JSAI (Journal Scientific and Applied Informatics)

Analysis of AI-Based Software Development (Gemini) Using ACM Code of Ethics Implementation

2025-02-05T09:41:04+08:00

This research aims to analyze the application of the ACM Code of Ethics in the development of AI Gemini software by Google DeepMind. With the development of artificial intelligence (AI) technology, developers need to pay attention to ethical aspects in every stage of system development. This research uses a qualitative approach with a data triangulation method, which includes document analysis, interviews with AI experts, and a literature study. The results show that although Gemini AI has complied with some key ethical principles in the ACM Code of Ethics, such as data security and privacy (90%) and human well-being (85%), there are still challenges related to transparency (60%) and bias mitigation (70%). Lack of transparency in algorithms and training data as well as potential bias in results generated by AI are the main issues that need to be improved. Based on the results, overall the Gemini AI has shown fairly good ethical compliance with an average of 76.67% but still requires improvement in the aspects of transparency, bias mitigation, and usage regulation.

Optimizing Network Management with Bandwidth Limitation and Blocking Certain Access at PT Laxo Global Access by Applying the NDLC Method

2025-05-01T17:57:49+08:00

This research focuses on optimizing network management at PT Laxo Global Akses by implementing bandwidth restrictions and restricting access to non-work related websites and applications. Internet usage in the company was previously unrestricted, resulting in decreased productivity and unstable network performance, especially during peak hours. To address these issues, this research applies the Network Development Life Cycle (NDLC) methodology and utilizes MikroTik devices for configuration. Key features such as Queue Tree for bandwidth distribution, Firewall Filtering for access control, and Hotspot User Management for user authentication were implemented. The redesigned network topology allows for more structured traffic management and real-time monitoring. The test results show that all test scenarios have succeeded as expected, so it can be concluded that the network configuration and policies implemented in the NDLC process were 100% successful at the implementation and testing stages.

Analysis of Maturity Alignment of Business Strategy with Information Technology at SAMSAT Bengkulu City Using Strategic Alignment Maturity Model (SAMM)

2025-05-02T09:54:50+08:00

Motor vehicle tax payments represent a substantial portion of regional income. However, recurrent delays in motorbike tax payments, notably in the Kandang Limun sub-district of Bengkulu City, pose a significant threat to regional development. This research aims to address these delays by predicting and implementing effective strategies. Using the RapidMiner application and the Artificial Neural Network (ANN) method, a delay rate of 36.14% was predicted. The study incorporates interviews to propose several strategies, including enhancing websites, improving offline and online services, implementing Drivethru services, and using SMS Blast notifications to combat delays. To evaluate the feasibility of these strategies, the research employs the Strategy Alignment Maturity Model (SAMM). The assessment at BPKD reveals a maturity level of 4, signifying an ability to improve and manage processes effectively.The maturity assessment suggests that the proposed strategies for overcoming delays are well-aligned with BPKD's capabilities. They have demonstrated a robust alignment between IT and business strategies, leveraging IT to enhance performance, and conducting thorough business and IT evaluations.In addition to the maturity assessment, the research offers suggestions and evaluation strategies. These encompass the adoption of biometrics for authentication, implementation of chatbots, Samsat self-service kiosks, real-time vehicle monitoring, and the introduction of automatic tax programs.

Implementation of NLP Election News Classification Using LSTM Algorithm

2025-05-16T08:56:36+08:00

This study examined the application of a Long Short-Term Memory (LSTM)-based text classification method to categorize election news according to presidential and vice-presidential candidate entities. The core problem addressed was the lack of an automated classification system capable of identifying political affiliations directly within the vast volume of digital news content. In this research, news data were collected from open-access sources and automatically labeled based on the occurrence of candidate-related keywords. A supervised learning approach was implemented using the LSTM architecture to capture sequential patterns within the news text. The evaluation results demonstrated that the model achieved a validation accuracy of 95.44% and a macro-averaged F1-score of 0.95, indicating strong classification performance across all candidate categories. Furthermore, predictions on test data revealed the model’s consistency and stability in recognizing political entities. This study confirmed the effectiveness of the LSTM-based approach for entity-based election news classification and highlighted its potential for integration into automated media analytics and political discourse monitoring systems.

Implementation of Agile Scrum Method and Return On Investment (ROI) Analysis on Library Information System

2025-05-16T09:09:10+08:00

The library is one of the important institutions that provide and manage information to support learning, teaching, and research activities. In its development, the need for an integrated and efficient library information system is increasing, along with the demands of digitizing services and managing data quickly and accurately. This research aims to implement the Agile Scrum method in the development of Library Information Systems and conduct a return-on-investment (ROI) analysis to measure the effectiveness of the investment from a business and economic perspective. Based on the research problem raised and the results of the research that has been conducted, it shows that the Scrum method is proven to be effective in increasing flexibility and responsiveness to user needs. Key features are completed on time, and user feedback can be responded to in the next sprint. Active collaboration minimizes the risk of errors and maintains system quality. The first-year ROI is positive although small (4.65%), but the system is sustainable, so the ROI will increase significantly in years 2 and 3 because costs remain low while benefits continue to grow.

Analysis of Archer.exe Malware to Identify Potential Threats on Operating Systems Using the Hybrid Analysis Method

2025-05-26T09:12:20+08:00

Cybersecurity has become a primary concern in the digital era, particularly regarding malware attacks targeting the Windows operating system. This study aims to analyze a Remote Access Trojan (RAT)-type malware named archer.exe, obtained from the Any.run platform. The method used is hybrid analysis, a combination of static analysis and dynamic analysis, to provide a comprehensive understanding of the malware's structure and behavior. Static analysis results show that archer.exe is a Portable Executable (PE) file with a size of 829.35 KB and employs packing techniques to conceal its payload. Meanwhile, dynamic analysis reveals that the malware modifies system registry keys, spawns child processes such as rundll32.exe and cmd.exe, and establishes a network connection to a Command and Control (C2) server at IP address 192.169.69.26 via the domain dominoduck2101.duckdns.org. These findings indicate that archer.exe poses a high risk of remote system access, data theft, and malicious background activity without user awareness. This study demonstrates that the hybrid analysis method is effective in identifying hidden threats and malicious behavior of RAT-type malware on Windows 10 systems.

Analysis of Canva and Gamma User Satisfaction Among Students Using the System Usability Scale (SUS) Method

2025-05-16T09:08:40+08:00

Canva and Gamma are web-based graphic design platforms widely used by students to create brochure, presentations, and social media content in a simple and efficient way. The purpose of this study is to evaluate user satisfaction. with both applications using the System Usability Scale (SUS) method. The study involved 100 students from Universitas Muhammadiyah Bengkulu who had used both platforms. The results indicate that Canva achieved a SUS score of 80.2, categorized as Excellent, while Gamma received an average score of 72.4, categorized as OK. These findings suggest that although both applications demonstrate good usability, Canva is perceived to be superior in terms of ease of use, feature integration, and learning curve. The outcomes of this study can serve as a reference for’s developers with educational institutions on selecting or developing design tools that are more responsive to user needs.