cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Raymond Sutjiadi, S.T., M.Kom
Contact Email
p3m@ikado.ac.id
Phone
+62317346375
Journal Mail Official
p3m@ikado.ac.id
Editorial Address
Pattimura No. 3 Kelurahan Sonokwijenan Kecamatan Sukomanunggal Kota Surabaya 60189
Location
Kota surabaya,
Jawa timur
INDONESIA
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
 24   25   26   27   28 
Classification of Foods Based on Nutritional Content Using K-Means and DBSCAN Clustering Methods Nurulhikmah, Fitria; Abdi, Deden Nur Eka
Teknika Vol. 13 No. 3 (2024): November 2024
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.v13i3.1067

Abstract

This study classifies foods based on their nutritional content using K-Means and DBSCAN clustering methods. The clustering quality was evaluated using the Davies-Bouldin Index (DBI) and Silhouette Score. K-Means was tested with different k values, while DBSCAN was analyzed with varying min_samples parameters. Additionally, a function was developed to group foods into three categories: Weight Gain, Obesity Prevention, and Weight Loss, based on calories, protein, fat, and carbohydrate content. The results show that K-Means is more effective than DBSCAN in clustering foods by nutritional content, yielding lower DBI values and higher Silhouette Scores. For example, K-Means with k = 3 achieved a DBI of 0.694930 and a Silhouette Score of 0.538921, while DBSCAN with eps = 0.75 and min_samples = 4 produced a DBI of 0.34546577 and a Silhouette Score of 0.492830814. This study concludes that K-Means provides superior clustering performance, enabling more specific dietary recommendations tailored to individual nutritional needs.
The Role of Information and Communication Technology in Advancing Sustainable Energy Transition in Developing Countries: Progress, Opportunities and Challenges Tanoto, Yusak
Teknika Vol. 13 No. 3 (2024): November 2024
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.v13i3.1068

Abstract

Sustainable energy transitions in developing countries are critical for balancing economic growth and environmental sustainability. Transitioning to renewable energy sources alleviates energy poverty and reduces reliance on fossil fuels. Information and communication technology (ICT) plays an important role in advancing the energy transition and achieving low-carbon energy utilization by facilitating the transition of power sectors to renewable energy sources. This paper provides an overview of the role of ICT in achieving sustainable energy transition in developing countries and jurisdictions. It emphasises the significance of SDG 7 and other sustainable energy transition indices for energy access and transition, as well as presenting their status and progress in various regions, including developing countries. This paper also discusses several types of available ICT tools and methods that enable digitalization in the power sector, such as smart grids, smart metres, energy management systems, Internet of Things (IoT) for energy, and renewable energy monitoring systems, as well as the opportunities and challenges of incorporating ICT into the context of developing countries' sustainable power sector.
Coloring Pekalongan Batik Using a Madura Dataset: A Comparative Study of GAN and Caffe-Based CNN Models Wahyudi, Muhamad Machrus Ali; Kurniawati, Arik; Damayanti, Fitri; Purnawan, I Ketut Adi
Teknika Vol. 13 No. 3 (2024): November 2024
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.v13i3.1071

Abstract

Madura Batik, as one of Indonesia's valuable cultural heritages, is known for its unique characteristics involving the use of bright colors such as red, yellow, and green, as well as traditional motifs that often feature elements of nature like flowers, leaves, and animals. Each motif in Madura Batik reflects the rich philosophy, values, and stories of Madura culture. This batik is also famous for its production process, which is largely carried out manually using traditional dyeing techniques. However, with the advancement of technology, there is a growing need to integrate technological innovations into the batik dyeing process without losing its traditional essence. This research combines Generative Adversarial Networks (GAN) models and compares them with Caffe-based pretrained Convolutional Neural Networks (CNN) to create new color variations in Pekalongan batik images. The input for the models is grayscale batik images, which are then processed to generate colorful outputs. The dataset used consists of 519 Madura batik images, with a distribution of 80% for training, 20% for validation, and 10 images for testing. The preprocessing process includes resizing, normalization, and batching to accelerate model convergence. Performance evaluation is conducted using FID, MSE, PSNR, and SSIM metrics. The results show that the GAN model with 100 epochs produces better image quality compared to the Caffe-based pretrained CNN model, particularly in terms of visual and structural similarity. In conclusion, the GAN method offers great potential for innovation in batik coloring without compromising its traditional motifs.
Classification of Student Learning Styles Using Artificial Neural Networks on Imbalanced Data Baharuddin, Fikri; Fajrin, Ahmad Miftah; Handani, Felix
Teknika Vol. 13 No. 3 (2024): November 2024
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.v13i3.1075

Abstract

The transformation of learning activities towards digital form since the COVID-19 pandemic can affect students' learning process. One of the factors that can affect this learning process is the learning style owned by each student. Learning patterns that are not in line with students' learning styles can influence their learning process. This study aims to identify students' learning styles based on data extracted from the Moodle Learning Management System (LMS). The research methods applied in this study include data collection by extracting data from Moodle LMS logs and classifying student learning styles using the Artificial Neural Network (ANN) algorithm. This study uses 310 log extraction data on the Moodle platform. The Isolation Forest algorithm was applied to this study to detect anomalies or outliers in the dataset. The data used in this study also has an unbalanced distribution of data per class. To prevent the performance degradation of the classifier model caused by the imbalance of data distribution, this study uses the SMOTE algorithm which can generate new synthetic data on minority class. This study combines three algorithms consisting of the Isolation Forest Algorithm for dataset management, the SMOTE Algorithm to solve the problem of data imbalance, and the ANN Algorithm to build a classification model. The model evaluation is carried out by considering the values of accuracy, precision, recall, and F1-Score to identify the reliability level of the produced model. Based on the research, this study produced a classifying model with an accuracy of 96%. The model produced in this study can be used to identify students' learning styles and as a reference for improving the quality of the teaching and learning process.
The Role of UTAUT2 in Understanding Technology Adoption: A Study of the Merdeka Mengajar Platform Among Indonesian Teachers Aminah, Siti; Aditya, Addin; Kanthi, Yekti Asmoro
Teknika Vol. 13 No. 3 (2024): November 2024
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.v13i3.1082

Abstract

This research investigates the adoption of the Merdeka Mengajar application using the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) framework. The study aims to identify the factors influencing teachers' behavioral intentions and usage behavior regarding this educational technology platform. A total of 383 teachers from various levels in Malang were sampled from a broader population of 8,936. Statistical analysis uses SEM (Structural Equation Modelling) analysis techniques. The findings suggest that performance expectancy, effort expectancy, social influence, hedonic motivation, and price value significantly influence behavioral intention. However, facilitating conditions and habit do not show a direct significant impact on use behavior. These results indicate that while technological support such as infrastructure and internet access is necessary, it alone may not be enough to motivate consistent usage without internal factors like perceived usefulness or enjoyment of the app. Moreover, the habitual use of new technology may require additional support and time before it can significantly affect behavior. This study contributes valuable insights into the adoption of educational technologies, especially in the Indonesian context, where digital learning platforms are increasingly being integrated into teaching practices. Future research may explore how ongoing support and user experience improvements can further enhance the app's adoption.
Perancangan Aplikasi Mobile Menggunakan Machine Learning Untuk Menentukan Klasifikasi Kategori Berita Hariyanti, Novi Tri; Rahmawati, Titasari; Wirapraja, Alexander
Teknika Vol. 13 No. 3 (2024): November 2024
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.v13i3.1093

Abstract

Berita yang umumnya terdapat pada media publikasi baik elektronik maupun media cetak yang beredar setiap harinya dalam volume yang besar, saat ini sebagian besar telah berpindah ke media digital yang memudahkan pengguna untuk mengakses artikel berita. Jumlah peredaran berita yang besar setiap harinya inilah yang seringkali membebani kerja dari editor dan penulis berita dalam menentukan kategori dari berita yang akan dirilis. Sistem ini dirancang untuk membantu dalam melakukan klasifikasi kategori berita, pada aplikasi ini aplikasi dirancang dalam bentuk aplikasi portal berita berbasis aplikasi mobil berbasis android. Pada penelitian ini menggunakan metode logistic regression sebagai metode klasifikasi biner dengan dataset yang digunakan pada penelitian ini merupakan judul berita yang dipublikasikan pada tahun 2020 dengan pembagian data sekitar 2000 dataset. Hasil dari penelitian ini adalah sistem aplikasi yang membantu dalam melakukan klasifikasi kategori berita dengan tingkat akurasi diatas 85%.
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.

Page 26 of 28 | Total Record : 276

 24   25   26   27   28 

Filter by Year

2012 2025


Reset
Filter By Issues
All Issue Vol. 14 No. 1 (2025): March 2025 Vol. 13 No. 3 (2024): November 2024 Vol 13 No 2 (2024): Juli 2024 Vol 13 No 1 (2024): Maret 2024 Vol 12 No 3 (2023): November 2023 Vol 12 No 2 (2023): Juli 2023 Vol 12 No 1 (2023): Maret 2023 Vol 11 No 3 (2022): November 2022 Vol 11 No 2 (2022): Juli 2022 Vol 11 No 1 (2022): Maret 2022 Vol 10 No 3 (2021): November 2021 Vol 10 No 2 (2021): Juli 2021 Vol 10 No 1 (2021): Maret 2021 Vol 9 No 2 (2020): November 2020 Vol 9 No 1 (2020): Juli 2020 Vol 8 No 2 (2019): November 2019 Vol 8 No 1 (2019): Juli 2019 Vol 7 No 2 (2018): November 2018 Vol 7 No 1 (2018): Juli 2018 Vol 6 No 1 (2017): November 2017 Vol 5 No 1 (2016): November 2016 Vol 4 No 1 (2015): November 2015 Vol 3 No 1 (2014): Juli 2014 Vol 2 No 1 (2013): Juli 2013 Vol 1 No 1 (2012): Juli 2012 More Issue