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Universitas Serang Raya Gedung Utama Lantai 3, Fakultas Teknologi Informasi Program Studi Sistem Informasi Jl. Raya Cilegon KM. 5, Taman, Drangong, Kec. Taktakan, Kota Serang, Banten 42162
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INDONESIA
JSiI (Jurnal Sistem Informasi)
Published by Universitas Serang Raya
ISSN : 24067768     EISSN : 25812181     DOI : https://doi.org/10.30656
Core Subject : Science,
Computer Science & IT Decision Sciences, Operations Research & Management
JSiI (Jurnal Sistem Informasi) is a scientific journal published by the Department of Information System Universitas Serang Raya (UNSERA). This journal contains scientific papers from Academics, Researchers, and Practitioners about research on information systems. JSiI (Jurnal Sistem Informasi) is published twice a year in March and September. The paper is an original script and applied research in information systems.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 348 Documents
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Potensi dan Tantangan Penerapan Platform Crowdfunding Donasi Berbasis Blockchain Muhammad Rizky; Teduh Dirgahayu
Jurnal Sistem Informasi Vol. 12 No. 1 (2025)
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/jsii.v12i1.9279

Abstract

The generosity of Indonesian society, influenced by tradition and religion, has continued to grow with the convenience of digital facilities for crowdfunding. However, there are still challenges to be addressed, such as accountability and transparency in the use of donated funds. The emergence of blockchain technology offers opportunities to enhance transparency, security, and efficiency in fundraising. This study aims to evaluate the potential and challenges of implementing blockchain-based donation crowdfunding platforms through a systematic literature review (SLR) approach following the PRISMA protocol. From the analysis of 41 articles, 37 blockchain-based crowdfunding platforms were found to have the potential to improve transparency, trust, efficiency, accountability, and reduce transaction costs. The main challenges faced include scalability, regulatory compliance, privacy concerns, user adoption, and integration with existing systems. The findings of this study provide valuable insights for nonprofit organizations and philanthropic institutions in leveraging blockchain technology for donation crowdfunding.
jurnal Analisis dan Pengembangan Tata Kelola Teknologi Informasi pada Kantor POS Kotabumi Menggunakan COBIT 2019: Analysis and Development of Information Technology Governance at the Kotabumi POS Office Using COBIT 2019 Wahyudi; Sutedi
Jurnal Sistem Informasi Vol. 12 No. 1 (2025)
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/jsii.v12i1.9771

Abstract

Analysis of process maturity in various organizational domains shows significant progress in operational effectiveness and management. Assessments were carried out on sub-processes in the MEA, DSS, DSS04, and DSS05 domains, with a focus on financial reporting accuracy, decision making, customer service, risk management, and operational efficiency. The results show that many processes are at a good level of maturity, with some sub-processes reaching the highest level of optimization. Although there are areas for improvement, particularly in internal communications and planning, the organization shows great potential for further development and improved performance in the future.   Keywords: Process maturity, operational efficiency, decision making, risk management, customer satisfaction
ANALISIS METODE MULTI-CRITERIA DECISION MAKING (MCDM) UNTUK PENILAIAN KERUSAKAN DAN KEBUTUHAN PEMULIHAN PASCABENCANA Dewa Ramadhan Artagautama; Fadhil Naufal Mafino Novian; Agusta Praba Ristadi Pinem
Jurnal Sistem Informasi Vol. 12 No. 1 (2025)
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/jsii.v12i1.9874

Abstract

Indonesia menghadapi risiko tinggi terhadap bencana alam, sehingga penetapan prioritas untuk rehabilitasi dan rekonstruksi pascabencana menjadi hal yang sangat penting. Studi ini mengevaluasi empat metode Multi-Criteria Decision Making (MCDM), yakni ELECTRE, ARAS, SMART, dan CoCoSo, dalam menentukan prioritas penanggulangan bencana berdasarkan data dari Penilaian Kerusakan dan Kerugian (DaLA) serta Penilaian Kebutuhan Pemulihan Manusia (HRNA). Data ini diolah menjadi matriks keputusan dengan enam kriteria utama, menghasilkan peringkat wilayah terdampak untuk masing-masing metode. Validasi melalui korelasi peringkat Spearman telah menghasilkan nilai korelasi sebesar 0,9636 untuk metode penelitian ELECTRE, ARAS, dan SMART, sedangkan metode CoCoSo memiliki korelasi sedikit lebih rendah, yakni 0,9364. Perbedaan ini disebabkan oleh pendekatan algoritma CoCoSo yang menggunakan multi-agregasi, yaitu kombinasi model penjumlahan bobot (WSM) dan perkalian bobot (WPM), yang memengaruhi hasil peringkat. Penelitian ini menyimpulkan bahwa keempat metode layak digunakan dalam pengambilan keputusan pascabencana, meskipun metode berbasis fungsi nilai optimal seperti ARAS cenderung menunjukkan korelasi lebih tinggi. Penelitian juga mendorong pengembangan sistem berbasis teknologi untuk mempercepat dan meningkatkan akurasi proses pengambilan keputusan dalam situasi pascabencana.
IMPLEMENTATION OF FIREBASE IN THE DEVELOPMENT OF ANDROID-BASED QUEUE RESERVATION AND TREATMENT RECORD APPLICATIONS Audy Fitri Ariani; Agung Brastama Putra; Tri Luhur Indayanti Sugata
Jurnal Sistem Informasi Vol. 12 No. 1 (2025)
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/jsii.v12i1.9880

Abstract

The development of an Android-based reservation and medical record management app is key to improving customer experience and operational efficiency in the beauty salon industry. This study explores the use of Firebase, offering features like Authentication, Firestore, Cloud Messaging, and Cloud Functions, to create a reliable mobile solution. Firebase enables real-time data management, secure authentication, and efficient notifications, enhancing both salon operations and customer experience. Developed with the Waterfall model and MVVM architecture, the app showed positive results in reservation and medical record management. Users can easily book appointments and access treatment history, with fast data transfer powered by Firebase. With response times of 120 ms for reads and 140 ms for writes, Firebase ensures seamless performance. The app reduced booking time by 79.91% compared to manual methods. Further development is recommended to include staff management and real-time analytics for optimized service and better customer insights.
PERFORMANCE EVALUATION OF LIGHTWEIGHT OBJECT DETECTION MODELS FOR REAL-TIME PERSONAL PROTECTIVE EQUIPMENT DETECTION IN THE CONSTRUCTION SITES Herman; Dion, Sandy Alferro; Yulianto, Andik
Jurnal Sistem Informasi Vol. 12 No. 1 (2025)
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/jsii.v12i1.9896

Abstract

The environment of construction industry was known to have a high risk and high number of occupational accidents and injuries. One of the main causes of the occurrences was the construction workers' negligence in wearing personal protection equipment. Computer vision-based approaches were developed to assist in personal protective equipment adherence to address this issue. Using lightweight machine learning algorithms, object recognition can help to detect if the PPEs are worn correctly. We evaluated performance of YOLOv8-Nano and YOLOv9-Tiny (state of the art lightweight object detection models). Custom dataset was used for training the models and then metrics like F1 score, precision, recall mAP50 and mAP50-95 were used to evaluate both models’ performance. Results found that both models were able to show promising real time detections, but the YOLOv9-Tiny model was able to outperform the YOLOv8-Nano model on many evaluation metrics. Specifically, in terms of mAP, YOLOv8-Nano achieved an mAP50 of 81.48, while YOLOv9-Tiny attained a slightly higher mAP50 of 82.70. Higher efficiency in these parameters will help small industry to enforce PPE adherence monitoring using edge device at a relatively low cost. Lastly, enhanced enforcement of PPE regulations through automated detection system can contribute to improve workplace safety which in turns will lead to less injuries.   Keywords: Object Recognition, Computer Vision, Machine Learning, Lightweight, Personal Protective Equipment, YOLO
DESAIN DAN PROTOTIPE SISTEM INVENTORI BARANG BERBASIS WEBSITE PADA JASA WARNA GYPSUM Eviana Hartanti; Muhammad Arifin; R. Rhoedy Setiawan
Jurnal Sistem Informasi Vol. 12 No. 1 (2025)
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/jsii.v12i1.9904

Abstract

This paper presents the design and prototype of a web-based inventory system specifically designed for Jasa Warna Gypsum, a retail business engaged in building materials. The main objective of this study is to address the inefficiencies in manual inventory management, which often leads to inaccurate stock data and delays in decision making. This study focuses on creating an easy-to-use UI/UX design that allows for real-time stock monitoring and management. The system design includes key features such as a real-time dashboard, WhatsApp notifications, and simplified stock tracking functionality to optimize inventory control. The research methodology involves a thorough analysis of the existing manual process, gathering user requirements through interviews and observations, and subsequent prototype design based on the identified needs. The UI/UX design was tested through user experience trials, which showed that the proposed system significantly improves efficiency in managing inventory, reduces time for input and output of stock, and minimizes human errors. Although this study was limited to the design and prototype stages, the results indicate that a full implementation of the system has the potential to solve the existing challenges in inventory management at Toko Jasa Warna Gypsum. This study concludes that the web-based inventory system design successfully meets its objectives and can serve as a baseline model for further development. Future research is recommended to focus on the full implementation and integration of the system in a real-world environment, expanding its capabilities for wider use in similar retail environments. The proposed system also has potential for further optimization, such as mobile integration and advanced reporting features. Keywords: inventory system, web-based, UI/UX design, inventory management, real-time monitoring
Review Framework dan Best Practise Standars COBIT 2019 untuk Implementasi Tata Kelola TI Suhartono, Bambang; Riadi, Imam; Sutikno, Tole
Jurnal Sistem Informasi Vol. 12 No. 1 (2025)
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/jsii.v12i1.9926

Abstract

Tata kelola teknologi informasi (TI) merupakan elemen krusial dalam memastikan keselarasan antara strategi TI dan tujuan bisnis organisasi. Implementasi tata kelola TI membutuhkan framework dan standar best practice yang teruji guna mendukung efektivitas, efisiensi, serta kepatuhan terhadap regulasi. Banyak organisasi menghadapi kesulitan dalam menentukan pendekatan yang tepat atau memilih Framework, standar yang paling sesuai dengan kebutuhan Bisnis. Artikel ini bertujuan untuk meninjau serta  mengulas mengenai COBIT 2019 dan juga mengetahui Framework dan standar best practice yang digunakan dalam COBIT 2019 serta lebih lanjut mengetahui mengenia framework dan standar mana yang paling banyak digunakan. Penelitian ini menggunakan metode literature review  pada COBIT 2019 dengan menganalisa penggunaan framework, standar pada masing-masing Domain serta Proses COBIT 2019. Hasil penelitian diharapkan dapat memberikan wawasan kepada para praktisi TI  untuk memilih pendekatan framework, standar sebagai sebuah pendekatan dalam Tata Kelola TI yang paling sesuai untuk Organisasi.
PRESERVING THE INDIGENOUS MUSICAL INSTRUMENTS OF PAPUAN USING AUGMENTED REALITY TECHNOLOGY Khosin, Noor; Dedi I Inan; Ratna Juita; Muhamad Indra
Jurnal Sistem Informasi Vol. 12 No. 1 (2025)
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/jsii.v12i1.9947

Abstract

This study explores the use of augmented reality (AR) technology as a technology enabling the preservation of traditional Papua musical instruments. It aims of understanding factors that influence the adoption of this technology by people living in Papua who are not indigenous Papuans. The use of AR as a tool for cultural preservation is still limited, particularly in the context of Papua, highlighting a research gap concerning the acceptance of AR technology in regions rich in culture but limited in technology adoption. The study employs Design Science Research (DSR) as a research framework. The development and evaluation in the DSR are conducted rigorously and robustly. Once the AR artifact is developed using uniteAR tool, subsequently it is evaluated employing UTAU2 as a theoretical lens. Particularly in the evaluation stage, it involves 115 respondents as participants in data collection. The data is analyzed with partial least square structural equation modeling (PLS-SEM). The main findings indicate that the measurement model has good reliability and validity, with an R² value of 0.8, meaning that Behavioral Intention and Use Behavior explain 80% of the variability in AR technology adoption. The findings also reveal that performance expectancy, effort expectancy, and facilitating conditions are significant factors driving AR technology adoption among respondents. The implications of this study are highly relevant for the development of strategies using AR technology to introduce and preserve traditional Papua musical instruments. These findings can be used by local governments, indigenous communities, and local content developers to design more effective solutions for enhancing AR adoption in Papua, taking into account key factors influencing public behavioral intentions. Thus, this research not only provides theoretical insights into technology adoption but also strengthens the integration of culture and technology in Papua, opening opportunities for more interactive and engaging cultural preservation.   Keywords:  Technology Adoption, Augmented Reality, Papua Traditional Musical Instruments, PLS-SEM, UTAUT  
DEVELOPMENT OF A PREDICTIVE MODEL FOR EARLY CHILDHOOD LEARNING SUCCESS BASED ON ENSEMBLE LEARNING WITH INTEGRATION OF PSYCHOLOGICAL AND DEMOGRAPHIC DATA Zaqi Kurniawan; Rizka Tiaharyadini; Arief Wibowo
Jurnal Sistem Informasi Vol. 12 No. 1 (2025)
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/jsii.v12i1.9956

Abstract

Early chilhood learning serves as a crucial foundation for cognitive and emotional development, significantly influencing future academic success. The use of machine learning technologies presents chances to improve the effectiveness and scalability of educational practices in the digital age. By creating an ensemble learning-based model which includes both demographic and psychological data. This study overcomes the shortcomings of earlier research, which frequently ignores the psychological elements operating learning outcomes. The F1-Score, Accuracy, Precision, and Recall measures are used in this study to evaluate prediction using Random Forests and Gradient Boosting Machines. With an F1-Score of 89%, Accuracy of 92 %, Precision of 90%, and Recall of 88%, the Random Forest model exceeded Gradient Boosting, proving its ability to manage data complexity while finding a balance between precision and recall. The results show while demographic characteristics like age, gender, and parental occupation have little impact on early learning achievement, academic performance and attendance are the most important predictors. This emphasizes the necessity of focused tactics to improve academic achievement and classroom engagement. The study is limited by the representativeness of the dataset and the limited extent of psychological data, notwithstanding its contributions. To improve the interpretability and use of prediction models in early childhood education, future research should address these constraints by integrating qualitative methodologies, utilizing sophisticated machine learning techniques, and considering larger psychological factors
PREDICTION MODEL FOR STUDENTS' ON-TIME GRADUATION USING ALGORITHM SUPPORT VECTOR MACHINE (SVM) BASED  PARTICLE SWARM OPTIMIZATION (PSO) Hidayatulloh, Syarif; Gandung Triyono; Kiki Ari Suwandi kosasih
Jurnal Sistem Informasi Vol. 12 No. 1 (2025)
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/jsii.v12i1.9964

Abstract

One of the indicators in assessing the tridharma of higher education outcomes and achievements is students' timely graduation and one indicator of the success of the higher education system is timely graduation. However, some students cannot complete their studies on time. In the process of completing the study, several problems emerged, one of which was in completing studies on time, there are problems that arise, such as students who are still repeating because there are grades that have not passed in the course, the Grade Point Average (GPA) is still lacking, the Semester Achievement Index (SAI) is still below the minimum, the total number of semester credit units (total credits) which still have not reached the minimum limit, then the number of active lecture statuses still exceeds 8 semesters, so this problem will have an impact on the accuracy of student study graduate data, where the target performance indicator for graduates is on time The student's target of graduating on time has not been achieved. The factors that cause the students not to graduate on time are not known. In identifying the problem, it was found that the Study Program does not have adequate information regarding the potential for students to graduate on time and the limitations of the study program in assisting students in completing on-time graduation The method used to solve this problem is by creating a prediction model for students' on-time graduation, so that students can receive adequate information regarding the potential for graduating on time. This research aims to create a prediction model for graduating on time using the Support Vector Machine (SVM) method based on Particle Swarm Optimization (PSO) with feature selection. information gain, so that the attributes selected and used are Semester Achievement Index 1, Semester Achievement Index 2, Semester Achievement Index 3, Semester Achievement Index 4, Grade Point Average (GPA) 1, Grade Point Average (GPA) 2, Grade Point Average (GPA) 3, Grade Point Average (GPA) 4, Semester Credit Units 1, and Semester Credit Units 4. The results in this study obtained accuracy values ​​of 0.799, precision 0.851, recall 0.605 and AUC 0.86

Page 32 of 35 | Total Record : 348

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