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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 20 Documents
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Search results for , issue "Vol. 14 No. 1 (2025): March 2025" : 20 Documents clear
Development of Interactive Learning Application for Basic Programming Based on Technological Pedagogical Content Knowledge Framework Soetjipto, Daniel Yulius; Dinata, Hendra; Angga, Melissa; Widjaja, Jovan Adriel
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.v14i1.1084

Abstract

Information technology students must take Algorithms and Programming. Research shows that 28% of US students fail their basic programming subject, which is essential to mastering programming. In line with the previous study, 39% of students in the Informatics Engineering department’s basic programming course at campus X in the odd semester of 2022/2023 failed the course. The learning process should be able to integrate technology into it. An interactive learning application was developed utilizing the Technological Pedagogical and Content Knowledge (TPACK) framework, incorporating a pedagogical paradigm in its design through simulation elements and animated visuals. Through an extensive design, this learning application enhances student engagement by 78.3%, encouraging continued utilization in their educational process. The trial involving the group of students utilizing this application revealed that 5 out of 34 students failed the course, in contrast to 7 out of 33 students from the group that studied without the application.
Single Sign-On (SSO) Implementation Using Keycloak, RADIUS, LDAP, and PacketFence for Network Access Andjarwirawan, Justinus
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.v14i1.1089

Abstract

The increasing demand for secure, seamless authentication mechanisms in public and private networks has fueled the need for more robust network access control (NAC) systems, as well as Single Sign-On (SSO) which is critical for organizations that require seamless and secure access across different platforms. This paper explores SSO in a fully open source implementations with Keycloak, RADIUS and LDAP; extending to captive portal implementations with PacketFence for Wi-Fi authentication. Specifically, this paper highlights the integration of PacketFence with FreeRADIUS for captive portal authentication, leveraging Keycloak for identity management and providing users with secure Wi-Fi access. Real-world examples, such as authenticating campus network users over Wi-Fi with 802.1X and captive portals, illustrate how these systems work in tandem to provide scalable and secure network access control. Testing showed up to 500 concurrent users with stable performance, minimal latency at a case study university. Key performance metrics included response times below 30ms.
LyFy: Enhancing Batik E-Commerce Live Streaming Through Real-Time Chat Filtering and Product Recommendation Oktian, Yustus Eko; Setiawan, Eugene Abigail; Wiradinata, Trianggoro; Maryati, Indra; Soekamto, Yosua Setyawan
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.v14i1.1104

Abstract

Live streaming has emerged as an essential tool for e-commerce, allowing sellers to engage with potential customers in real-time. However, the massive influx of comments during these sessions often includes a mix of useful product-related queries and irrelevant or distracting messages, which can overwhelm the presenter and reduce the effectiveness of the stream. In this paper, we propose LyFy, a browser-based extension designed to filter live chat messages and provide personalized product recommendations in real-time, specifically applied in Batik e-commerce to support the preservation and promotion of this unique cultural heritage of Indonesia. Our system uses a combination of natural language processing (NLP) and machine learning models to identify relevant comments, group similar queries, and offer product suggestions based on viewers' interests. We demonstrate the effectiveness of this system through a prototype implementation and evaluate its performance with qualitative feedback from streamers and users. The evaluation results indicate high user satisfaction, with over 51% of respondents rating LyFy as highly effective and 52% as highly efficient, making it a valuable tool for enhancing e-commerce live streaming interactions.
Optimization of MSMEs Clustering in Sampang District Using K-Medoids Method and Silhouette Coefficient Method Firmansyah, Muhammad Iqbal; Kustiyahningsih, Yeni; Rahmanita, Eza; Abidin, Mochammad Syahrul; Satoto, Budi Dwi
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.v14i1.1116

Abstract

Micro, Small, and Medium Enterprises (MSMEs) are an important sector in the economy, playing a significant role in creating jobs and driving local economic growth. This study aims to identify the business development patterns of MSMEs in Sampang District using the K-Medoids method. The background issue raised is the lack of appropriate segmentation for MSMEs, which complicates the efforts of the government and business actors in designing suitable development strategies. The dataset used consists of 1,276 MSME data points with six variables: Type of Business, Number of Workers, Production Capacity, Revenue, Assets, and Business License. The data processing steps include data conversion, one-hot encoding, and normalization to ensure uniformity. Clustering is performed using the Elbow method to determine the optimal number of clusters, with K=4 chosen as the optimal cluster number based on the highest Silhouette Coefficient value of 0.5662 compared to other K values. The Silhouette Coefficient values for K=2 are 0.3711, K=5 is 0.5389, K=7 is 0.5201, and K=9 is 0.4737. The clustering results show that this cluster encompasses various types of services, trade, to food and beverages sectors. This segmentation can support data-driven decision-making at the village level. Although this research shows promising results, it is recommended to expand the quantity and variety of data and consider external factors affecting MSME performance. Thus, this study makes a valuable contribution to understanding the business characteristics of MSMEs in Sampang District.
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.

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