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All Journal International Journal of Electrical and Computer Engineering Pixel : Jurnal Ilmiah Komputer Grafis Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Teknologi Informasi dan Komunikasi Journal of Technology Informatics and Engineering Scientific Journal of Informatics International Journal of Graphic Design
Wibowo, Mars Caroline
Universitas Sains Dan Teknologi Komputer
Arts Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Mechanical Engineering

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Utilizing phpMyAdmin for System Design in Enterprise Administration Wibowo, Mars Caroline; Wijanarko Adi Putra, Toni
Journal of Technology Informatics and Engineering Vol 3 No 2 (2024): Agustus : Journal of Technology Informatics and Engineering
Publisher : University of Science and Computer Technology

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/jtie.v3i2.193

Abstract

In today's digital landscape, effective data management is essential for organizations, particularly small and medium-sized enterprises (SMEs) that often struggle with traditional manual methods, leading to inefficiencies and data inaccuracies. This research aims to investigate the implementation of phpMyAdmin, a web-based database management tool, to enhance administrative systems within SMEs. The study employs a mixed-methods approach, integrating qualitative case studies and quantitative surveys to gather comprehensive insights into user experiences and operational performance. The findings reveal that the adoption of phpMyAdmin significantly improves data management efficiency, with 75% of respondents expressing satisfaction with its user-friendly interface. However, challenges such as security vulnerabilities and the necessity for user training were also identified, indicating that while phpMyAdmin offers substantial benefits, organizations must address these issues to fully leverage their capabilities. The implications of this research suggest that SMEs should prioritize investing in user training and implementing robust security measures to mitigate risks associated with data management. By doing so, organizations can enhance their operational efficiency and decision-making processes. Future research should focus on the long-term impacts of phpMyAdmin and explore its integration with other management systems to further optimize organizational performance.
Characterization Of Composition Error Summary Using Machine Learning Techniques And Natural Language Processing Mars Caroline Wibowo; Budi Raharjo
Pixel :Jurnal Ilmiah Komputer Grafis Vol 16 No 1 (2023): Vol 16 No 1 (2023): Jurnal Ilmiah Komputer Grafis
Publisher : UNIVERSITAS STEKOM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/pixel.v16i1.1885

Abstract

As software technology becomes more complex, software maintenance costs become more expensive. In connection with this, the development of software engineering makes the software system has many Composition choices that can be adjusted to the needs of the user. Error fixing involves analyzing Error Summary and modifying code. If bug-fixing steps are made as efficiently and effectively as possible then maintenance costs can be minimal. The purpose of this research is to establish a tool of machine learning for identifying Composition Error Summary and to find out the types of special Composition choices that can be used to save costs, time, and effort. In this study, the T-test was applied to appraise the analytical implication of conduct metrics when the “F-test” was taken to the Variance’s test. Classifiers used in this study are “All words” or “AW”, “Highly Informative Words” or “H-IW”, and “Highly Informative Words plus Bigram” or “H-WB”. Identical validation and Vexed validation techniques were used to calculate the effectiveness of machine learning tools. The results of this research denote that the instrument is competent for definitive Composition Error Summary and other Composition choices for definite Error Summary. This research determines the practicality of machine learning techniques in corrective issues relevant to Error summary. The result of this study also explained that Composition/non-Composition Error Summaries have contrasting aspects that can be accomplished by machine learning devices. The advanced tool could be upgraded in some areas to create it more powerful. The array identification section of the current study has limitations, an array with different words and Composition recognition tools tend to prefer Compositions with more words, so improvements to this could implicate consideration of the semantics of Error Summary, equivalent, and use of n-grams. Also, in using the technology of machine learning and Natural Language processing some advancements to be made to the present characterization structure so for future research it is highly recommended to clear up the first’s Error Summary before operating several operations in the present study.Composition Error Summary
Aesthetic Photography Analysis on Instagram: A Visual Study of Social Media using ATLAS.ti Wibowo, Mars Caroline; Purnomo, Hindriyanto Dwi; Hartomo, Kristoko Dwi; Sembiring, Irwan
Scientific Journal of Informatics Vol. 11 No. 4: November 2024
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v11i4.13985

Abstract

Purpose: This study aims to analyze the dominant trends in color and composition within aesthetic photography on Instagram and explore their influence on user interaction, specifically likes and comments. Given the growing role of visual aesthetics in digital marketing, understanding these elements is crucial for content creators, brands, and businesses aiming to maximize engagement. Unlike previous studies that focus on general social media engagement, this research integrates technology-driven qualitative analysis using ATLAS.ti, enabling structured coding and thematic identification of visual elements. Methods: A qualitative content analysis was conducted on 591 Instagram posts tagged with #AestheticPhotography and #VisualAesthetic. Data was collected using Instagram scraping (PhantomBuster), extracting both visual (color palettes, composition techniques) and textual (captions, metadata) elements. The ATLAS.ti software was used to analyze recurring visual patterns and color extraction was performed via Google Colab and Python for accuracy. Result: The results show that natural colors (48.18%) and pastel tones (30.90%) are dominant in aesthetic photography, contributing to higher engagement due to their harmonious and calming effect. Composition techniques such as center alignment (40.51%) and the Rule of Thirds (23.27%) significantly correlate with user interaction, as they align with cognitive load theory and visual perception principles. Additionally, short captions (≤10 words) were more effective in enhancing engagement, receiving 8,876 likes and 4,432 comments on average, compared to longer captions. Novelty: This study bridges the gap between visual aesthetics and computational analysis, using ATLAS.ti to systematically examine social media trends. Unlike previous studies that focus solely on quantitative metrics, this research provides qualitative insights into how color and composition influence engagement. The findings offer practical guidance for content creators, designers, and marketers, suggesting that strong visual composition and color harmony can enhance audience engagement.
Design and Implementation of Animated Stickers as an Educational Tool for Adolescent Drug Awareness Using the MDLC Method Nugroho, Aris Sarwo; Wibowo, Mars Caroline
International Journal of Graphic Design Vol. 2 No. 2 (2024): IJGD : International Journal of Graphic Design
Publisher : University of Science and Computer Technology

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/ijgd.v2i2.2114

Abstract

This study aims to design and implement animated stickers as an educational medium for drug abuse prevention using the Multimedia Development Life Cycle (MDLC) method. The MDLC process includes six phases: concept, design, material collection, development, testing, and distribution. In the concept phase, the educational goals and target audience are defined. The design phase involves creating visual sketches and animations using Adobe animate. In the material collection phase, relevant information about drug abuse is gathered from trusted sources. During the development phase, the animated stickers are created, incorporating visual and textual elements to convey anti-drug messages. The testing phase evaluates the effectiveness of the stickers using a survey of 100 adolescents aged 13-18 years. The results show a significant increase in understanding of drug abuse, with a 48% improvement in comprehension after exposure to the animated stickers, as measured by a Likert scale survey. The effectiveness was primarily evaluated based on user feedback regarding visual appeal, message clarity, and motivation to avoid drugs. The final phase involves distributing the animated stickers through social media platforms and messaging apps, targeting a broader audience. This study demonstrates that animated stickers are a highly effective tool for increasing drug awareness among young people
The Influence of Minimalist Design Elements on Visual Preferences of Generation Z: A Quantitative Study Wibowo, Mars Caroline; Zainudin, Ahmad; Sugiarto, Sugiarto
International Journal of Graphic Design Vol. 2 No. 2 (2024): IJGD : International Journal of Graphic Design
Publisher : University of Science and Computer Technology

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/ijgd.v2i2.2133

Abstract

Minimalist design has become a dominant trend across various visual media, from digital advertising to mobile applications. Generation Z, as digital natives with high exposure to visual content, exhibits unique preferences toward minimalist design. However, limited research has focused on identifying which elements of minimalist design most influence their visual preferences. This study aims to analyze the impact of key minimalist design elements—white space, simple typography, neutral colors, and layout—on the visual preferences of Generation Z. A quantitative approach was adopted using a survey-based methodology. The study involved 200 respondents from Generation Z in Indonesia, selected through purposive sampling. The research instrument was a questionnaire employing a 5-point Likert scale to measure preferences for each minimalist design element. The collected data were analyzed using descriptive statistics and regression analysis to identify the most influential elements. The findings reveal that white space is the most influential element for Generation Z, with an average score of 4.3 and a regression coefficient of 0.45 (p < 0.01). Neutral colors and simple typography also show significant impacts, with coefficients of 0.32 (p < 0.05) and 0.28 (p < 0.05), respectively. Conversely, layout demonstrated the least influence, with a coefficient of 0.15 (p > 0.05). These results confirm that Generation Z favors clean, simple, and focused designs that effectively use white space and calming color palettes. This study contributes to the graphic design literature by offering insights into the visual preferences of Generation Z. Practically, the findings provide actionable guidelines for graphic designers to create more effective digital campaigns targeting young audiences. Future research is recommended to explore cross-cultural variations in visual preferences and the role of specific media platforms in shaping these preferences.
Deep Learning-Based Visualization of Network Threat Patterns Using GAN-Generated Infographic Wibowo, Mars Caroline; Setyawan, Iwan; Setiawan, Adi; Sembiring, Irwan
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 9 No 4 (2025): August 2025
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v9i4.6717

Abstract

Despite the growing sophistication of cyberattacks, current network traffic analysis tools often lack intuitive visual support, limiting human analysts’ ability to interpret complex threat behaviors. To address this gap, this study proposes a novel deep learning-based visualization framework using a Deep Convolutional Generative Adversarial Network (DCGAN) to synthesize threat-specific infographics from structured numerical features in the CICIDS 2017 dataset. Unlike conventional methods, such as PCA or static dashboards, which often result in abstract or non-adaptive visuals, our approach generates class-distinct grayscale images that preserve the behavioral patterns of various attacks, including denial-of-service, brute force, and port scanning. The preprocessing pipeline reshapes the selected flow-based features into 28×28 matrices to train the generative model. Evaluation using the Frechet Inception Distance (FID) yielded a score of 28.4, whereas a CNN classifier trained on the generated images achieved 91.2% accuracy, confirming visual fidelity and semantic integrity. Additionally, a panel of human experts rated the interpretability of the generated images at 4.3 out of 5.0. These findings demonstrate that generative visualization can enhance human-centered threat analysis by bridging raw data with interpretable imagery, thereby offering a scalable and explainable approach for integrating AI into real-time security workflows.
5G NETWORK TRAFFIC FORECASTING USING MACHINE LEARNING Budi Raharjo; Mars Caroline Wibowo
JURNAL TEKNOLOGI INFORMASI DAN KOMUNIKASI Vol. 13 No. 2 (2022): September
Publisher : UNIVERSITAS STEKOM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/jtikp.v13i2.850

Abstract

The idea of network chunks being described as virtual subsets of the physical resources of 5G infrastructure is used in standards for 5G communications. The efficiency of ML predictors for traffic prediction in 5G networks has been established in recent research so that it becomes to assess the capability demands of each network slice and to see how it progresses as a large number of network slices are deployed over a 5G network over time to be very important. The main objective of this research is to establish the model that has the potential to help network management and resource allocation in 5G networks with machine learning performance analysis in predicting network traffic on high-dimensional spatial-temporal cellular data, in addition to investigating the effectiveness of various neural network models in traffic prediction from univariate and multivariate perspectives. The research method used is a quantitative research method using correlation analysis, statistical analysis, and distribution analysis on the temporal and spatiotemporal frameworks developed to predict traffic from a univariate and multivariate perspective. To predict 24-hour mobile traffic requires combining spatial and temporal dependencies. The univariate analysis will be carried out by applying a temporal framework that includes FCSN, 1DCNN, SSLSTM and ARLSTM to capture temporal dependencies. The results of various experiments in this study show that the proposed spatiotemporal model outperforms the temporal model and other techniques in the mobile traffic forecasting literature including internet, SMS, and calls.
THREAT ATTRIBUTES HANGING IN THE WILD ANDROID Irda Yunianto; Mars Caroline Wibowo; Budi Raharjo
Journal of Technology Informatics and Engineering Vol. 1 No. 3 (2022): December: Journal of Technology Informatics and Engineering
Publisher : University of Science and Computer Technology

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/jtie.v1i3.150

Abstract

Android is a complicated system that applications and component are usable and support for multiple work together, giving rise to highly complex interdependence relationships. Meanwhile, the Android environment is notable for being greatlty disparate and decentralized: different Operation System version is personalized and re-personalized by different parties about fast and used by whoever that can develop an application for that version. Android secure its explanation sources over an app sandbox and permissions model, where each application execution in this part can entrance only suspectible overall assets and another application component (value providers, services, activities, publication receivers) by the appropriate liscense. This study uses Harehunter measurement to automatically detect Hare vulnerabilities in Android system applications. Harehunter and HareGuard performance evaluations were carried out in this study, both of which proved to be highly effective. The approach used here is divergent investigation, by searching all quoted, decompiled script, and obvious data for targeted attribute determination as an initial step, and running an XML parser. The outcome of this research show that the impact of Hares is very significant. The application of HareGuard in this study proved to be effective in detecting all attack applications that were made. Further evaluation of the performance impact on the minimum system host. For future research, to make Harehunter more effective, it is suggested to use a more qualified analyzer. So that this direction can be explored in more depth.
Empowering Urban Farmers: An Asynchronous Learning Application for Greenhouse Management Wibowo, Mars Caroline; Santoso, Joseph Teguh
Journal of Technology Informatics and Engineering Vol. 3 No. 2 (2024): Agustus : Journal of Technology Informatics and Engineering
Publisher : University of Science and Computer Technology

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/jtie.v3i2.185

Abstract

This paper addresses the growing need for effective educational tools in greenhouse gardening, particularly for beginners lacking prior agricultural knowledge. Despite the increasing availability of mobile applications aimed at agricultural education, many existing resources fail to engage users through interactive experiences, thereby limiting their practical skill development. This study identifies a significant knowledge gap regarding the specific needs of novice gardeners and the effectiveness of current educational applications. To address this gap, we developed an innovative mobile application designed to facilitate asynchronous learning through interactive features such as discussion forums and quizzes. A mixed-methods approach was employed, involving user testing with 30 participants to evaluate the application’s usability and engagement levels. The results indicated that 90% of users found the application intuitive and easy to navigate, with enhanced motivation attributed to its engaging visual design. These findings suggest that the proposed application not only meets the educational needs of users but also fosters a more interactive and responsive learning environment. The implications of this research highlight the potential for mobile applications to significantly improve practical knowledge and skills in greenhouse management, ultimately contributing to more sustainable agricultural practices
Reliability of Arduino Serial Communication Systems: A Case Study on the Application of Cyclic Redundancy Check (CRC) Raharjo, Budi; Wibowo, Mars Caroline
Journal of Technology Informatics and Engineering Vol. 3 No. 2 (2024): Agustus : Journal of Technology Informatics and Engineering
Publisher : University of Science and Computer Technology

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/jtie.v3i2.186

Abstract

In embedded systems, serial communication plays a crucial role in data transfer, particularly in Arduino-based projects. However, factors such as electromagnetic interference, noise, and signal degradation can compromise data integrity, leading to significant errors. Effective error detection systems are essential to ensure reliable data exchange. The Cyclic Redundancy Check (CRC) is one such method known for its ability to detect errors. Despite its potential, the practical application and impact of CRC on Arduino communication systems have not been extensively explored. This study implements CRC within Arduino serial communication by designing and developing software that integrates CRC for real-time error detection. The study rigorously tests this implementation in various scenarios to evaluate its performance, comparing data integrity with and without CRC. The results show that incorporating CRC significantly improves the reliability of data transmission in Arduino applications, enhancing error detection accuracy. This improvement strengthens existing systems and provides a solid foundation for developing more complex communication frameworks. The research advances reliable communication systems in embedded technologies. By demonstrating CRC's effectiveness in enhancing data integrity, the study offers valuable insights for developers and researchers seeking to improve serial communication across different applications.
Co-Authors Adi Setiawan Ahmad Zainudin Andik Prakasa Hadi Ayyub Hamdanu Budi Nurmana Mulyana Slamet Budi Raharjo Budi Raharjo Budi Raharjo Budi Raharjo Hindriyanto Dwi Purnomo Irda Yunianto Irda Yunianto Irwan Sembiring Iwan Setyawan Joseph Teguh Santoso Kristoko Dwi Hartomo Mufadhol Nugroho, Aris Sarwo Santoso, Joseph Teguh Sugiarto S Suryani Suryani Suwadi Suwadi Suwadi Suwadi Toni Wijanarko Adi Putra