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Jatilima : Jurnal Multimedia Dan Teknologi Informasi
Published by Cattleya Darmaya Fortuna
ISSN : -     EISSN : 27211800     DOI : -
Core Subject : Science,
Computer Science & IT
JATILIMA merupakan jurnal yang terbit dua nomor dalam satu volume (tahun), yaitu Peridoe I Bulan April dan Periode II Bulan Oktober. JATILIMA mempublikasikan tulisan-tulisan ilmiah hasil pemikiran, studi literatur, dan penelitian dalam bidang Ilmu Komputer. JATILIMA merupakan jurnal dengan sistem review yang merupakaan aspek penting dalam penyebaran ilmu pengetahuan.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 260 Documents
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The Effect of STEAM-Based Learning Assisted by Educational Games and Virtual Reality on Junior High School Students’ Learning Motivation in Basic Programming Materials Novianti, Riska; Achmad Buchori; Wijayanto
Jurnal Multimedia dan Teknologi Informasi (Jatilima) Vol. 7 No. 06 (2026): Jatilima : Jurnal Multimedia Dan Teknologi Informasi
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jatilima.v7i06.2283

Abstract

This study is motivated by the need for technology-based learning innovations to enhance students’ learning motivation, particularly through the integration of the STEAM approach with educational games and virtual reality. This study aims to analyze the effect of STEAM-based learning assisted by educational games and virtual reality on students’ learning motivation. The method used was a quasi-experimental design with a pretest-posttest control group. The research subjects consisted of 56 students divided into an experimental class and a control class. Data were collected using a learning motivation questionnaire that had been tested for validity and reliability, while data analysis was conducted using multiple linear regression tests with IBM SPSS Statistics 27. The results showed that simultaneously, educational games and virtual reality had a significant effect (sig. 0.031 < 0.05) on students’ learning motivation. However, partially, educational games did not have a significant effect (sig. 0.091 > 0.05), and virtual reality also did not show a significant effect (sig. 0.984 > 0.05). The coefficient of determination (R²) value of 0.242 indicates that both variables contributed 24.2% to students’ learning motivation. These findings suggest that the integration of technology in STEAM learning has the potential to improve learning motivation; however, the effectiveness of each medium still needs to be optimized to produce a more significant partial effect.
A Role‑Based Document Verification and Authorization System with QR Code Integration for Campus Administrative Processes Pinem, Sanjaya; El Rezen Purba, Doni; Yakob, Freddy
Jurnal Multimedia dan Teknologi Informasi (Jatilima) Vol. 7 No. 5 (2026): Jatilima : Jurnal Multimedia Dan Teknologi Informasi
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jatilima.v7i5.2293

Abstract

Document authentication has become a critical necessity for various institutions to prevent forgery, such as data manipulation or page substitution. While QR code technology is widely used, many current implementations rely on static links lacking robust validation mechanisms, making them susceptible to exploitation. This study aims to develop a QR code-based document verification system with a centralized validation architecture that is practical and efficient for small-to-medium-sized institutions. The research methodology employs the Software Development Life Cycle (SDLC) Waterfall model, encompassing requirements analysis, system design, implementation, testing, and maintenance. The system is designed with a multi-role workflow (Admin, Lecturer, and Guest) where the QR code serves solely as a reference identity, while the actual validation occurs within a centralized database to minimize spoofing risks. Results from Black Box Testing confirm that the system effectively manages the document lifecycle, from initial upload to electronic signature (TTE) application and real-time public verification via unique URLs. This implementation demonstrates that centralized hash validation is a sufficient security measure to mitigate document forgery risks without requiring high-complexity infrastructure.
Round-Trip Time Estimation Using Hybrid Neuro-Fuzzy Based On Subtractive Clustering Hassan Rizky Putra Sailellah; Suma Danu Ristianto
Jurnal Multimedia dan Teknologi Informasi (Jatilima) Vol. 7 No. 06 (2026): Jatilima : Jurnal Multimedia Dan Teknologi Informasi
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jatilima.v7i06.2159

Abstract

Round-trip time (RTT) is a key latency indicator for quality-of-service (QoS) control and task orchestration in cloud–edge systems. However, RTT is highly time-varying due to congestion dynamics, routing changes, and fluctuating traffic conditions, motivating short-term prediction to enable proactive decision making. This paper investigates a hybrid neuro-fuzzy baseline for RTT prediction implemented using an Adaptive Neuro-Fuzzy Inference System (ANFIS) with subtractive-clustering-based initialization to avoid rule explosion in high-dimensional inputs. A controlled dataset was generated in Mininet using a dumbbell topology with injected delays (1–1000 ms). In total, 100,000 raw RTT records were collected (100 RTT measurements per run across 1000 runs) and aggregated into 1000 supervised samples paired with TCP-state features. Experiments followed a unified and reproducible protocol with a fixed 60/10/30 train/validation/test split, train-only feature standardization, train-only target normalization with inverse transformation for reporting, and validation-based checkpoint selection. The ANFIS baseline (radius ????=0.5r=0.5, 19 rules) achieved RMSE/ MAE/ MAPE/ ????2 of 1191.63/ 751.02/ 0.001921/ 0.999996 on validation and 1207.23/ 664.70/ 0.001311/ 0.999996 on testing. Training required 546.91 s, while inference remained lightweight (0.0846 s for 100 validation samples and 0.1493 s for 300 test samples). Diagnostic analyses using learning curves, parity plots, residual inspection, and empirical error distributions further supported the strong agreement between predicted and observed RTT values. These results indicate that ANFIS with subtractive clustering can deliver accurate and low-latency RTT prediction suitable for QoS-aware orchestration pipelines where training can be performed offline.
Detection of Corn Leaf Blight Disease Based on GLCM and HSV Feature Extraction Using Support Vector Machine Sami&#039;un, Defitroh Chen; Arnoldus Janssen Dahur; Mamed Manalu; M Aidil Arif; Dery Yuswanto Jaya
Jurnal Multimedia dan Teknologi Informasi (Jatilima) Vol. 7 No. 06 (2026): Jatilima : Jurnal Multimedia Dan Teknologi Informasi
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jatilima.v7i06.2270

Abstract

Corn leaf blight is a major disease that reduces crop productivity, making early detection essential. This study proposes an image-based detection method using Gray Level Co-occurrence Matrix (GLCM) and HSV feature extraction with Support Vector Machine (SVM) classification. The dataset, obtained from Kaggle, consists of 2308 corn leaf images categorized into healthy and blight classes. The method includes preprocessing, segmentation, feature extraction, and classification. Preprocessing involves resizing, grayscale conversion, noise reduction, and normalization. Segmentation is performed using Otsu thresholding and K-Means clustering to isolate leaf regions and highlight disease areas. Feature extraction combines four GLCM texture features and three HSV color features to represent each image. The SVM model, evaluated using an 80:20 data split, achieved an accuracy of 94.8% with balanced precision, recall, and F1-score values of approximately 0.95. These results indicate that the proposed method is effective for detecting corn leaf blight and has potential for practical agricultural applications
Performance Evaluation of a Mobile Attendance System Using Dual-Factor Dynamic Qr Code and Gps Geofencing Rosma Siregar; Bagoes Maulana; Muhammad Isnaini; Elsa Sabrina; Harvei Desmon Hutahaean
Jurnal Multimedia dan Teknologi Informasi (Jatilima) Vol. 7 No. 06 (2026): Jatilima : Jurnal Multimedia Dan Teknologi Informasi
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jatilima.v7i06.2281

Abstract

This study develops and evaluates an Android-based attendance system integrating dual-factor authentication using dynamic QR codes and GPS geofencing to prevent proxy attendance in higher education. The system was developed using the Waterfall model and evaluated through quantitative experiments measuring response time, GPS accuracy drift, and security robustness via Black-Box testing. Results show high efficiency with an average response time below 1.5 seconds. GPS validation achieved an average drift of 4.2 meters outdoors and 12.5 meters indoors, remaining within the 30-meter geofencing threshold. The system successfully rejected unauthorized attempts, including out-of-range scans and fake GPS spoofing. These findings demonstrate that combining dynamic QR codes with GPS validation significantly improves attendance authenticity and system reliability compared to single-factor methods. The study provides empirical evidence of a robust and scalable solution for secure mobile-based attendance systems in higher education.
A K-Prototypes-Based Approach for Modeling Student Segmentation Based on Learning Strategies to Support Academic Decision-Making Nurul Ain Farhana; Putri Maulidina Fadilah; Putri Harliana; Suwanto
Jurnal Multimedia dan Teknologi Informasi (Jatilima) Vol. 7 No. 06 (2026): Jatilima : Jurnal Multimedia Dan Teknologi Informasi
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jatilima.v7i06.2282

Abstract

This study aims to model student segmentation based on learning strategies using the K-Prototypes clustering algorithm. The data used consist of mixed-type variables, including categorical variables (gender and major) and numerical variables such as grade point average (GPA), learning habits, motivation, learning environment, health and social support, academic involvement, and academic achievement. The analysis was conducted through several stages, including data preprocessing, exploratory data analysis, and clustering using the K-Prototypes algorithm. The optimal number of clusters was determined using the Elbow and Silhouette methods, both of which indicated that four clusters provide the best clustering structure. The results show that students can be grouped into four distinct clusters with different characteristics. Cluster 3 represents highly motivated and high-achieving students with strong engagement, while Cluster 1 consists of students with good academic performance supported by favorable learning conditions. Cluster 4 includes students with moderate characteristics, and Cluster 2 represents students with lower performance and weaker learning strategies. The clustering results were further validated using t-SNE visualization, which shows a reasonably clear distribution of clusters despite some overlap. Overall, this study demonstrates that the K-Prototypes algorithm is effective in handling mixed-type educational data and can provide meaningful insights to support data-driven academic decision-making and the development of targeted learning strategies.
The Effect of STEAM-Based Learning Assisted by Educational Games and Virtual Reality on Junior High School Students’ Learning Motivation in Basic Programming Materials Riska Novianti; Achmad Buchori; Wijayanto
Jurnal Multimedia dan Teknologi Informasi (Jatilima) Vol. 7 No. 06 (2026): Jatilima : Jurnal Multimedia Dan Teknologi Informasi
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jatilima.v7i06.2283

Abstract

This study is motivated by the need for technology-based learning innovations to enhance students’ learning motivation, particularly through the integration of the STEAM approach with educational games and virtual reality. This study aims to analyze the effect of STEAM-based learning assisted by educational games and virtual reality on students’ learning motivation. The method used was a quasi-experimental design with a pretest-posttest control group. The research subjects consisted of 56 students divided into an experimental class and a control class. Data were collected using a learning motivation questionnaire that had been tested for validity and reliability, while data analysis was conducted using multiple linear regression tests with IBM SPSS Statistics 27. The results showed that simultaneously, educational games and virtual reality had a significant effect (sig. 0.031 < 0.05) on students’ learning motivation. However, partially, educational games did not have a significant effect (sig. 0.091 > 0.05), and virtual reality also did not show a significant effect (sig. 0.984 > 0.05). The coefficient of determination (R²) value of 0.242 indicates that both variables contributed 24.2% to students’ learning motivation. These findings suggest that the integration of technology in STEAM learning has the potential to improve learning motivation; however, the effectiveness of each medium still needs to be optimized to produce a more significant partial effect.
Implementation of NLP in Groupin Implementation of NLP in Grouping Social Assistance Recipients: A Case Study of Girisubo District Mahmud Isti Panggalih; Farida Ardiani
Jurnal Multimedia dan Teknologi Informasi (Jatilima) Vol. 7 No. 07 (2026): Jatilima : Jurnal Multimedia Dan Teknologi Informasi
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jatilima.v7i07.2333

Abstract

This research aims to examine and implement text analysis of social assistance recipients data using Natural Language Processing (NLP) methods as a solution to accelerate and improve efficiency in the process of categorizing aid recipients. Based on the design and testing processes carried out, the developed system is capable of automatically processing descriptive data of aid recipients and grouping them into appropriate categories, such as the elderly, school children, pregnant women, the disabled, and minors. The research design uses System Development Research. The results of the NLP system implementation in the case study of categorizing social assistance recipients in Girisubo District show a significant improvement in operational efficiency and classification accuracy. Quantitatively, the trained NLP model successfully achieved high performance metrics. The average classification accuracy exceeds 90%, with data clustering computation time much faster compared to the manual process that takes hours. The main conclusion of this study indicates that the implementation of Natural Language Processing (NLP) in Girisubo District is effective in classifying categories of aid recipients. The model shows the strongest performance in the Pregnant Women group (95% Accuracy) and Persons with Disabilities (97% Accuracy) with perfect Precision of 100%. The performance for the Elderly and School Children is also very good (minimum 89% Accuracy). Overall, the system has proven reliable and is capable of automatically grouping descriptive data into the appropriate categories.
PENGELOMPOKAN HARGA SEPEDA MOTOR BEKAS BERDASARKAN TAHUN PRODUKSI DAN KAPASITAS MESIN MENGGUNAKAN ALGORITMA K-MEANS Bagus Januar; Abdul Halim Hasugian
Jurnal Multimedia dan Teknologi Informasi (Jatilima) Vol. 7 No. 07 (2026): Jatilima : Jurnal Multimedia Dan Teknologi Informasi
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jatilima.v7i07.2276

Abstract

Pengelompokan harga sepeda motor bekas menjadi hal penting dalam membantu konsumen maupun penjual dalam menentukan nilai pasar yang wajar. Riset ini memiliki akhir untuk mengelompokkan harga motor second berdasarkan tahun produksi dan kapasitas mesin memakai algoritma K-Means. Adapun data yang dipakai berupa dataset motor second yang mencakup variabel tahun produksi, kapasitas mesin (cc), dan harga. Metode yang digunakan meliputi tahap pengumpulan data, preprocessing, penetapan nilai cluster memakai metode Elbow, serta penerapan algoritma K-Means untuk proses pengelompokan. Hasil Riset mengemukakan bahwa data mampu dibagi ke dalam beberapa klaster yang merepresentasikan kategori harga tertentu, seperti rendah, sedang, dan tinggi. Pengelompokan ini memberikan gambaran pola harga berdasarkan karakteristik kendaraan, sehingga mampu membantu untuk pengambilan keputusan baik bagi pembeli maupun penjual.
ANALISIS EFEKTIVITAS MEDIA INTERAKTIF DALAM MENINGKATKAN PARTISIPASI BELAJAR SISWA PADA PEMBELAJARAN DI ERA DIGITAL DI YAYASAN SMP ADVENT AIR BERSIH MEDAN Genimas Hulu; Norenta Sitohang
Jurnal Multimedia dan Teknologi Informasi (Jatilima) Vol. 7 No. 04 (2025): Jatilima : Jurnal Multimedia Dan Teknologi Informasi
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jatilima.v7i04.1910

Abstract

Riset ini dilaksanakan dengan tujuan menilai efektivitas media pembelajaran interaktif dalam mendongkrak keterlibatan dan motivasi akademik siswa pada pelajaran Informatika/TIK di era digital. Metode kuantitatif dengan desain eksperimental digunakan, melibatkan 50 siswa dari Yayasan SMP Advent Air Bersih Medan yang dibagi menjadi kelompok eksperimen (menggunakan media interaktif seperti kuis dan game edukatif) dan kelompok kontrol (menggunakan media tradisional). Pengambilan data dilakukan melalui kuesioner skala Likert, yang kemudian dianalisis menggunakan SPSS. Hasil penelitian menunjukkan peningkatan signifikan pada tingkat partisipasi, dengan nilai rata-rata 4.23 untuk kelompok eksperimen berbanding 3.80 pada kelompok kontrol. Secara keseluruhan, media interaktif terbukti efektif meningkatkan partisipasi, memperkuat pemahaman materi, dan menciptakan proses belajar yang lebih menarik dan relevan, sehingga kualitas pembelajaran siswa terangkat.

Page 23 of 26 | Total Record : 260

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