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INDONESIA
Journal of Information Systems and Informatics
Published by Asosiasi Doktor Sistem Informasi Indonesia
ISSN : 26565935     EISSN : 26564882     DOI : 10.63158/journalisi
Core Subject : Science,
Computer Science & IT
Journal-ISI is a scientific article journal that is the result of ideas, great and original thoughts about the latest research and technological developments covering the fields of information systems, information technology, informatics engineering, and computer science, and industrial engineering which is summarized in one publisher. Journal-ISI became one of the means for researchers to publish their great works published two times in one year, namely in March and September with e-ISSN: 2656-4882 and p-ISSN: 2656-5935.
Arjuna Subject : -
Articles 653 Documents
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Unlocking the Potential of OLT for Startup ISPs in Indonesia: Challenges and Strategies Mustofa, Dinar; Saputra, Dhanar Intan Surya; Kusuma, Velizha S; Aminuddin, Afrig; Wirasto, Anggit; Apitiadi, Satyo Dwi
Journal of Information System and Informatics Vol 6 No 4 (2024): December
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v6i4.943

Abstract

This study explores the implementation of Optical Line Terminal (OLT) technology by Internet Service Providers (ISPs) startups in underserved and remote areas of Indonesia, examining its effectiveness, challenges, and opportunities. The research reveals that OLT technology can significantly improve internet service quality, with measurable increases in speed (up to 30%) and reliability (20% improvement), especially in rural areas. However, ISP startups face several technical challenges, including inadequate fiber optic infrastructure, high initial investment costs, and the complex geographical conditions across Indonesia’s diverse islands. Regulatory barriers, such as lengthy licensing processes and inconsistent policies, further hinder the deployment of OLT technology. Despite these challenges, the study identifies key opportunities for ISP startups to overcome these obstacles. Collaboration with government initiatives like the Palapa Ring and the potential integration with 5G and IoT technologies can reduce costs and accelerate network deployment. Additionally, leveraging existing infrastructure enables faster expansion of broadband services, particularly in remote regions. The research also finds that ISP startups adopting OLT technology can significantly narrow the digital divide by expanding service coverage in underserved areas, with a noted 25% increase in digital inclusion. These findings offer valuable insights for policymakers and business leaders, informing strategies to optimize OLT technology and foster a more equitable digital transformation across Indonesia, particularly in expanding access to broadband internet in marginalized regions.
Evaluating YOLOv5 and YOLOv8: Advancements in Human Detection Ma Muriyah, Nimatul; Sim, Joel Hamim; Yulianto, Andik
Journal of Information System and Informatics Vol 6 No 4 (2024): December
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v6i4.944

Abstract

The YOLO (You Only Look Once) method is a state-of-the-art approach in real- time object detection, known for its high-speed image processing capabilities. Recently YOLO versions have differed in performance, particularly in terms of detection accuracy and computational efficiency. The objective of this study is to assess the effectiveness and performance of YOLOv5 and YOLOv8 in real-time human detection applications using the SEMMA (Sample, Explore, Modify, Model, and Assess) methodology also. The dataset was processed through the Roboflow platform, which facilitated both the dataset management and the labeling process. Roboflow's tools streamlined the annotation of images, ensuring consistent labeling for deep learning model training and evaluation. F1 score, recall score, and precision score are compared both YOLOv5 and YOLOv8 to evaluate the performance of these architectures. The result of the evaluations shows that the performance of the YOLOv8 is better than the YOLOv5 which, YOLOv5 achieved F1-score equal 0.5865 (58%), recall score equal 0.83 (83%), and precision score of 0.4535 (45%). Meanwhile, YOLOv8 demonstrated better performance, with F1-score of 0.7921 (79%), recall score of 0.8289 (82%), and precision score of 0.7585 (75%). Base on the evaluations, we concluded that the performance of the YOLOv8 model is greater than the YOLOv5 model for Precision, and F1-Score, while YOLOv5 has slightly better score on recall. The contribution of this study is going to implemented into Audio guidance for the blind’s prototype that have been developing in previous study.
Information Security Evaluation at Hospital Using Index KAMI 5.0 and Recommendations Based on ISO/IEC 27001:2022 Wibawa, I Nyoman Adi Artha; Susila, Anak Agung Ngurah Hary; Pasirulloh, Muhammad Alam
Journal of Information System and Informatics Vol 6 No 4 (2024): December
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v6i4.949

Abstract

Bali Mandara Regional Hospital integrates information technology into its healthcare services, but ransomware attacks pose significant risks to data security. In accordance with the 2016 Indonesian Ministry of Communication and Informatics regulation, Electronic System Operators (PSE) are required to ensure information security, emphasizing confidentiality, integrity, and availability. To support this, the National Cyber and Crypto Agency introduced the Index KAMI, an evaluation tool aligned with ISO/IEC 27001 standards. This study evaluates the hospital’s information security using Index KAMI 5.0, yielding a score of 177, which classifies its readiness as “Not Eligible” for ISO 27001 compliance. Recommendations for improvement include establishing clear governance policies, implementing systematic risk management, enhancing asset management with integrated inventories, and strengthening data protection through access control and encryption. Additional measures involve improving physical security with surveillance systems and fostering stronger vendor relationships through binding SLA agreements. By adopting these measures, Bali Mandara Regional Hospital can enhance its security system, protect patient data, and achieve compliance with international standards.
Risk Analysis of Business Continuity Plan in Light Steel Company Using ISO 31000 Framework Andry, Johanes Fernandes; Christianto, Kevin; Purnomo, Yunianto; Lee, Francka Sakti
Journal of Information System and Informatics Vol 6 No 4 (2024): December
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v6i4.955

Abstract

Light Steel Company is an industry engaged in manufacturing, has adopted technology and has a data center. The purpose of this study is to provide a guide and strategy for preventing risks and actions to minimize and overcome risks that can be used and implemented, so that the company's business processes can continue to run sustainably. This study uses Business Continuity Plan (BCP) using ISO 31000. Data collection is used by an interviewing employee who works at this organization. The analysis shows there are 15 possible risks that will hinder the operation of Light Steel companies based on the risk level high, medium, and low categories. High risk level is 26.7%, there are 4 possible risks, namely R05 (Loss of spare parts), R06 (Unscheduled maintenance and care for trucks and equipment spare parts), R10 (Server down) and R012 (Network connection problems). Medium risk level is 26.7%, there are 4 possible risks, namely R02 (flood), R07 (Cybercrime), R08 (Hacking), and R011 (Sudden power outage). Finally for low risk level is 46.6%, there are 7 possible risks, namely R01 (Earthquake), R03 (Dust), R04 (Fire), R09 (Abuse of access rights), R13 (Overheat), R14 (Data Corrupt), and R15 (Virus Attack, Malware).
Developing a UKM Activity Application for Universities in North Jakarta Using Scrum Christianto, Kevin; Lee, Francka Sakti; Witari, Putu Sita; Andry, Johanes Fernandes; Budiyantara, Agus
Journal of Information System and Informatics Vol 6 No 4 (2024): December
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v6i4.956

Abstract

Student Activity Units (UKM) plays an important role in supporting the development of student skills outside of academic activities. However, the management of UKM activities often faces obstacles in communication, administration, and membership management. This study aims to develop a UKM Activity Application designed to improve the operational efficiency of UKMs at Universities in North Jakarta. This application is equipped with key features such as member registration, activity management, attendance, and transparency of financial administration. The development was carried out using the Scrum method, which involves an iterative process starting from user needs analysis, product backlog preparation, to feature development in sprints. Daily stand-up meetings are held to monitor progress, and sprint reviews are used for evaluation and adjustment. The final result of this study is an application that is able to improve the efficiency of UKM activity management, strengthen communication between members, and increase student involvement in campus activities. This application is expected to be a modern digital solution to facilitate the management of UKMs in the university environment.
Hotel Guest Length of Stay Prediction Using Random Forest Regressor Singgalen, Yerik Afrianto
Journal of Information System and Informatics Vol 6 No 4 (2024): December
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v6i4.959

Abstract

This research offers a robust framework for integrating predictive analytics into hospitality operations, contributing to sustainable growth and competitive advantage in the industry. This research investigates the application of the Random Forest Regression model to predict the Length of Stay (LoS) of hotel guests, leveraging key features such as country, guest type, room type, and rating. The study addresses the need for precise forecasting to optimize resource allocation, improve operational efficiency, and support data-driven decision-making in the hospitality sector. The methodology involves data collection from a structured dataset of guest reviews, preprocessing through encoding categorical variables, converting target values into numeric forms, and standardizing features to ensure consistency and uniformity. The dataset is split into training (80%) and testing (20%) subsets, with hyperparameters such as n_estimators=100 and random_state=42 set to ensure stability and reproducibility during model training. The Random Forest Regression model demonstrated strong predictive performance, achieving an R-squared value of 0.85 and a Mean Absolute Error (MAE) of 1.06. Feature importance analysis identified "country" as the most significant variable (importance score: 0.5), followed by guest type (0.2), room type (0.15), and rating (0.15). The Predicted vs. Actual Plot and Error Distribution evaluation reveals that most errors cluster near zero, indicating high accuracy with minor deviations in extreme cases. These findings emphasize the model’s potential to enhance marketing strategies, optimize resource allocation, and improve guest satisfaction. This research offers a robust framework for integrating predictive analytics into hospitality operations, contributing to sustainable growth and competitive advantage in the industry.
Employee Performance Evaluation Using ANP and TOPSIS Situmeang, Monica; Fakhriza, M.
Journal of Information System and Informatics Vol 6 No 4 (2024): December
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v6i4.963

Abstract

In the era of competitive globalization, employee performance evaluation is crucial for ensuring productivity and quality in human resources. This research addresses the challenge of subjectivity in performance evaluation by integrating the Analytical Network Process (ANP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods. The study identifies relevant evaluation criteria, assigns weights using ANP, and prioritizes employee performance objectively through TOPSIS. Using a Research and Development (RnD) approach, data were collected via observations, interviews, and documentation. Results demonstrate that the combination of ANP and TOPSIS significantly improves the accuracy and fairness of evaluations, reducing bias by 20% and enhancing transparency by 15% compared to traditional methods. Employees with a preference score of 1.00, such as Sumadin, Siti, and Ardianto, were deemed to have optimal performance across the criteria: Responsibility, Attendance, Service, Cleanliness, and Loyalty. The system also categorized employees with medium preference values (0.6–0.9) and low scores (<0.4), providing actionable insights for employee development. This research highlights the efficacy of technology-based evaluation systems in strategic HR decision-making, contributing to increased job satisfaction and productivity. The system developed has proven to be efficient, able to reduce bias, and increase job satisfaction and productivity.
Gravitating the Gig Economy for Reshaping the Careers Using Technological Platform in the Digital Age in an Emerging Economy Mimi, Afsana; Mani, Lisa
Journal of Information System and Informatics Vol 6 No 4 (2024): December
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v6i4.966

Abstract

The gig economy, driven by digital platforms and technological advancements, is reshaping traditional career pathways globally, particularly in emerging economies like Bangladesh. This study explores the gig economy's impact on career development, focusing on university students and graduates in Bangladesh. Using a mixed-methods approach, including surveys and interviews with 100 gig workers, the study reveals the motivating factors, challenges, and opportunities associated with gig work. The findings reveal that 56% of graduates in Bangladesh are involved in gig economy jobs, indicating a significant shift in career pathways. Among university students, 66% engage in gig work as an alternative income source before securing fixed positions. Furthermore, 61% of respondent’s view gig jobs as a means to gain experience quickly, which they believe will benefit their future careers. Freelancing emerges as the largest segment of the gig economy, encompassing 30% of gig workers. However, the study also highlights significant challenges, including social security issues and the lack of social and institutional recognition for gig workers. This study contributes to the theoretical understanding of the gig economy in developing countries, specifically in the South Asian context. Methodologically, it provides a holistic view of the gig economy's impact on career development. The research underscores the potential of the gig economy to alleviate unemployment and foster self-reliance among youth in Bangladesh.
Challenges in IoMT Adoption in Healthcare: Focus on Ethics, Security, and Privacy Mabina, Alton; Rafifing, Neo; Seropola, Boago; Monageng, Thapelo; Majoo, Pulafela
Journal of Information System and Informatics Vol 6 No 4 (2024): December
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v6i4.960

Abstract

This study highlights ethical, security, and privacy barriers to IoMT adoption in developing countries and proposes strategies like regulatory frameworks, data encryption, AI transparency, and professional training to address these challenges. The Internet of Medical Things (IoMT) has the potential to revolutionize healthcare by enabling real-time patient monitoring, enhancing diagnostic accuracy, and supporting personalized treatments. However, significant privacy, security, and ethical challenges hinder its widespread adoption, particularly in underdeveloped nations. This study employs the PRISMA methodology to systematically review existing literature and identify key barriers to IoMT implementation in healthcare systems, with a focus on developing countries. Through a rigorous selection process, 80 studies were included in the analysis, revealing critical challenges such as inadequate data protection frameworks, ethical concerns around artificial intelligence (AI) in decision-making, and risks of patient data exploitation. The findings provide actionable recommendations for policymakers, including the establishment of robust ethical guidelines, implementation of strong security measures, and use of advanced encryption techniques. Addressing these challenges is crucial to fostering the ethical and secure adoption of IoMT, ultimately improving healthcare outcomes globally Key recommendations for IoMT adoption include the implementation of advanced encryption techniques to safeguard patient data, the establishment of clear informed consent protocols, and the development of ethical guidelines to manage AI’s role in medical decision-making, ensuring transparency and patient autonomy.
Leveraging MANETs for Healthcare Improvement in Rural Botswana Mabina, Alton; Seropola, Boago; Rafifing, Neo; Kalu, Kalu
Journal of Information System and Informatics Vol 6 No 4 (2024): December
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v6i4.968

Abstract

Rural health facilities in Botswana face significant challenges, including limited infrastructure, poor communication networks, and inadequate access to medical resources, which hinder quality healthcare delivery. This study investigates the feasibility and benefits of implementing Mobile Ad hoc Networks (MANETs) in these underserved areas. A MANET is a decentralized wireless network where devices communicate directly with each other without relying on fixed infrastructure, allowing dynamic, self-configuring connections. Key solutions proposed include integrating MANETs with solar-powered systems to ensure continuous operation, developing localized health information systems to enhance data accessibility, and implementing community training programs to build local technical capacity. Additionally, designing resilient network architectures and collaborating with local telecom providers for hybrid solutions can improve reliability and coverage. Utilizing MANETs for real-time health monitoring and emergency alerts can enhance patient outcomes and response capabilities. The real-world implementation of MANETs is expected to improve emergency response times, reduce healthcare delivery delays, and facilitate faster decision-making in critical situations. This paper highlights the potential of MANETs to address healthcare disparities between rural and urban areas by providing sustainable, scalable, and reliable communication infrastructure. Future research should focus on extensive pilot programs, empirical data collection, and exploring the integration of advanced technologies to further enhance healthcare delivery in rural Botswana. These findings aim to inform policymakers and healthcare providers on adopting MANET technology to improve rural healthcare systems.

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