massively adopted in Indonesia, yet user experience evaluation remains largely limited to global sentiment analysis. This study implements Aspect-Based Sentiment Analysis (ABSA) using a dual-Transformer approach: DeBERTa zero-shot for aspect extraction and IndoBERT for sentiment classification on 5,000 Indonesian-language reviews from the Google Play Store across four aspect categories. Manual validation by two annotators on 300 samples yielded Cohen’s Kappa of  (aspect) and  (sentiment), both Moderate. Evaluation against the gold standard showed aspect accuracy of 37.5% (weighted F1 = 0.42) and sentiment accuracy of 64.7% (weighted F1 = 0.61). Sensitivity analysis across five hypothesis templates revealed inter-template Kappa of 0.19–0.63, confirming template selection impact on predictions. Comparative analysis reveals Copilot achieves the highest satisfaction (mean score 4.67), while Claude records the most complaints (36.9% negative). This study contributes a validated comparative ABSA framework for Indonesian-language LLM applications

Page 20 of 20 | Total Record : 195

 16   17   18   19   20 

Filter by Year

2020 2026


Reset
Filter By Issues
All Issue Vol. 7 No. 1 (2026): Mei 2026 Vol. 6 No. 2 (2025): Edisi November 2025 Vol. 6 No. 1 (2025): Mei 2025 Vol. 5 No. 2 (2024): Edisi November 2024 Vol. 5 No. 1 (2024): Mei 2024 Vol. 4 No. 2 (2023): November 2023 Vol. 4 No. 1 (2023): Mei 2023 Vol. 3 No. 2 (2022): November 2022 Vol. 3 No. 1 (2022): Mei 2022 Vol. 2 No. 2 (2021): November 2021 Vol. 2 No. 1 (2021): Mei 2021 Vol. 1 No. 2 (2020): November 2020 Vol. 1 No. 1 (2020): Mei 2020 More Issue