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INDONESIA
Indonesian Journal of Information System
Published by Universitas Atma Jaya Yogyakarta
ISSN : 26230119     EISSN : 26232308     DOI : -
Core Subject : Science,
Computer Science & IT
Arjuna Subject : -
Articles 192 Documents
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Workplace Hazard Identification through Near-Miss Reports: A Social Network Analysis Anggraini , Dita Putri; Ambarwati, Rita; Dedy, Dedy; Toirxonovna, Alimova Mashhura
Indonesian Journal of Information Systems Vol. 7 No. 1 (2024): August 2024
Publisher : Program Studi Sistem Informasi Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijis.v7i1.8891

Abstract

Occupational Safety and Health (OHS) is an effort to create a safe and healthy working environment. The company, which is engaged in power generation, experienced many near-miss cases from 2016 to 2023. Near-miss incidents are an early signal of the potential for severe accidents in the future if not resolved immediately. Identifying and addressing potential hazards early is necessary to prevent fatal work accidents. This study aims to analyze the reporting pattern of near-miss incidents by company employees through the IZAT application (Zero et al.) with a social network analysis (SNA) approach. This method identifies relationships and interaction patterns between employees in reporting near-miss incidents, thus revealing objects that need special attention. Data was obtained from September 2020 to July 2023. The analysis showed that 276 employees actively reported various near-miss incidents through IZAT (Zero Accident Assistant Application). This pattern reflects employees' sensitivity to potential hazards in their work environment. The findings of this study make a positive contribution to the improvement of the occupational safety and health management system in the company regarding the mitigation of potential hazards based on incoming report data. The recommendations provided are related to occupational safety aspects that need to be prioritized for management improvement. The implication of this research is to increase employee awareness in identifying and reporting potential hazards so as to prevent work accidents in the future.
A Comparative Tale of Peer-to-Peer, Client-to-Peer and Hybrid Networks in Federated Social Networking Sites in Educational Institutions Mugoniwa, Beauty; Ngassam, Ernest Ketcha; Singh, Shawren
Indonesian Journal of Information Systems Vol. 7 No. 1 (2024): August 2024
Publisher : Program Studi Sistem Informasi Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijis.v7i1.9025

Abstract

Due to increase in use of social networking sites(SNSs) in educational institutions, it has become common for institutions to adopt SNSs in academic institutions. Federated social networking sites(FSNSs) are powerful decentralisation platforms for educational activities. Qualitative scientific thorough review of relevant literature from multiple databases and qualitative survey from experts for Hybrid FSNS validation purposes. Peer-to-peer, client-to-server and hybrid networks present an excellent way of decentralising SNSs, however institution may need to scrutinise underlying functional and non-functional capabilities of each network architecture in order to come up with best platform for their institutions. Contemporary education need eLearning models that addresses critical needs for more effective and scalable educational solutions that can leverage benefits of SNSs while overcoming their limitations. Stakeholders should be able to make an informed decision as to which network to employ in their FSNSs, so that they can benefit from platforms’ specific educational opportunities.
Enhancing Eye Health Diagnosis through Deep Transfer Learning: Unveiling Insights from Low Quality Fundus Images S. Pariselvam; Kumar, Sathish; M. Govindarajan; R. Keerthivasan; I. Srivathsan
Indonesian Journal of Information Systems Vol. 7 No. 2 (2025): February 2025
Publisher : Program Studi Sistem Informasi Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijis.v7i2.9103

Abstract

Due to the frequency of eye illnesses, effective and precise diagnostic instruments are required. This work suggests an approach that uses low quality fundus images with deep transfer learning more precisely, the EfficientNetB0 architecture to improve eye health diagnosis. We tackle the problem caused by the quality of fundus photographs that are commonly found in clinical settings, which frequently display noise and abnormalities. Our methodology consists of pretraining the EfficientNetB0 model on a sizable dataset of excellent fundus photos, followed by fine-tuning it on a dataset of poor fundus photos. By employing this transfer learning technique, the model enhances its diagnostic capabilities by learning to identify significant features from the low-quality images. We ran tests on a variety of datasets that included fundus photos of varying degrees of deterioration in order to assess our approach. As compared to conventional techniques, the results reveal a significant improvement in diagnostic accuracy, demonstrating the effectiveness of deep transfer learning for improving eye health diagnosis from difficult fundus images. With fused features from MobileNet and DenseNet-121 models, the ANN specifically achieved accuracies of 98.5% for cataracts, 99.1% for diabetic retinopathy, 99% for glaucoma, and 99.5% for normal conditions.
IT Risk Management Analysis Based on ISO 31000 and Bow Tie Analysis (BTA) in Higher Education Institution Prasetyo, Beny; Salsabila, Aura; Yulia Retnani, Windi Eka
Indonesian Journal of Information Systems Vol. 7 No. 1 (2024): August 2024
Publisher : Program Studi Sistem Informasi Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijis.v7i1.9673

Abstract

The Division of Applications and Software is a part of the Academic Support Unit (UPA) for Information and Communication Technology at Universitas Jember (UNEJ) or UPA TIK UNEJ. Based on interviews, UPA TIK UNEJ has not yet implemented risk management, leading to recurring issues in their IT services. Risk management is crucial for preventing and mitigating negative impacts that can harm the organization. Additionally, it is a requirement for internal quality management system audits, according to UNEJ Rector's Decision Number 20588/UN25/LL/2018. This study aims to identify, analyze, and assess potential risks in the Division of Applications and Software at UPA TIK UNEJ and to apply Bow Tie Analysis (BTA) to identify preventive and mitigative actions for the highest-rated risks. The approach used is ISO 31000:2018, which provides a comprehensive framework for risk management. For in-depth risk analysis, the BTA method, combining event tree analysis (ETA) and fault tree analysis (FTA), is utilized. The research begins with context establishment through interviews, followed by risk identification, analysis, assessment, and mitigation. The results show 21 risks identified in the process of developing information systems or applications. The top three priority risks are coded R02, R04, and R19. The second priority includes 17 risks, and the third priority includes 1 risk.
A Case Study: The Secondary Students Overall Satisfaction on Online Learning MOHD, SITI MUNIRAH; Mohamad Jan, Nurhidaya; Mohd Idris, Fadzidah; Kaco, Hatika; Kamarudin, Shafinah
Indonesian Journal of Information Systems Vol. 7 No. 1 (2024): August 2024
Publisher : Program Studi Sistem Informasi Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijis.v7i1.9719

Abstract

Online learning has revolutionized education by offering a flexible platform that transcends geographical boundaries and time constraints. It provides various multimedia resources, interactive exercises, and personalized feedback, enhancing the learning experience. However, online classes have challenges, such as decreased student engagement, technical issues, and a lack of structure, leading to procrastination and decreased productivity. This research aims to delve into the level of satisfaction experienced by talented high school students in terms of their virtual classroom experience. The study was conducted through an online survey using purposive and convenient sampling techniques. The data analysis showed that most students expressed satisfaction with the online classes, indicating that they found them informative, engaging, and meaningful. However, a few minor adjustments could be made to enhance students' experience, such as more opportunities for interactive participation, additional resources, and more precise instructions. Overall, the research highlights the positive impact of online education on the learning experience of gifted high school students.
Importance IT Role of IT Self-Efficacy towards Actual Competency, IT Usage, and Productivity: A Case Study on University Students Susanto, Tony Dwi; Assani, Saffana; Caroline Chan
Indonesian Journal of Information Systems Vol. 7 No. 2 (2025): February 2025
Publisher : Program Studi Sistem Informasi Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijis.v7i2.10044

Abstract

Teaching how to use technology and encouraging students to improve their learning productivity by using technology are challenging. This study aims to investigate the important role of IT self-efficacy towards IT actual competency, actual usage of IT, and productivity in the case of university students to propose a teaching strategy that can improve students’ competency from “know-what” to “know-how” continued to real usage and productivity. It produces a model of the relationships between IT self-efficacy, IT actual competency, actual usage of information technology, and productivity. The relationships were quantitively measured using data from 89 students. The construct validity of the measurement model was examined using convergent and discriminant validity analysis. The hypothesized model was tested using structural equation modeling and bootstrap analysis. The findings suggest that IT self-efficacy does not directly impact actual usage and productivity. Still, it directly affects IT actual competency, leading to actual usage and productivity. In terms of novelty, this study examines a comprehensive relationship between 4 variables: IT self-efficacy, IT actual competency, IT usage, and Productivity, while the other existing studies just examined the relationships between 2 variables: IT self-efficacy and IT actual competency, IT self-efficacy and attitude towards IT usage, IT self-efficacy and IT Usage. For practical contributions, this study highlights the importance of improving students’ IT self-efficacy as an initial strategy to motivate students to use technology in their learning process which can lead to improved productivity.
Application Of Expert System In Determining Diseases In Potato Plants Ikhwan, Ali; Bi Rahmani , Nur Ahmadi; H. Aly, Moustafa; Aslami, Nuri; Dedi Irawan, Muhammad; Ahmad, Imam
Indonesian Journal of Information Systems Vol. 7 No. 2 (2025): February 2025
Publisher : Program Studi Sistem Informasi Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijis.v7i2.10213

Abstract

This research aims to develop an expert system in diagnosing diseases in potato plants using the Case Based Reasoning (CBR) method approach combined with the K-Nearest Neighbor (K-NN) algorithm. The system is designed to help farmers identify the type of disease based on the symptoms that appear, as well as provide relevant solutions to increase crop productivity. In previous research, the CBR method showed a limited accuracy rate of 74% because it only relied on one algorithm. Through the application of two methods in data analysis, namely CBR and K-NN, this study succeeded in increasing the diagnosis accuracy to be higher than the previous approach of 80%. The system is implemented in the form of a web-based application that is easily accessible by farmers. The results show that the integration of these two methods provides more optimal, effective, and accurate results in detecting potato plant diseases based on symptom data. The findings are expected to contribute significantly to the development of agricultural technology, especially in improving the harvest success of potato farmers in Indonesia.
Improved Banking Customer Retention Prediction Based on Advanced Machine Learning Models Linda Wahyu Widianti; Adhitio Satyo Bayangkari Karno; Hastomo, Widi; Aryo Nur Utomo; Dodi Arif; Indra Sari Kusuma Wardhana; Deon Strydom
Indonesian Journal of Information Systems Vol. 7 No. 2 (2025): February 2025
Publisher : Program Studi Sistem Informasi Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijis.v7i2.10364

Abstract

The quick growth of the banking sector is reflected in the rise in the number of banks. In addition to the intense competition among banks for new customers, efforts to keep existing ones are essential to minimizing potential losses for the company. To ascertain whether customers will leave the bank or remain customers, this study will employ churn forecasts. A 1,750,036-customer demographic dataset, which includes data on bank customers who have left or are still customers, is used in the training process to compare five machine learning technology models in order to investigate the improvement of binary classification prediction accuracy. These models are Decision Tree, Random Forest, Gradient Boost, Cat Boost, and Light Gradient Boosting Machine (LGBM). According to the study's results, LGBM performs better than the other four models since it has the highest recall and accuracy and the fewest False Negatives. The LGBM model's corresponding accuracy, precision, recall, f1 score, and AUC are 0.8789, 0.8978, 0.8553, 0.8758, and 0.9694. This demonstrates that, in comparison to traditional methods, machine learning optimization can produce notable advantages in churn risk classification. This study offers compelling proof that sophisticated machine learning modeling can revolutionize banking industry client retention management.
An exploration of students' cyber threats perception in the digital age Donald Mothisi; Mujinga, Mathias
Indonesian Journal of Information Systems Vol. 7 No. 2 (2025): February 2025
Publisher : Program Studi Sistem Informasi Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijis.v7i2.10424

Abstract

This study aims to investigate cyber threat awareness among students from a rural-based university and propose a model to enhance their awareness. Students rely on information and communication technologies (ICTs) for educational and personal activities. Students in rural areas may have less cybersecurity education and awareness than their urban counterparts. This can affect their awareness of malware, social engineering, and other cyber threats. It also heightens the challenges students face in mitigating security breaches. Data was collected using a survey to assess students' awareness of cyber threats. This assisted in determining students' knowledge, attitude, and behaviour (KAB) when engaged in online activities. The results indicated that less than 20 per cent of the students are aware of threats like Trojan horses, phishing, and keyloggers. The limited awareness of these threats could negatively impact students' ability to protect their information resources. It is recommended that rural-based students are continuously made aware of cyber threats. This study proposes the student online threat awareness model (SOTAM) to enhance cyber threat awareness among students.
Chargeback as an ICT Cost Reduction Strategy Ajufo, George
Indonesian Journal of Information Systems Vol. 7 No. 2 (2025): February 2025
Publisher : Program Studi Sistem Informasi Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijis.v7i2.10554

Abstract

A leading financial institution in Nigeria, hereinafter referred to as "the Bank," has deployed Information and Communications Technology (ICT) systems to drive the Bank's strategy and operations with significant success, albeit with massive investments. However, despite the benefits derived, there have been concerns, especially with the dwindling revenues of the Bank, that the ever-increasing cost of ICT could become unsustainable. These concerns have led the Bank's management to request the ICT Department to find ways of reducing costs. This study investigated the adoption of ICT chargeback to reduce ICT costs in the Bank without impacting ICT service quality. The study utilized variables identified by prior researchers on ICT chargeback. Data was gathered from the Bank's staff using online surveys. The findings from the analysis of data provided sufficient evidence to support the assertion that ICT chargeback adoption would lead to ICT cost reduction in the Bank, consistent with the results of previous studies. The study also indicated that chargeback adoption would facilitate decision-making and more responsible usage of ICT infrastructure in the Bank. However, the study also found some negative consequences which would result from its adoption. For instance, the study showed that ICT Chargeback would discourage innovation due to cost consciousness and foster an unhealthy relationship between ICT and the business. In conclusion, the study recommended the adoption of ICT chargeback with the caveat that the negative consequences identified should be minimized to ensure that they do not vitiate the gains from the adoption.

Page 19 of 20 | Total Record : 192

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