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Development of a Teacher Administrative Information System Digitally-Based Inside the Classroom Sandi Rohmatullah Alifa; Firman Jaya; Nur Azizah
J-INTECH ( Journal of Information and Technology) Vol 14 No 01 (2026): Journal of Information and Technology
Publisher : LPPM Universitas Bhinneka Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/j-intech.v14i01.2253

Abstract

The development of information technology encourages educational institutions to undergo digital transformation in administrative management, including student attendance recording. MA Syamsul Jinan is still using a manual attendance system that causes various problems, such as low efficiency, a high potential for recording errors, difficulties in data storage, and the risk of attendance data manipulation. This study aims to develop a web-based digital attendance system as part of a classroom administrative information system to improve the efficiency, accuracy, and transparency of managing student attendance data. The research method used is Research and Development (R&D) with the Waterfall development model which includes requirements analysis, design, implementation, testing, and maintenance. Data were collected through observation, questionnaires, and documentation. System quality evaluation refers to the ISO/IEC 25010 standard with a focus on six aspects, namely functionality suitability, usability, reliability, user satisfaction, maintainability, and portability. The results show that all system features function well, with a usability level of 87.6% which falls into the very good category. The system has reliability, ease of maintenance, and can run optimally on various devices and browsers. Thus, the web-based digital attendance system is declared feasible to implement and capable of improving the quality of educational administration at MA Syamsul Jinan.
Web-Based Umrah Administration Information System at PT. Nur Haramain Mulia Tour
Journal of Electrical Engineering and Computer (JEECOM) Vol 8, No 1 (2026)
Publisher : Universitas Nurul Jadid

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33650/jeecom.v8i1.14873

Abstract

PT. Nur Haramain Mulia Tour still handled several umrah administrative processes manually, including pilgrim registration, data retrieval, and report preparation. This condition reduced efficiency and increased the risk of data loss and service delays. This study aimed to develop a web-based umrah administration information system to improve administrative services, facilitate online registration, and support more structured data management. The system was developed using the Rapid Application Development approach, which consists of requirement planning, system design, and implementation stages. Data were collected through observation, interviews, and literature study, while the application was implemented using the Laravel framework and MySQL database. The resulting system supports major administrative functions, including registration, pilgrim data management, information access, and report generation within a centralized database environment. System evaluation was conducted using black-box testing for internal validation and questionnaire-based external testing involving administrative staff and prospective pilgrims. The external testing results showed a satisfaction score of 94%, indicating that the system was highly acceptable to users. The study concludes that the proposed web-based system improves the effectiveness and efficiency of umrah administrative services and assists both staff and pilgrims in managing registration and information processes more accurately and systematically.
Information System Success Model for the Evaluation of E-Government Applications in the Public Sector (Case Study: Whole App – Bandung Super App) Paramita Paramita; Luthfi Ramadani; Basuki Rahmad
Eduvest - Journal of Universal Studies Vol. 6 No. 4 (2026): Eduvest - Journal of Universal Studies
Publisher : Green Publisher Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59188/eduvest.v6i4.52693

Abstract

This study examines the effectiveness of an e-government application implemented by the Bandung City Government, namely the Kabeh (Bandung Super App), in supporting public service delivery. The background of this research is driven by the gap between the government’s objectives in providing digital public services and the actual user experience, which reflects low adoption, limited functionality, and user dissatisfaction. Therefore, this study aims to evaluate the success of the application using a modified DeLone and McLean Information Systems Success Model by incorporating Digital Literacy as an additional variable. This research employed a mixed methods approach, combining quantitative data through questionnaires and qualitative data through semi-structured interviews. The quantitative analysis measures relationships among variables such as System Quality, Information Quality, Service Quality, Digital Literacy, Intention to Use, User Satisfaction, and Net Benefit, while qualitative findings enrich the interpretation of user perceptions. The results indicate that Service Quality significantly influences Intention to Use, while Information Quality, Service Quality, Intention to Use, and Net Benefit significantly affect User Satisfaction. However, System Quality and Digital Literacy show no significant influence on both Intention to Use and User Satisfaction. Overall, the study concludes that the success of the application is primarily determined by service quality, information relevance, and perceived benefits, rather than technical aspects alone.
Design and Construction of a Long Range (LoRa) Based Rat Pest Monitoring Information System Model on Agricultural Land: Rancang Bangun Model Sistem Informasi Monitoring Hama Tikus Pada Lahan Pertanian Berbasis Long Range (LoRa) Vina Oktaviani; Baso Maruddani; Muhammad Rohidh Alfayidh
JOINCS (Journal of Informatics, Network, and Computer Science) Vol. 8 No. 2 (2025): November
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/joincs.v8i2.1695

Abstract

Penelitian ini menyajikan perancangan dan implementasi model sistem informasi monitoring hama pertanian berbasis Long Range (LoRa) yang dikembangkan untuk area persawahan terpencil dengan keterbatasan jaringan internet. Serangan hama tikus berkontribusi besar terhadap penurunan produktivitas padi sehingga diperlukan sistem monitoring otomatis yang mampu mendeteksi pergerakan hama dan mengirimkan informasi secara real-time. Sistem yang dikembangkan mengintegrasikan sensor Passive Infrared (PIR) untuk deteksi gerakan, ESP32-CAM untuk akuisisi citra, aktuator ultrasonik untuk pengusiran hama, serta modul LoRa sebagai media transmisi jarak jauh. Data yang diterima diproses dan divisualisasikan melalui dashboard sistem informasi pertanian berbasis web yang menampilkan notifikasi deteksi, citra hama, serta histori monitoring. Hasil pengujian menunjukkan bahwa sensor PIR mampu mendeteksi pergerakan hingga jarak 3 meter dengan tegangan stabil. Komunikasi LoRa dapat beroperasi hingga jarak 300 meter dengan kehilangan paket minimal, sedangkan dashboard sistem informasi berhasil menampilkan aliran data secara real-time dan menyimpan rekam jejak monitoring secara terstruktur. Sistem ini dinilai sesuai diterapkan pada lingkungan pertanian dan mendukung praktik smart farming.
The Relationship Between Digital Information Exposure and Social Stigma in People with Mental Disorders in Rural Areas Based on Traditional Culture Stefani Chairunisa Kurniawati; Sifa Fauziah; Sri Kurnia Dewi
Jurnal Kesehatan Komunitas Indonesia Vol 6 No 1: April 2026
Publisher : Al-Hijrah Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58545/jkki.v6i1.679

Abstract

Background: Social stigma toward people with mental disorders (PMD/ODGJ) remains prevalent in rural communities, where traditional cultural beliefs often reinforce negative perceptions. Limited exposure to evidence-based digital health information may exacerbate stigma by hindering accurate mental health literacy. Objective: This study aimed to examine the relationship between digital information exposure and social stigma toward PMD in a traditional rural setting. Methods: A quantitative cross-sectional study was conducted in Nyalindung Village, Cianjur Regency, involving 109 community members selected via purposive sampling. Digital information exposure was measured using the eHealth Literacy Scale (eHEALS), and social stigma was assessed using the Perceived Devaluation and Discrimination Scale (PDDS). Data were analyzed using descriptive statistics and the Chi-Square test (α = 0.05). Results: The majority of respondents reported low digital information exposure (52.3%), and 78.9% exhibited high social stigma toward PMD. Statistical analysis revealed a significant relationship between digital information exposure and social stigma (p < 0.001), with lower exposure strongly associated with higher stigma levels. Conclusion: Limited exposure to digital mental health information is significantly associated with elevated social stigma in traditional rural communities. Integrating culturally sensitive, digital-based mental health literacy interventions into primary healthcare and community outreach programs is recommended to reduce stigma and foster inclusive support systems.
Adaptive Graph Based Intelligence Models for Cross Domain Knowledge Discovery in Large Scale Heterogeneous Information Systems Winny Purbaratri; Krisna Widi Nugraha; Rian Ardianto; Rosyid Ridlo Al-Hakim; Yogiek Indra Kurniawan; Ribut Julianto
Global Science: Journal of Information Technology and Computer Science Vol. 1 No. 4 (2025): December: Global Science: Journal of Information Technology and Computer Scienc
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70062/globalscience.v1i4.193

Abstract

The rapid growth of heterogeneous information systems across multiple domains has introduced complex challenges in data analysis, particularly when dealing with diverse data types such as text, images, and sensor data. Traditional machine learning (ML) methods often struggle to capture the intricate relationships inherent in these large scale datasets, as they typically rely on linear models and feature vectors that fail to represent the full complexity of the data. This study aims to develop an adaptive graph based intelligence model that addresses these challenges by leveraging the power of graph structures to represent heterogeneous data and capture both structural dependencies and semantic connections. The proposed model integrates Graph Neural Networks (GNNs) with adaptive learning mechanisms, allowing for continuous knowledge extraction, pattern discovery, and cross domain inference. By representing diverse data sources as interconnected graphs, the model enables the transfer of knowledge across different domains, improving its ability to make accurate predictions and generate insights in dynamic environments. The results demonstrate that the graph based model outperforms traditional machine learning techniques in terms of accuracy, efficiency, and scalability, especially when applied to real world applications involving large and complex datasets. This paper also discusses the advantages of the adaptive learning mechanisms, which personalize the model’s training process and improve its robustness over time. Furthermore, the findings highlight the model’s potential for cross domain knowledge discovery, with applications in fields such as healthcare, marketing, and industrial automation. Finally, the paper offers recommendations for future research, including refining adaptive learning mechanisms and exploring new graph based techniques to enhance the representational power of the model. The study contributes to the ongoing development of intelligent systems capable of handling heterogeneous data across multiple domains and offers a foundation for future advancements in cross domain knowledge discovery.
Context Sensitive Artificial Intelligence for Dynamic User Behavior Modeling in Next Generation Smart Information Platforms Rusmin Saragih; Enda Ribka Meganta P; Tiwuk Widiastuti; Ahmad Jurnaidi Wahidin; Erlita Sulistiati; Muhamad Furqon
Global Science: Journal of Information Technology and Computer Science Vol. 1 No. 4 (2025): December: Global Science: Journal of Information Technology and Computer Scienc
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70062/globalscience.v1i4.194

Abstract

This study explores the development and implementation of a context sensitive artificial intelligence (AI) model designed to predict and personalize user behavior in smart information platforms. Traditional user behavior models often fail to adapt to dynamic and evolving user needs, especially in diverse environments where contextual factors such as time of day, location, and device type play a critical role in shaping user preferences. To address these limitations, the proposed context sensitive AI model integrates real time contextual data alongside traditional behavioral data, enabling it to make more accurate predictions and provide personalized, relevant content. The model utilizes advanced machine learning techniques, such as deep learning and reinforcement learning, to continuously update and refine user behavior models based on contextual shifts. Through the integration of contextual parameters, the model demonstrates improved prediction accuracy, system responsiveness, and overall user satisfaction compared to static, context agnostic models. Furthermore, the study discusses the key advantages of context aware AI, such as its ability to dynamically adjust to real time changes in user behavior, providing more adaptive, personalized services. Challenges encountered during the model's development, including issues related to data privacy, scalability, and the integration of multiple contextual data sources, are also addressed. The findings suggest that context sensitive AI can significantly enhance the effectiveness of smart platforms by improving user engagement and content relevance. Finally, the study provides recommendations for further research to explore deep learning methods for context detection and to improve the discoverability and integration of AI driven features in user interfaces.
Integrating Semantic Computing and Predictive Analytics to Enhance Reliability and Scalability of Global Information Systems
Global Science: Journal of Information Technology and Computer Science Vol. 1 No. 4 (2025): December: Global Science: Journal of Information Technology and Computer Scienc
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70062/globalscience.v1i4.196

Abstract

Global information systems (GIS) are essential for managing large scale data across industries such as healthcare, finance, and urban planning. As the volume and complexity of data continue to grow, there is an increasing need for systems that can handle these demands while maintaining reliability and scalability. This research explores the integration of semantic computing and predictive analytics as a solution to improve the performance of GIS. Semantic computing, through the use of ontologies and standardized data models, enhances data interoperability, allowing systems to interpret and exchange data meaningfully across diverse platforms. On the other hand, predictive analytics uses statistical methods and machine learning models to forecast system behavior and optimize resource allocation, ensuring systems remain adaptive under varying loads. By integrating these two methodologies, this study demonstrates how they can address key challenges in global information systems, such as fault tolerance, system adaptability, and real time decision making. The results show significant improvements in system reliability and scalability, as well as better performance under high data volumes and diverse user interactions. The integrated approach was tested in several use cases, including urban planning, healthcare, and supply chain management, with results indicating that systems utilizing both semantic computing and predictive analytics are more resilient, accurate, and efficient. This paper discusses the practical implications of this integration for global scale applications and suggests future research directions, including the incorporation of emerging technologies like blockchain and artificial intelligence to further enhance the capabilities of GIS.
The Role of Accounting Information Systems in Improving the Sustainability of Consumer Cooperatives in KPRI Sehat Rembang Laiyinatul Azizah; Agustina Eka Harjanti; Heni Risnawati
Advances in Management & Financial Reporting Vol. 4 No. 2 (2026): February - May
Publisher : Yayasan Pendidikan Bukhari Dwi Muslim

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60079/amfr.v4i2.720

Abstract

Purpose: This study examines the role of Accounting Information Systems (AIS) in supporting the sustainability of consumer cooperatives at KPRI SEHAT Rembang. Research Method: A descriptive qualitative approach was employed. Data were collected through interviews, observation, and documentation involving the cooperative’s chairman, treasurer, and employees. The data were analyzed using data reduction, data display, and conclusion drawing, with triangulation applied to ensure validity. Results and Discussion: The findings indicate that KPRI SEHAT Rembang has implemented an AIS based on Microsoft Excel to record transactions, manage savings and loans, and prepare financial statements. Although the system remains relatively simple and semi-manual, it has been applied consistently and provides financial information to support administrative activities, reporting, SHU calculation, and managerial decision-making. Implications: The study suggests that even a simple AIS can strengthen financial management practices and contribute to cooperative sustainability. Further research may explore the effectiveness of more integrated digital accounting systems in improving cooperative performance.
Development Individual Work Activity Report Information System at PT. Ayub Pri Tower Kreasi Website based Dimas Putra Ramadhan Mendrofa; Hardiansyah Putra; Abdul Khaliq
Bahasa Indonesia Vol 17 No 11 (2026): Instal : Jurnal Komputer
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jurnalinstall.v17i11.463

Abstract

PT. Ayub Pri Tower Kreasi operates in the construction and network installation services sector. Based on interviews and observations, work activity reporting is still done manually after the job is completed and by only one person. This creates obstacles such as a lack of information, potential reporting errors, and difficulties in storing and retrieval of historical data. As a result, management does not obtain accurate and real-time information on employee work activities, hampering decision-making and employee performance evaluation. Therefore, this research aims to develop a web-based individual work activity information reporting system. This system is expected to assist management in operations, support decision-making, improve performance, and ensure the accountability of each employee. Through the data and information from the developed system, company management can make effective decisions, conduct evaluations and assess management strategies, and ensure each technician/employee's performance. The system was developed using the waterfall method, which includes analysis, design, implementation, testing, and maintenance. System testing was conducted using black box testing to ensure system functions operate as required.

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