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Jurnal Pilar Nusa Mandiri

pilar
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Published by STMIK Nusa Mandiri

ISSN : 19781946 EISSN : 25276514 DOI : -

Core Subject : Science,

Computer Science & IT

Jurnal Pilar merupakan jurnal ilmiah yang diterbitkan oleh program studi sistem informasi STMIK Nusa Mandiri. Jurnal ini berisi tentang karya ilmiah yang bertemakan: Rekayasa Perangkat Lunak, Sistem Pakar, Sistem Penunjang, Keputusan, Perancangan Sistem Informasi, Data Mining, Pengolahan Citra.

Arjuna Subject : -

Articles 395 Documents

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DEVELOPMENT OF RESPIRATORY SYSTEM RPG GAME USING UNITY WITH A* (A STAR) ALGORITHM Yulyanto, Yulyanto; Nugraha, Rika; Kusuma, Sigit Setya
Jurnal Pilar Nusa Mandiri Vol. 20 No. 2 (2024): Pilar Nusa Mandiri : Journal of Computing and Information System Publishing Pe
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/pilar.v20i2.5911

This research addresses the need for more engaging and interactive methods to improve elementary students' understanding of complex scientific concepts, particularly the respiratory system. To overcome the limitations of traditional teaching methods, an educational Role-Playing Game (RPG) incorporating the A* (A-Star) algorithm was developed for optimal game navigation. The study followed the ADDIE development model, which involves Analysis, Design, Development, Implementation, and Evaluation. During the analysis phase, learning needs were determined through interviews and classroom observations. The design phase involved creating game scenarios and integrating educational content with interactive elements. The A* algorithm was applied during development to ensure efficient navigation. The game was implemented in a 5th-grade classroom in Kuningan, and its effectiveness was evaluated using pre-tests, post-tests, and student questionnaires. Results demonstrated a significant increase in students' understanding, with average post-test scores rising from 58 to 85. Feedback from both students and teachers was very positive, with the game receiving a 94.2% acceptance rate. The study suggests that RPG-based educational games with intelligent algorithms like A* can greatly enhance science education by offering a more engaging and effective learning experience, contributing to advancements in technology-based learning and setting a standard for future educational game development.

VTUBER PERSONAS IN DIGITAL WAYANG: A REVIEW OF INNOVATIVE CULTURAL PROMOTION FOR INDONESIAN HERITAGE Hermawan, Hellik; Subarkah, Pungkas; Utomo, Anwar Tri; Ilham, Fatah; Saputra, Dhanar Intan Surya
Jurnal Pilar Nusa Mandiri Vol. 20 No. 2 (2024): Pilar Nusa Mandiri : Journal of Computing and Information System Publishing Pe
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/pilar.v20i2.5921

This study investigates the integration of VTuber into Wayang Digital as a strategic initiative to promote Indonesian cultural heritage. By leveraging advanced technologies such as real-time motion capture and artificial intelligence (AI), the project aims to enhance the animation quality and interaction of VTuber, creating a more immersive and engaging experience for audiences. The research focuses on three key aspects: VTuber integration's effectiveness in attracting international audiences, optimizing real-time motion capture for high-quality animation, and applying AI algorithms to create adaptive, responsive interactions between VTubers and their viewers. Through these innovations, the study aims to enrich the narrative and visual appeal of Wayang Digital, making it more accessible and appealing to a diverse global audience. The findings show that integrating advanced technologies enhances Wayang Digital's storytelling, aesthetics, and effectiveness as a powerful tool for cultural promotion. AI-enabled adaptive interactions create a personalized viewer experience, deepening audience connections with the traditional art form. High-quality animation preserves and effectively communicates Wayang's cultural nuances to audiences, enhancing its impact and cultural promotion. This study underscores the importance of continuous technological innovation and strategic implementation in the preservation and globalization of Indonesian heritage through digital media, suggesting that the future of cultural preservation lies in the seamless integration of tradition with cutting-edge technology.

EVALUATING HIGHER EDUCATION WEBSITE QUALITY USING WEBQUAL 4.0 AND IMPORTANCE PERFORMANCE ANALYSIS (IPA) Murdoko, Wiji; Jatnika, Ihsan
Jurnal Pilar Nusa Mandiri Vol. 20 No. 2 (2024): Pilar Nusa Mandiri : Journal of Computing and Information System Publishing Pe
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/pilar.v20i2.5789

LLDikti Region III is a unit operating under the Ministry of Education, Culture, Research, and Technology, responsible for promoting the enhancement of higher education quality in Jakarta. One of the media used by LLDikti Region III to serve stakeholders is through its website; therefore, the quality of services on the website must be continuously enhanced. The aim of this research is to determine whether the LLDikti Region III website meets user expectations, measured using the Webqual 4.0 method and Importance-Performance Analysis (IPA). Usability, information quality, and service interaction quality that will be used to evaluate the quality of this website. The respondents consist of members of the academic community from universities within the LLDikti Region III. Data was collected through an online questionnaire using stratified sampling techniques with 165 respondents. The results of this study show that 54.9% of the website's quality affects user satisfaction, while the remainder is influenced by variables not tested in this study. Based on the analysis conducted using the IPA method, several indicators in quadrant I still require significant attention, as they are considered important by users but have low performance. From these findings, the researcher suggests developing the website in areas where performance is low, particularly for indicators in quadrant I.

MEASURING INFORMATION TECHNOLOGY GOVERNANCE USING COBIT 2019 FRAMEWORK AT TOURISM INDUSTRY Lee, Nicholas; Wella, Wella
Jurnal Pilar Nusa Mandiri Vol. 21 No. 1 (2025): Pilar Nusa Mandiri : Journal of Computing and Information System Publishing Pe
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/pilar.v21i1.6060

Although PT XYZ has adopted information technology, it has not formally assessed its governance, leading to persistent issues in IT management, human resource capabilities, and alignment with business processes. This study evaluates IT governance at PT XYZ, a company in the travel and tourism industry, where rapid technological advancements have impacted operations. Using the COBIT 2019 framework, the study assessed IT governance through interviews and literature review, focusing on the domains APO04 – Managed Innovation, BAI02 – Managed Requirements Definition, BAI03 – Managed Solution Identification & Build, and BAI05 – Managed Organizational Change. The results indicate that these domains are at level 2, "Largely Achieved," highlighting areas of improvement. This benchmark provides practical recommendations to enhance IT governance and improve integration between IT and business functions. The findings offer PT XYZ actionable steps to strengthen governance practices, improve organizational performance, and better align technology with strategic business goals.

CONTINUOUS INTEGRATION PIPELINE WITH JENKINS Alexander, Alexander; Wella, Wella
Jurnal Pilar Nusa Mandiri Vol. 21 No. 1 (2025): Pilar Nusa Mandiri : Journal of Computing and Information System Publishing Pe
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/pilar.v21i1.6062

The advancement of technology has led to continuous improvement in application development. As a result, there is a growing demand for application software. Tech companies are constantly working on building and updating their existing applications. The development process is prolonged because to the intricate nature of the build and deployment procedures, ensuring that the application software can be accessed and utilized by individuals across the internet. To address these issues, this research aims to construct and enhance a system capable of automating the entire build and deployment process. By eliminating human intervention, potential errors and downtime that may prevent access to the deployed application can be avoided. The system was developed using the RAD or Rapid Application Development method, with the goal of simplifying and expediting the development process. A DevOps Engineer facilitates the implementation of Continuous Integration in order to reduce the duration of the entire Software Development Life Cycle (SDLC) by utilizing an open-source tool named Jenkins. This ensures that the application development process is efficient and adheres to the designated schedule, allowing all users to benefit from timely delivery.

PERFORMANCE COMPARISON OF RANDOM FOREST REGRESSION, SVR MODELS IN STOCK PRICE PREDICTION Urrochman, Maysas Yafi; Asy'ari, Hasyim; Hizham, Fadhel Akhmad
Jurnal Pilar Nusa Mandiri Vol. 21 No. 1 (2025): Pilar Nusa Mandiri : Journal of Computing and Information System Publishing Pe
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/pilar.v21i1.6072

The stock market is characterized by high volatility and complexity, making it an intriguing and challenging subject for researchers and practitioners. This study aims to predict stock prices by comparing the performance of two machine learning models: Random Forest Regression and Support Vector Regression (SVR). These models were selected for their ability to handle complex data and high volatility. The dataset used in this study consists of BNI stock data over the last five years (2019–2024), comprising a total of 1,211 data points. Testing was conducted using a cross-validation approach, and model performance was evaluated based on several metrics, including MSE, R², RMSE, MAPE, MAE, and Score. The results indicate that Random Forest Regression outperforms SVR. The model achieved an MAE of 17.766, an RMSE of 22.376, and an R² of 0.997. These findings suggest that Random Forest Regression is more effective in predicting stock prices, particularly in unstable market conditions. This study recommends Random Forest Regression as a reliable model for stock price prediction, with potential applications in other stock markets with similar characteristics.

MAPPING OF DOMESTIC AND FOREIGN TOURIST VISITS IN EAST JAVA USING THE DBSCAN METHOD Qori'atunnadyah, Marita
Jurnal Pilar Nusa Mandiri Vol. 21 No. 1 (2025): Pilar Nusa Mandiri : Journal of Computing and Information System Publishing Pe
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/pilar.v21i1.6073

Tourism is important in economic growth and regional development, especially in East Java Province with diverse tourist attractions. However, the mapping of domestic and foreign tourist visit patterns in this province is still limited. For this reason, this study uses the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) method which can group density-based data without determining the number of clusters from the beginning and handle noise. The study aims to map districts/cities in East Java based on the number of tourist visits from 2018 to 2022, using visit data from the East Java Provincial Culture and Tourism Office. The analysis results show that in domestic tourist data, with parameters MinPts = 3 and ε = 1.00, one main cluster is formed consisting of 31 tourist locations and 7 noisy locations. In foreign tourist data, with ε = 0.6 and MinPts = 3, there is one cluster with 30 tourist locations and 8 other locations are categorized as noisy. Noisy locations tend to have higher visits but do not fit into the main cluster. These findings provide important insights for more targeted tourism promotion strategies and efficient resource allocation in East Java.

GENERATION Z'S AND ANDROID OS: HOW USER EXPERIENCE, SECURITY, AND SYSTEM PERFORMANCE SHAPE SATISFACTION Murni, Cahyasari Kartika; Choiri, Achmad Firman; Hizham, Fadhel Akhmad
Jurnal Pilar Nusa Mandiri Vol. 21 No. 1 (2025): Pilar Nusa Mandiri : Journal of Computing and Information System Publishing Pe
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/pilar.v21i1.6082

This paper investigates Generation Z's opinion of the Android OS through an analysis of system performance, security, and user experience and their influence on general satisfaction. With Technology Adaptation (Z) as a mediator, the study focuses on three main factors: User Experience (X1), Security and Privacy (X2), and System Performance and Stability (X3), specifically among students who use Android devices. Data were collected through a structured questionnaire, and the analysis was conducted using the Partial Least Squares (PLS) method to evaluate the relationships between the variables. The findings reveal that, in addition to frequent updates, Generation Z's satisfaction is significantly influenced by the accessibility, performance, and security features of Android. The results highlight the importance of a positive user experience and robust security measures in enhancing user satisfaction. Continuous development in these areas is crucial for improving user engagement and contentment with Android devices.

PASSWORD STRENGTH STUDY USING THE ZXCVBN ALGORITHM AND BRUTE-FORCE TIME ESTIMATION TO STRENGTHEN CYBERSECURITY Saputra, Whisnu Yudha; Sugiarti, Sugiarti; Junianto, Haris; Suhartono, Didit
Jurnal Pilar Nusa Mandiri Vol. 21 No. 1 (2025): Pilar Nusa Mandiri : Journal of Computing and Information System Publishing Pe
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/pilar.v21i1.6119

This research analyzes password strength based on its length and complexity using brute force attack simulations. The study begins with collecting password data from various sources to ensure sufficient variation in complexity levels. Next, the passwords are evaluated using the Zxcvbn algorithm, which provides a strength score as well as information about the time required to crack them. The same passwords are also evaluated using Brute-force Time Estimation to calculate the estimated time required to crack the password. After both algorithms have been evaluated, the results are analyzed to find the correlation between the Zxcvbn score and the estimated brute force time. The results of the data analysis are then visualized in the form of graphs or diagrams to facilitate understanding and assessment of password security. This simulation estimates the time required to guess a password, depending on the level of password complexity. Although the simulation results show that long and complex passwords are more secure, the actual strength of the password is highly dependent on the tools used by the attacker. In addition, digital security is not only limited to passwords, but also depends on various loopholes that can be exploited, such as personal data leaks or software vulnerabilities. Therefore, a comprehensive security approach is essential to protect users from potential cyberattacks. This study aims to provide in-depth insights into the strength and vulnerability of passwords and the effectiveness of algorithms in assessing password security.

PREDICTING SOLAR POWER GENERATION: A MACHINE LEARNING APPROACH FOR GRID STABILITY AND EFFICIENCY Setiawati, Popong; Karno, Adhitio Satyo Bayangkari; Hastomo, Widi; Sestri, Ellya; Kasoni, Dian; Arif, Dodi; Razi, Fahrul
Jurnal Pilar Nusa Mandiri Vol. 21 No. 1 (2025): Pilar Nusa Mandiri : Journal of Computing and Information System Publishing Pe
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/pilar.v21i1.6126

In countries with high levels of insolation, the demand for renewable energy sources has driven the rapid emergence and growth of solar power plants. Maintaining grid stability and efficient power management in response to weather variations that affect solar radiation intensity and battery consumption limits remains a major challenge. This study aims to develop a machine learning-based prediction model to estimate the electricity generated by solar power plants using weather data. Four algorithms are utilized: Linear Regression, Random Forest Regressor, Decision Tree Regressor, and Gradient Boosting Regressor. The results show that the Random Forest algorithm produces the best model, with MAE and RMSE values of 0.1114281 and 0.3187232, respectively. This research contributes to the literature, particularly on the relatively unexplored topic of using multiple machine learning models to predict energy output from photovoltaic systems. The findings have the potential to inform more efficient energy policies and improve energy integration technologies for grid-connected solar power systems.

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