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PENENTUAN AREA WAJAH MENGGUNAKAN ALGORITMA VIOLA-JONES UNTUK APLIKASI MANIPULASI WARNA CITRA DIGITAL Rainhard, Rainhard; Mulyana, Teady Matius Surya
Jurnal Algoritma, Logika dan Komputasi Vol 8, No 1 (2025): Jurnal ALU, Maret 2025
Publisher : Universitas Bunda Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30813/j-alu.v8i1.8152

Nowadays, many smartphones have a high-resolution camera module thus giving them ability to take photo and store it as digital image, with enormous size and dimension. Capturing photo with smartphone is also getting more common and some of the photo contain a subject of human face.The Objective of this research is to implementing the Viola-Jones Object Detection Algorithm to a colour manipulation application for digital image that has been produced by smartphone. Object Detection is a branch of Computer Vision that used to detect the presence of an object using feature or template. In this research, Viola-Jones will be used for detecting the presence of human face on a digital image. The Result of this research is that the Viola-Jones Object Detection Algorithm can be implemented to the digital image colour manipulation application. This application can detect the presence of human face on the digital image.The Conclusion of this research is that Viola-Jones algorithm is able to detect the presence of human face on the smartphone-produced digital image with 93% detection accuracy, based on the ratio of the total amount of face detected by the total amount of real face presence. Proven with the testing of 20 types of digital image with one face, and many faces.

Desain User Experience (UX) Pada Website Smart City untuk Meningkatkan Aksesibilitas Layanan Publik Wijaya, Agustinus Fritz; Surya Mulyana, Teady Matius; Liunard, Garren Janico
Jurnal Teknologi dan Manajemen Industri Terapan Vol. 4 No. 2 (2025): Jurnal Teknologi dan Manajemen Industri Terapan
Publisher : Yayasan Inovasi Kemajuan Intelektual

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55826/jtmit.v4i2.582

Perkembangan konsep smart city menuntut pemerintah untuk menyediakan layanan publik yang tidak hanya efisien dan terintegrasi, tetapi juga inklusif dan mudah diakses oleh seluruh lapisan masyarakat. Penelitian ini bertujuan merancang dan mengevaluasi desain user experience (UX) pada website smart city guna meningkatkan aksesibilitas digital, khususnya bagi kelompok rentan seperti penyandang disabilitas dan lansia. Pendekatan Human-Centered Design (HCD) dan standar Web Content Accessibility Guidelines (WCAG 2.1) diintegrasikan dalam proses perancangan. Metode penelitian meliputi observasi, studi literatur, wawancara, penyebaran kuesioner, serta evaluasi heuristik dan usability testing terhadap prototipe website. Hasil pengujian menggunakan System Usability Scale (SUS) menunjukkan skor rata-rata 86,4 (kategori “Excellent”), dengan mayoritas pengguna dapat mengakses fitur utama dalam waktu kurang dari dua menit. Elemen UX seperti navigasi intuitif, kontras warna tinggi, kompatibilitas screen reader, dan desain responsif terbukti meningkatkan kenyamanan dan efektivitas interaksi pengguna. Penelitian ini memberikan kontribusi praktis dan teoretis dalam pengembangan website smart city yang inklusif dan berorientasi pada pengguna, serta mendorong transformasi digital layanan publik yang berkelanjutan.

Menentukan Aksi Lawan Komputer Pada Game Strategi Menggunakan Algoritma K-Nearest Neighbour Michael Freddy; Teady Matius Surya Mulyana
Jurnal Teknik Informatika dan Sistem Informasi Vol 8 No 3 (2022): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v8i3.5137

Advances in computer technology allow various devices to complete complex computing, especially in the entertainment industry and the biggest example is games. Strategy game is the type of game that most often gets an Artificial Intelligence or AI system implemented to imitate human behaviour when playing games. Many game AI systems are predictable so players get bored quickly, so adaptive and simple AI is needed to make it easier for game developers. K-Nearest Neighbour is a classification algorithm with supervised learning, this algorithm will be used in this study. The research method tests the level of accuracy in determining the class by providing a sample of data which is divided into training data and test data. The measure of the level of accuracy is calculated using the confusion matrix after the test table is obtained. The results of the study concluded that the K-Nearest Neighbour algorithm can determine computer opponents fairly well. More data samples are needed as data training to increase the level of classification accuracy.

Understanding Consumer Behavior in Live Streaming E-Commerce: A Technology Acceptance Model Perspective Herlina, Herlina; Andry, Johanes Fernandes; Mulyana, Teady Matius Surya; Wilujeng, Fuji Rahayu; Sasongko, Yohanes Probo Dwi; Rachmad, Teguh Hidayatul
Inspiration: Jurnal Teknologi Informasi dan Komunikasi Vol. 15 No. 1 (2025): Inspiration: Jurnal Teknologi Informasi dan Komunikasi
Publisher : Pusat Penelitian dan Pengabdian Pada Masyarakat Sekolah Tinggi Manajemen Informatika dan Komputer AKBA Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35585/inspir.v15i1.105

Live streaming has rapidly become a transformative feature within the landscape of online shopping, not only serving as an interactive marketing tool but also reshaping consumer decision-making processes in the digital marketplace. Far beyond a mere add-on, live streaming represents a disruptive innovation that significantly alters consumer–vendor engagement and accelerates the evolution of e-commerce ecosystems. To gain a deeper understanding of this phenomenon, the present study employs the Technology Acceptance Model (TAM) as a theoretical lens to investigate the drivers of consumer adoption and sustained usage of live streaming in online shopping contexts. Data were collected from 150 active users of live streaming features through purposive accidental sampling and analyzed using path analysis with AMOS software. The results provide strong empirical evidence that the TAM constructs Perceived Usefulness (PU), Perceived Ease of Use (PEU), Attitude Toward Using (ATU), Behavioral Intention to Use (BIU), and Actual System Use (AU) are all significantly and positively interrelated. These findings underscore the strategic importance of consumer perceptions of utility and ease of use in fostering favorable attitudes, strengthening behavioral intentions, and translating into actual system usage. This research not only validates TAM in the context of live streaming but also offers critical implications for global e-commerce stakeholders and technology developers by highlighting how interactive features can be optimized to enhance consumer engagement, trust, and long-term digital marketplace sustainability.

Fire Detection Using Logistic Regression with GLCM, RGB Ratio, RGB Intersection, and Color Moments Dickens, Pieter; Mulyana, Teady Matius Surya
Jurnal Ilmu Komputer dan Informatika Vol 5 No 1 (2025): JIKI - Juni 2025
Publisher : CV Firmos

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54082/jiki.250

Fires pose a significant threat to human safety and property, particularly in densely populated urban environments where rapid and accurate early detection is critical. This study proposes an automated fire detection system based on computer vision and Logistic Regression classification, utilizing a combination of texture and color-based features to improve detection performance. The proposed approach integrates Gray-Level Co-occurrence Matrix (GLCM), RGB Ratio, RGB Intersection, and Color Moments to extract discriminative features from fire and non-fire images. The dataset, obtained from Kaggle, was preprocessed through HSV-based color segmentation to isolate candidate fire regions before manual annotation. The extracted features were then used to train a Logistic Regression model with hyperparameter tuning of the max_iter parameter to achieve optimal convergence. Experimental results show that the proposed model achieved an accuracy of 86% and a recall of 84% on the training dataset, and an accuracy of 87% with a recall of 82% on the test dataset. Despite these promising results, some false negatives were observed, indicating the need for further refinement to improve sensitivity. Comparative evaluation with a Convolutional Neural Network (CNN) demonstrated that the Logistic Regression approach achieved higher average processing speed, reaching up to 16.2 FPS for video input, compared to 11 FPS for CNN, making it more suitable for real-time applications. Overall, the integration of multi-feature extraction with Logistic Regression offers a balance between accuracy and computational efficiency for early fire detection in real-world scenarios.

Pemeriksa Primalitas Suatu Bilangan Menggunakan Pemrograman Dinamis Mulyana, Teady Matius Surya; Wijaya, Agustinus Frits; Ginting, Jusia Amanda; Lee, Francka Sakti; Alvaro, Giovanni
Computatio : Journal of Computer Science and Information Systems Vol. 9 No. 1 (2025): Computatio: Journal of Computer Science and Information Systems
Publisher : Faculty of Information Technology, Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/computatio.v9i1.34534

Bilangan prima merupakan bilangan yang sangat penting dalam berbagai bidang komputasi. Sebagai bilangan yang tidak habis terbagi bilangan manapun selain 1 dan bilangan itu sendiri, sehingga sering dimanfaatkan pada pengkodean yang memerlukan bilangan unik. Salah satu masalah yang timbul sehubungna dengan keperluan bilangan prima ini adalah untuk mendapatkan suatu bilangan unik yang prima memerlukan pengujian primalitas bilangan. Pemeriksaan primalitas dapat mengintegrasikan prinsip Dynamic Programming (DP) melalui teknik memoization dan penyimpanan data persisten. Proses ini akan memanfaatkan tabel bilangan prima yang tersimpan sehingga dapat digunakan Kembali pada pengujian bilangan primalitas bilangan berikutnya. Pendekatan trial division, memungkinkan sistem untuk secara menyimpan dan menggunakan kembali hasil komputasi sebelumnya, sehingga mempercepat proses pemeriksaan bilangan prima di masa mendatang. Uji coba pembagian dioptimalkan dengan batas akar kuadrat. Melalui serangkaian pengujian kinerja, hasil menunjukkan peningkatan efisiensi yang signifikan. Waktu eksekusi berkurang drastis ketika bilangan yang diperiksa sudah ada dalam tabel memoized atau berada dalam jangkauan bilangan prima yang telah dibangun sebelumnya. Namun, penelitian ini juga mengidentifikasi keterbatasan kinerja yang substansial. Ketika program dihadapkan pada kebutuhan untuk memperluas tabel ke rentang bilangan yang sangat besar, algoritma uji coba pembagian sekuensial yang digunakan untuk perluasan tabel menjadi tidak optimal dan memakan waktu komputasi yang sangat lama.

KUANTISASI WARNA KARTUN DARI CITRA NATURAL MENGGUNAKAN K-MEANS KLASTERING Mulyana, Teady Matius Surya; Roberto, Alben; Hakim, Lukman; Herlina, Herlina; Wijaya, Agustinus Fritz
Jurnal Algoritma, Logika dan Komputasi Vol 8, No 2 (2025)
Publisher : Universitas Bunda Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30813/j-alu.v8i2.9056

Cartoons are characterized by simple, flat, and solid colors, making them appealing for various applications, such as avatars or entertainment. However, the manual cartoonization process demands high artistic skill and is time-consuming. This research aims to automate the process through color quantization using K-Means Clustering as a solution to simplify the color palette of natural images. The main issue addressed is the selection of the optimal color mode and features to achieve the desired cartoon effect. In the methodology, the HSI (Hue, Saturation, Intensity) color mode is utilized, where K-Means clustering is specifically applied to the Hue feature only to separate color grouping from the influence of light gradation. The resulting clusters are then combined with discretized Intensity values to sharply distinguish between dark and light colors. Experimental results indicate that the K-Means algorithm is effective for color quantization, producing simpler and more solid colors that visually approximate the original color tones. This study proves that using the Hue feature in K-Means is a suitable strategy for realizing the flat color palette characteristic of cartoons.

Desain User Experience (UX) Pada Website Smart City untuk Meningkatkan Aksesibilitas Layanan Publik Wijaya, Agustinus Fritz; Surya Mulyana, Teady Matius; Liunard, Garren Janico
Jurnal Teknologi dan Manajemen Industri Terapan Vol. 4 No. 2 (2025): Jurnal Teknologi dan Manajemen Industri Terapan
Publisher : Yayasan Inovasi Kemajuan Intelektual

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55826/jtmit.v4i2.582

Perkembangan konsep smart city menuntut pemerintah untuk menyediakan layanan publik yang tidak hanya efisien dan terintegrasi, tetapi juga inklusif dan mudah diakses oleh seluruh lapisan masyarakat. Penelitian ini bertujuan merancang dan mengevaluasi desain user experience (UX) pada website smart city guna meningkatkan aksesibilitas digital, khususnya bagi kelompok rentan seperti penyandang disabilitas dan lansia. Pendekatan Human-Centered Design (HCD) dan standar Web Content Accessibility Guidelines (WCAG 2.1) diintegrasikan dalam proses perancangan. Metode penelitian meliputi observasi, studi literatur, wawancara, penyebaran kuesioner, serta evaluasi heuristik dan usability testing terhadap prototipe website. Hasil pengujian menggunakan System Usability Scale (SUS) menunjukkan skor rata-rata 86,4 (kategori “Excellent”), dengan mayoritas pengguna dapat mengakses fitur utama dalam waktu kurang dari dua menit. Elemen UX seperti navigasi intuitif, kontras warna tinggi, kompatibilitas screen reader, dan desain responsif terbukti meningkatkan kenyamanan dan efektivitas interaksi pengguna. Penelitian ini memberikan kontribusi praktis dan teoretis dalam pengembangan website smart city yang inklusif dan berorientasi pada pengguna, serta mendorong transformasi digital layanan publik yang berkelanjutan.

PENGEMBANGAN APLIKASI PEMBELAJARAN IMERSIF BERBASIS VIRTUAL REALITY MENGGUNAKAN METODE MDLC DAN EVALUASI EUQ Ginting, Jusia Amanda; Sembiring, Irwan; Suryantara, I Gusti Ngurah; Mulyana, Teady Matius Surya; Alamsyah, Ferry
Infotech: Journal of Technology Information Vol 11, No 2 (2025): NOVEMBER
Publisher : ISTEK WIDURI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37365/jti.v11i2.426

The advancement of technology in the field of Virtual Reality (VR) offers new opportunities for developing more interactive and immersive learning media. One of the main challenges in online learning is the low level of student engagement in the learning process, as well as the tendency for instructional methods to remain passive. Recognizing this gap and the need for a new technological approach that can encourage active participation, this study aims to develop a VR-based learning application called “FirstMetaClass”. This application is designed to simulate a virtual classroom environment to enhance students’ learning experiences. The application development process follows the Multimedia Development Life Cycle (MDLC) method. The quality of the user experience was evaluated using the Extended User Experience Questionnaire (EUQ). The respondents consisted of 42 university students who participated in the application trial and completed the evaluation questionnaire. The results of the study show that all EUQ dimensions achieved an average score above 4.0 on a 1–5 scale. These findings confirm that the “FirstMetaClass” application successfully provides a positive, engaging, and user-friendly learning experience, while creating a classroom atmosphere that closely resembles the real world and fosters a sense of presence for users.

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