International Journal of Cyber and IT Service Management (IJCITSM)

Analysis of The Application Information Technology On Employee Work Productivity PT Rajendra Kesatria Perkasa Depok

Rini Septiowati — Thu, 30 Oct 2025 00:00:00 +0000

The rapid development of Information Technology (IT) has significantly influenced organizational performance, particularly in enhancing employee productivity, efficiency, and work quality. This study focuses on PT Rajendra Ksatria Perkasa in Depok with the aim of analyzing how the implementation of IT affects employee work productivity. A qualitative research design was employed through a case study approach combined with SWOT analysis, with data collected from in-depth interviews and relevant document analysis. The findings reveal that optimal utilization of IT contributes positively by increasing efficiency and strengthening team collaboration. Nevertheless, challenges remain, including the limited understanding among employees regarding effective technology use. Opportunities also arise as digital advancements provide broader access to innovation in the workplace, yet threats such as decreased focus due to uncontrolled use of technology must be anticipated. Overall, the results highlight the importance of strategic management in maximizing the benefits of IT while simultaneously addressing its potential weaknesses and risks. Furthermore, the study provides a foundation for future research on the broader implications of digitalization within organizational contexts.

Unveiling the Hidden Risks of Capital Inflows on Non-Financial Firm Performance in Indonesia

Hesti Werdaningtyas, Noer Azam Achsani, Anny Ratnawati, Tony Irawan — Mon, 22 Dec 2025 00:00:00 +0000

The limited research on the impact of external debt on financial system stability at the micro level creates a clear need for further investigation. The positive contributions to the relevant discourse of this study lie in its attempt to address that gap by conducting a comprehensive micro panel data analysis, covering the performance of 523 individual Non-Financial Corporations (NFCs) in Indonesia, based on panel data. Additionally, this study employs advanced methodology, utilising a dynamic model and System-Generalised Methods of Moments (Sys-GMM) estimation. The research have tackled endogeneity issues using GMM estimators to ensure the robustness of our findings. The results indicate that different capital flows exert varying impacts on corporate performance. In particular, private external debt inflows and Portfolio Investments (PI) have a positive influence on the financial stability of firms. Conversely, direct investment in manufacturing firms and corporate credit growth have a significant impact on corporate financial stability. From a macroprudential policy perspective, the findings highlight the importance of monitoring corporate vulnerabilities, as it may pose risks to the banking sector. These insights provide valuable guidance for policymakers in developing more effective external debt management strategies to ensure financial stability.

Predicting Professional Entrepreneurial Intention Through Core Determinants of Entrepreneurial Attitude

Sunanto Sunanto, Kasmad Kasmad, Jeni Andriani — Tue, 30 Dec 2025 00:00:00 +0000

The level of entrepreneurship among professional pharmacists is comparable to Indonesia's overall level of entrepreneurship, which is relatively low. This phenomenon is associated with entrepreneurial marketing behavior focused on Entrepreneurial Intention. For the first time in the context of professional pharmacists in Greater Jakarta, the influence of Entrepreneurial Education (EE) and Entrepreneurial Self-efficacy (ESE) on Entrepreneurial Attitude (EA) and its implications for Entrepreneurial Intention (EI) was observed using the Theory of Planned Behavior (TPB). Through proportional random sampling, 391 pharmacists were selected using the Slovin formula (5% margin of error). Confirmatory Factor Analysis (CFA) and Structural Equation Modeling (SEM) were used for quantitative analysis. The findings showed that ESE was the most powerful factor, with EE, ESE and EA all having positive and substantial direct effects on EI. The mediating effect of EA was evident in the influence of ESE on EI, but not EE. This study's novel approach lies in its consideration of the unique characteristics of healthcare entrepreneurship, which differ from general entrepreneurship due to constraints such as the complexity of the dual role. This research provides business insights to promote EI as necessity among professional pharmacists.

Digital Learning Platforms as Facilitator for University-Business Collaboration in Logistics Management Curriculum Design

Novi Indah Susanthi, Mohammad Ali, Asep Herry Hernawan — Tue, 23 Dec 2025 00:00:00 +0000

The logistics industry requires graduates who possess adaptive competencies and practical skills to respond effectively to dynamic industry demands, highlighting the importance of innovative and industry-oriented curriculum design. This study aims to analyze the implementation of a Logistics Management curriculum based on graduate competencies, with a particular focus on the application of learning strategies as a core component of the curriculum. A quantitative approach was employed using the fourth phase of Design and Development Research (DDR), which involved the experimental implementation of learning strategies in two logistics management classes following a needs analysis, competency identification, and curriculum design stages. The curriculum was developed based on five key components, competencies, learning objectives, content of materials, learning strategies, and evaluation. The results indicate that active learning approaches, including Project-based Learning (PjBL), Problem-based Learning (PBL), and Case Methods, positively support student engagement and competency development, students also reveal the need for more hands-on learning experiences, clearer instructional guidance, and stronger integration between theoretical knowledge and real-world logistics practices. This study contributes to innovation in logistics curriculum design by demonstrating how technology-enhanced active learning supported by digital learning platforms can function as enablers of industry-oriented education, strengthen university–business collaboration, and better prepare graduates for professional roles in the logistics sector.

Impact of HR Management on AI Implementation and Data Protection in Indonesian Manufacturing

Wed, 21 Jan 2026 00:00:00 +0000

This study aims to analyze the influence of Human Resource Management (HRM) strategies on the implementation of Artificial Intelligence (AI) in industrial forecasting and data protection within the cybersecurity era in Indonesian manufacturing companies. A quantitative approach was used with a survey method to collect data from 96 employees of manufacturing companies in Indonesia, determined by the Lemeshow formula. The findings show that HRM strategy has a positive and significant effect on industrial forecasting, with a t-statistic of 48.639 > 1.984 and a P-value of 0.000 < 0.05. Furthermore, HRM strategy significantly affects data protection, with a t-statistic of 27.927 > 1.984 and a P-value of 0.000 < 0.05. Industrial forecasting positively influences AI implementation, with a t-statistic of 27.927 > 1.984 and a P-value of 0.000 < 0.05, while data protection also positively affects AI implementation, supported by a t-statistic of 2.457 > 1.984 and a P-value of 0.014 < 0.05. Additionally, HRM strategy significantly influences AI implementation, with a t-statistic of 6.020 > 1.984 and a P-value of 0.000 < 0.05. Finally, HRM strategy positively impacts AI implementation through data protection, indicated by a t-statistic of 2.421 > 1.984 and a P-value of 0.016 < 0.05. In conclusion, this study highlights the importance of HRM strategies in enhancing AI implementation and cybersecurity in Indonesian manufacturing companies, underscoring the need for integrating HR strategies with AI and data protection systems to optimize operational efficiency and safeguard against cyber threats.

Improving Smear-Negative Tuberculosis Detection Using Data Augmentation and Faster R-CNN

Wed, 21 Jan 2026 00:00:00 +0000

Smear-Negative Pulmonary Tuberculosis (SNPT) remains a major diagnostic challenge due to the low bacterial load that frequently causes false negative results in sputum microscopy. Chest X-ray imaging is commonly used as a complementary diagnostic tool however its interpretation relies heavily on expert radiologists and is prone to subjectivity. Recent developments in deep learning particularly object detection models provide promising opportunities to improve diagnostic accuracy. This study aims to develop and evaluate a deep learning based approach for SNPT detection in chest X-ray images using a Faster R-CNN model with a ResNet architecture. The proposed method applies data augmentation techniques including flipping rotation scaling and random brightness adjustment to enhance training data diversity and reduce overfitting. The model was implemented using PyTorch and evaluated using accuracy precision recall and F1 score. Experimental results indicate that data augmentation substantially improves performance achieving 76.60% accuracy and 68.57% F1 score compared to 53.06% accuracy and 51.06% F1 score without augmentation. Improved recall reflects higher sensitivity in detecting SNPT cases. These findings indicate that data augmentation enhances the robustness and generalization of Faster R-CNN models for SNPT detection and supports the potential of AI assisted diagnostic systems in tuberculosis screening programs.

International Journal of Cyber ​​and IT Service Management (IJCITSM)

Analysis of The Application Information Technology On Employee Work Productivity PT Rajendra Kesatria Perkasa Depok

Unveiling the Hidden Risks of Capital Inflows on Non-Financial Firm Performance in Indonesia

Predicting Professional Entrepreneurial Intention Through Core Determinants of Entrepreneurial Attitude

Digital Learning Platforms as Facilitator for University-Business Collaboration in Logistics Management Curriculum Design

Impact of HR Management on AI Implementation and Data Protection in Indonesian Manufacturing

Improving Smear-Negative Tuberculosis Detection Using Data Augmentation and Faster R-CNN

International Journal of Cyber and IT Service Management (IJCITSM)