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Teknika
Published by Institut Informatika Indonesia Surabaya
ISSN : 25498037     EISSN : 25498045     DOI : https://doi.org/10.34148/teknika
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering Engineering
Teknika is a peer-reviewed journal dedicated to disseminate research articles in Information and Communication Technology (ICT) area. Researchers, lecturers, students, or practitioners are welcomed to submit paper which has topic below: Computer Networks Computer Security Artificial Intelligence Machine Learning Human Computer Interaction Computer Vision Virtual/Augmented Reality Digital Image Processing Data Mining Web Mining Computer Architecture Software Engineering Decision Support System Information System Audit Business Information System Datawarehouse & OLAP And any other topics relevant with Information and Communication Technology (ICT) area
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 276 Documents
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Comparison of The Accuracy of K-Nearest Neighbor and Roberta Algorithm in Analysis of Sentiment on Miawaug Youtube Channel Comments Rahmawan, Fachrudin Okta; Hanafi; Dhuita, Windha Mega Pradnya
Teknika Vol. 14 No. 1 (2025): March 2025
Publisher : Center for Research and Community Service, Institut Informatika Indonesia (IKADO) Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34148/teknika.v14i1.1117

Abstract

This study aims to evaluate the accuracy of two algorithms, K-Nearest Neighbor (KNN) and Robustly Optimized BERT Approach (RoBERTa), in analyzing sentiment within comments on MiawAug’s YouTube channel. Sentiment analysis was conducted on two sentiment categories: binary classification (positive and negative) and multi-class classification (positive, neutral, and negative). Using KNN, the binary classification yielded an accuracy of 86.12%, F1-score of 87.44%, recall of 96.64%, and precision of 79.89%. In contrast, the multi-class classification achieved 98.21% accuracy, F1-score, and recall with a precision of 98.23%. However, the RoBERTa model outperformed KNN, achieving 93.89% accuracy, 93.88% F1-score, 94.59% recall, and 93.22% precision in binary classification. For multi-class classification, RoBERTa further excelled, attaining 99.21% across accuracy, F1-score, recall, and precision. These findings demonstrate that RoBERTa surpasses KNN in sentiment analysis, especially in multi-class contexts, indicating its greater robustness for this application.
Implementation and Analysis of Container Image Optimization Using Alpine Linux and Multi-Stage Builds Fachrudin, Mochamad Rizal; Affandi, Arif Saivul
Teknika Vol. 14 No. 1 (2025): March 2025
Publisher : Center for Research and Community Service, Institut Informatika Indonesia (IKADO) Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34148/teknika.v14i1.1118

Abstract

Containerization enables isolation within a host, with Docker being a popular tool for packaging applications and their dependencies in container images. However, challenges like slow build processes and bloated image sizes can consume resources, slow down builds, and pose security risks. This study optimizes Docker images by combining the Alpine base image with multi-stage builds, analyzing size, build speed, and security across different combinations and environments to identify and propose the most efficient combination solution. The approach used is a quantitative quasi-experiment with a within-subject design. The sample used was a JavaScript framework, with the main experimental group being the combination of Alpine and multi-stage builds, while the comparison group included combinations of Node and Node-Alpine, both in single-stage and multi-stage configurations, as well as single-stage Alpine. Data was obtained from CI/CD, container registry, and Trivy reports. Analyzed by descriptive analysis, One-Way ANOVA or Kruskal Wallis test, and post-hoc test. The results show that combining multi-stage builds with Alpine is considered best practice because it produces the smallest image size, reducing it by up to 94% compared to single-stage Node. It also achieves the shortest build times across all environments and presents low vulnerability issues. However, it is important to note that while the Alpine multi-stage combination offers the most efficient build times, it experiences a 1.3x increase in duration in low-spec environments.
User Experience Analysis of ShopeeFood Service Using Google's HEART Framework Oktarina, Felicia; Handoyo, Emanuel Ristian; Rahayu, Flourensia Sapty
Teknika Vol. 14 No. 1 (2025): March 2025
Publisher : Center for Research and Community Service, Institut Informatika Indonesia (IKADO) Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34148/teknika.v14i1.1141

Abstract

The proliferation of online food delivery services has intensified the importance of user experience (UX) in determining business success. Since its launch in Indonesia in 2021, ShopeeFood, integrated within the Shopee application, has been competing with established players like GoFood, necessitating a comprehensive understanding of its user experience factors. This study employed Google's HEART Framework to evaluate the user experience of ShopeeFood through a goals-signals-metrics process, encompassing five key variables: Happiness, Engagement, Adoption, Retention, and Task Success. A mixed-method approach was implemented, combining quantitative data collection through questionnaires (n=100) with qualitative insights from user interviews, establishing a minimum target threshold of 70% for each measured variable. Statistical analysis revealed that most HEART variables demonstrated mean values falling within the "high" to "very high" categories; however, a notable exception was observed in the Retention variable, which failed to meet the predetermined minimum threshold of 70%. The findings indicate positive user reception of ShopeeFood across multiple experience dimensions, while highlighting specific challenges in user retention. To address these challenges, the study suggests implementing targeted retention strategies such as loyalty programs and enhanced user engagement initiatives. These strategies aim to transition users from promotion-driven engagement to value-based loyalty, thereby improving long-term user retention and solidifying ShopeeFood's competitive position in the market.
Security Testing of XYZ Website Application Using ISSAF and OWASP WSTG v4.2 Methods Yusuf, Muhammad Firdaus; Hikmah, Ira Rosianal; Amiruddin; Sunaringtyas, Septia Ulfa
Teknika Vol. 14 No. 1 (2025): March 2025
Publisher : Center for Research and Community Service, Institut Informatika Indonesia (IKADO) Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34148/teknika.v14i1.1156

Abstract

The research focuses on improving the security of information systems in ABC City, specifically on the XYZ website application developed by the Communication and Informatics Office ABC to assist in governmental administration and manage various critical data. This study is motivated by the high incidence of cybersecurity threats in the governmental administration sector, as reported by Badan Siber dan Sandi Negara in November 2023. The primary objective of this research is to identify security vulnerabilities within the XYZ website application. The research employs the Information Systems Security Assessment Framework (ISSAF) as the primary security testing framework and the OWASP Web Security Testing Guide (WSTG) version 4.2 as the guide for the penetration testing phase, one of the stages in ISSAF for validating vulnerabilities. Validated vulnerabilities are further assessed for severity using the OWASP Risk Rating guidelines to estimate the risk and impact of potential attacks on the Communication and Informatics Office ABC. The research methodology uses a black-box testing approach. To ensure a structured approach, it provides security recommendations using the SMAACT method. This research includes a report on the identified vulnerabilities and recommendations that the Communication and Informatics Office ABC can implement to address these vulnerabilities. The findings of this study are expected to provide insights into existing security vulnerabilities within the website application and practical recommendations for improvement, benefiting both the practical context of enhancing information security at the Communication and Informatics Office ABC and the theoretical context as a reference for similar future research.
Implementation of Machine Learning Model to Detect Sign Language Movement in SIBI Learning Media Fitriani, Leni; Kurniadi, Dede; Rajab, Ilham Syahidatul
Teknika Vol. 14 No. 1 (2025): March 2025
Publisher : Center for Research and Community Service, Institut Informatika Indonesia (IKADO) Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34148/teknika.v14i1.1159

Abstract

This research focuses on the development of a web-based Indonesian Sign Language System (SIBI) learning application with motion detection to improve the precision of sign language practice. Despite the government's introduction of SIBI as an official system, existing platforms lack tools to validate the accuracy of hand movements. Using the Design Sprint methodology—comprising Understand, Define, Sketch, Decide, Prototype, and Validate phases—this study employs Microsoft Azure Machine Learning to create a motion detection model capable of recognizing SIBI gestures. The application offers an interactive learning experience, allowing users to practice and receive real-time feedback on their accuracy. Initial trials demonstrated high prediction accuracy, achieving 99.82% on public datasets and 96.4% on private datasets. Beta testing revealed an 86% satisfaction rate among users, indicating the application’s effectiveness in enhancing the learning process. By providing accessibility through standard web browsers and incorporating advanced motion detection, this application contributes to inclusivity, facilitating broader public understanding and interest in learning sign language.
Factors Influencing Continuance Intention to Play Online Games Keraf, Boniface Boliona Badilangoe; Pramana, Edwin; Gunawan
Teknika Vol. 14 No. 1 (2025): March 2025
Publisher : Center for Research and Community Service, Institut Informatika Indonesia (IKADO) Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34148/teknika.v14i1.1163

Abstract

This study aims to identify and analyze the factors influencing continuance intention in playing online games, a rapidly growing global entertainment sector that attracts players from diverse backgrounds. Using the Expectation Confirmation Model (ECM), this research explores the psychological and behavioral aspects that drive players to continue playing. To achieve this objective, data were collected through a survey using Google Forms distributed to schools, colleges, and social media. A total of 505 active player responses were collected, and 469 valid data entries were retained after screening. The analysis was conducted using Structural Equation Modeling (SEM) with SPSS and AMOS software to identify the impact of each factor. The results from SPSS and AMOS calculations showed that Flow was not significant, and Engagement was excluded due to failing the validity test. These findings help developers and policymakers better understand player motivations to create more effective strategies for building a sustainable gaming industry. The study found that Social Influence had the greatest impact on continuance intention. Players were more likely to continue playing if the game was popular in their environment or had a large market. This factor fosters a sense of community and social support among players, from friends, family, and communities who play the same game. Perceived Usefulness and Perceived Enjoyment followed, contributing significantly as well.
Understanding Student Sentiment Towards Informatics Engineering: Strategies to Attract High School and Vocational Graduates Bau, Rahmat Taufik R. L.; A, Hermila; Latief, Mukhlisulfatih
Teknika Vol. 14 No. 1 (2025): March 2025
Publisher : Center for Research and Community Service, Institut Informatika Indonesia (IKADO) Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34148/teknika.v14i1.1165

Abstract

Higher education plays a crucial role in shaping the future of the younger generation, and in the ever-evolving digital era, technology has become an integral part of the education process. Amid the ongoing digital transformation, students’ interest in the Informatics Engineering major is increasing; however, challenges remain in attracting high school (SMA) and vocational school (SMK) students to pursue this field. This research aims to provide a deeper understanding of students' sentiments toward the Informatics Engineering major and to formulate an effective promotional strategy to encourage high school and vocational school graduates to choose this path. To achieve these objectives, the research employs the TextBlob classification method, a natural language processing tool that assigns sentiment polarity scores (positive, neutral, or negative) to textual data. Sentiment analysis was conducted on responses collected through questionnaires, involving number of high school and vocational school students. The results of the sentiment analysis for high school (SMA) students reveal that out of 209 data points, 93 tweets (44.5%) were categorized as positive sentiment, citing career prospects and academic opportunities as key motivators. In contrast, For vocational school (SMK) students, among 135 data points analyzed, 50 tweets (37.0%) were categorized as positive sentiment, prioritizing practical skills and industry readiness. Based on the findings, the study formulates targeted promotional strategies. For SMA students, the focus should be on showcasing career prospects, technical skill development, and success stories in the tech industry. For SMK students, the promotion should emphasize practical, hands-on skills, industry partnerships, and job-readiness. This research provides recommendations for tailored promotional approaches to enhance students’ awareness and interest in Informatics Engineering, thereby encouraging greater enrollment in the field.
The Impact and Challenges of Parak Acil Online in Banjarmasin’s E-Government Transformation Teguh, Devi Anastaia Budiawaty; Kristanto, Budi
Teknika Vol. 14 No. 1 (2025): March 2025
Publisher : Center for Research and Community Service, Institut Informatika Indonesia (IKADO) Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34148/teknika.v14i1.1172

Abstract

The rapid development of information and communication technology (ICT) in the Industrial 4.0 era has transformed governance globally, including in Indonesia, where e-government initiatives are a national priority. This study examines the implementation and impact of Parak Acil Online, a digital platform introduced by the Population and Civil Registration Office (Disdukcapil) in Banjarmasin, aimed at streamlining public service delivery for population documents such as e-KTP, family cards, and birth certificates. The research employs a qualitative approach, guided by the E-GovQual and Delone & McLean IS Success models, to evaluate the platform’s performance across six dimensions: Ease of Use, Trust, Functionality of Interaction Environment, Reliability, Content and Appearance, and Citizen Support. Findings reveal that Parak Acil Online significantly enhances service accessibility, transparency, and efficiency. However, challenges persist, including digital literacy gaps, infrastructure limitations, and system performance issues, such as delays and occasional crashes during peak usage. Respondents highlighted the need for improved accessibility features, real-time support tools, and enhanced backend optimization. This study contributes by providing a comprehensive evaluation framework and actionable insights for optimizing e-government platforms in developing regions. By addressing these challenges, Parak Acil Online can achieve sustainable digital transformation and serve as a benchmark for equitable public service delivery in Indonesia and beyond.
Enhancing Image Quality in Facial Recognition Systems with GAN-Based Reconstruction Techniques Wijaya, Beni; Satyawan, Arief Suryadi; Haqiqi, Mokh. Mirza Etnisa; Susilawati, Helfy; Artemysia, Khaulyca Arva; Sopian, Sani Moch.; Shamie, M. Ikbal; Firman
Teknika Vol. 14 No. 1 (2025): March 2025
Publisher : Center for Research and Community Service, Institut Informatika Indonesia (IKADO) Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34148/teknika.v14i1.1180

Abstract

Facial recognition systems are pivotal in modern applications such as security, healthcare, and public services, where accurate identification is crucial. However, environmental factors, transmission errors, or deliberate obfuscations often degrade facial image quality, leading to misidentification and service disruptions. This study employs Generative Adversarial Networks (GANs) to address these challenges by reconstructing corrupted or occluded facial images with high fidelity. The proposed methodology integrates advanced GAN architectures, multi-scale feature extraction, and contextual loss functions to enhance reconstruction quality. Six experimental modifications to the GAN model were implemented, incorporating additional residual blocks, enhanced loss functions combining adversarial, perceptual, and reconstruction losses, and skip connections for improved spatial consistency. Extensive testing was conducted using Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index (SSIM) to quantify reconstruction quality, alongside face detection validation using SFace. The final model achieved an average PSNR of 26.93 and an average SSIM of 0.90, with confidence levels exceeding 0.55 in face detection tests, demonstrating its ability to preserve identity and structural integrity under challenging conditions, including occlusion and noise.  The results highlight that advanced GAN-based methods effectively restore degraded facial images, ensuring accurate face detection and robust identity preservation. This research provides a significant contribution to facial image processing, offering practical solutions for applications requiring high-quality image reconstruction and reliable facial recognition.
Ancient Javanese Manuscript Reconstruction Using Generative Adversarial Network with StarGAN v2 Variations Wibowo, Kukuh Cokro; Damayanti, Fitri; Abdilqoyyim, Fanky
Teknika Vol. 14 No. 1 (2025): March 2025
Publisher : Center for Research and Community Service, Institut Informatika Indonesia (IKADO) Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34148/teknika.v14i1.1182

Abstract

Ancient Javanese manuscripts are part of Indonesia's cultural heritage; most of them are usually in bad condition due to the age and environmental surroundings. This paper presents a manuscript reconstruction using the Generative Adversarial Network model, using the variation of StarGAN v2. The primary objective of this research is to assist philologists in reconstructing damaged manuscripts more efficiently, reducing the time and effort compared to manual reconstruction methods. The training for 100 epochs is performed by the model in order to generate the reconstruction image closest to ground truth. This study is done on a dataset that consists of a set of damaged manuscript images. In this dataset, 80% is for training, 20% is for validation, and 10 images are used for testing. Quality assessment will be made on image outputs during training, based on PSNR, SSIM, and LPIPS metrics. The results indicate that the PSNR increases from 16.1234 dB at the 50th epoch to 17.5588 dB at the 100th epoch, while the SSIM increases from 0.8374 to 0.8519, showing a strong improvement in image quality. Despite the LPIPS having a very slight increase from 0.1020 to 0.1051, this evidences that the model can be further improved. Overall, this study demonstrates that the StarGAN v2 model is effective in reconstructing ancient Javanese manuscripts-a great contribution to the field of cultural heritage preservation using modern technology.

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