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Jurnal Teknologi Informasi dan Multimedia
Published by Puslitbang Sekawan Institute Nusa Tenggara
ISSN : 27152529     EISSN : 26849151     DOI : https://doi.org/10.35746/jtim.v2i1
Core Subject : Science,
Computer Science & IT
Cakupan dan ruang lingkup JTIM terdiri dari Databases System, Data Mining/Web Mining, Datawarehouse, Artificial Integelence, Business Integelence, Cloud & Grid Computing, Decision Support System, Human Computer & Interaction, Mobile Computing & Application, E-System, Machine Learning, Deep Learning, Information Retrievel (IR), Computer Network & Security, Multimedia System, Sistem Informasi, Sistem Informasi Geografis (GIS), Sistem Informasi Akuntansi, Database Security, Network Security, Fuzzy Logic, Expert System, Image Processing, Computer Graphic, Computer Vision, Semantic Web, Animation dan lainnya yang serumpun dengan Teknologi Informasi dan Multimedia.
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Articles 15 Documents
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Search results for , issue "Vol. 7 No. 2 (2025): May" : 15 Documents clear
Smart Traffic untuk Menghitung Volume Kendaraan dan Klasifikasi Kondisi Lalu Lintas Menggunakan Model YOLOv7 Kurniadin Abd Latif; Putri Tanisa Utami; Apriani Apriani; Fatimatuzzahra Fatimatuzzahra; Ria Rismayati
Jurnal Teknologi Informasi dan Multimedia Vol. 7 No. 2 (2025): May
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v7i2.667

Abstract

One of the most complex challenges in urban management, particularly in developing countries, is traffic control. Traffic congestion has become a global issue, significantly affecting mobility, economic productivity, and quality of life. To address this problem, smart traffic systems are increasingly being adopted as adaptive and efficient solutions. This study aims to implement the You Only Look Once version 7 (YOLOv7) object detection model within a smart traffic system to calculate vehicle volume and monitor traffic conditions in real time. YOLOv7 is chosen for its high object detection accuracy, even in dynamic and complex environments where objects are fast-moving or overlapping in dense backgrounds. The methodology involves processing a 2-minute-30-second CCTV video recording taken from a street in New York City. Vehicle detection is conducted by applying bounding boxes over specific areas within the video frames, which serve as virtual counters for vehicles passing through. The experimental results demonstrate that the system effectively counts vehicles per second and identifies traffic conditions, which in this case remained smooth throughout the observation period. These findings highlight the potential of implementing YOLOv7 in smart traffic systems to support data-driven, automated, and real-time traffic management.
Media Pembelajaran Peralatan Servis Sepeda Motor dengan Menerapkan Teknologi Augmented Reality Miftahul Madani; Melati Rosanensi
Jurnal Teknologi Informasi dan Multimedia Vol. 7 No. 2 (2025): May
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v7i2.682

Abstract

Learning media is one of the key components in the educational process. Teachers need to pay special attention to the use of learning media during teaching and learning activities. However, a lack of variety and suboptimal utilization of learning media often causes students to lose interest in learning. In fact, learning media aim to serve as tools to enhance the effectiveness of the learning process. Learning media are available in various forms, one of which is printed media or verbal explanation-based methods that are widely used in schools. This type of media is chosen for its practicality, adaptability to students' abilities, and ease of distribution. However, printed media have limitations, such as the inability to present elements like sound, animation, or three-dimensional objects. This study employs the Multimedia Development Life Cycle (MDLC) method, which consists of six stages: Concept, Design, Material Collection, Assembly, Testing, and Distribution. The final product of this research is an application in ".apk" format that can be installed on Android devices. Augmented reality is a term used to describe various types of display technology that can add or integrate information in the form of text, symbols or graphics into the user's view of the real world, this application utilizes Augmented Reality technology to introduce motorcycle service tools, helping vocational high school (SMK) students acquire basic skills and access information via their smartphones. User testing using the Likert Scale resulted in a score of 33.46, which falls into the "Strongly Agree" category.
Studi Pemodelan dan Prediksi Aktivitas Antibakteri Biopo-limer Kitosan Menggunakan Response Surface Methodology (RSM) Halil Akhyar; Selvira Anandia Intan Maulidya; Muhammad Mukaddam Alaydrus; Maz Isa Ansyori; Mohammad Zaenuddin Hamidi; I Gede Pasek Suta Wijaya; Ramaditia Dwiyansaputra; Pahrul Irfan
Jurnal Teknologi Informasi dan Multimedia Vol. 7 No. 2 (2025): May
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v7i2.713

Abstract

Infections occured in the human are mostly caused by uncontrolled growth of Staphylococcus aureus bacteria. A strategy to inhibit bacterial growth can use antibacterial agents such as chitosan. The mechanism of the effectiveness of chitosan as an antibacterial is quite complex, even the data on its antibacterial activity is quite fluctuating so that it is difficult to analyze accurately and efficiently. Therefore, the purpose of the study was to predict the inhibition zone of s.aureus bacteria through laboratory experiments combined with modeling using the Central Composite Design (CCD) approach. The research was carried out with two main stages, including chitosan isolation and calculation of bacterial inhibition zones. The production of chitosan leverages the microwave isolation and FTIR to examine for the degree of deacetylation and its functional group using. Furthermore, the antibacterial activity of chitosan biopolymer was tested using the diffusion method combined with modeling using the RSM CCD approach. The results showed that chitosam from oyster shell was obtained by DD of 83.29% and the emergence of typical chitosan groups, such as amine (NH2) and hydroxyl (OH). Chitosan can hamper the growth of s. aureus bacteria with an inhibition zone of up to 0.40 mm. The experimental data were combined with computational modeling obtained the values of the determination coefficient R2 = 0.6083. The modeling was assessed by p-value of < 0.0001 and F-value of 13.46. Statistically, the obtained model is relevant to the relationship between the number of bacterial colonies and the concentration of chitosan solution with the bacterial inhibition zone. Based on numerical analysis and modeling, the predicted values of the number of s. aureus bacterial colonies and chitosan concentrations were 550,000 CFU/ml and 42.5%. Therefore, Pearl shells can be isolated into chitosan, as well as chitosan has the potential to be a good antibacterial agent. The model has good prediction performance, but it rquires to increase the number of point spreads and it is necessary to validate the prediction results to obtain actual predictions.
Penerapan Metode K-Nearest Neighbor Untuk Prediksi Jumlah Kasus HIV di Provinsi Jawa Barat Muhammad Adam Rizky Habibi; Shofa Shofia Hilabi; Bayu Priyatna; Elfina Novalia
Jurnal Teknologi Informasi dan Multimedia Vol. 7 No. 2 (2025): May
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v7i2.721

Abstract

The high number of HIV/AIDS cases in Indonesia, especially in West Java Province, is a serious challenge in the field of public health. Limitations in understanding the pattern of spread and predicting the trend of HIV cases cause countermeasures to be less than optimal. To overcome this, this study was conducted with the aim of predicting the number of HIV cases in West Java using the K-Nearest Neighbor (KNN) algorithm, based on historical data from Open Data Jabar from 2019 to 2023 which includes 1,617 data from various districts / cities. The research stages include data collection, preprocessing, feature selection, normalization, division of training and test data, and model evaluation using regression metrics: Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and R-squared (R²). The evaluation results show that the KNN model with an optimal K value of 19 produces an MAE of 142.31, MSE of 40,442.92, RMSE of 201.10, and R² value of 0.2397. Predictions for 2024 show that areas with the highest number of HIV cases are in Bandung City, Bogor Regency, Bekasi City, Bekasi Regency, and Indramayu Regency.
Implementasi Algoritma Dijkstra dan Bellman-Ford untuk Optimasi Rute Pemadam Kebakaran di Kota Praya Sunardi Sunardi; Muhamad Azwar; Dedy Sofian MZ; Angga Radlisa Samsudin; Fazlul Rahman
Jurnal Teknologi Informasi dan Multimedia Vol. 7 No. 2 (2025): May
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v7i2.744

Abstract

Forest and land fires are critical emergencies requiring rapid response to minimize casualties and property damage. In urban areas like Praya City, fire department response delays are often caused by inefficient routing, especially with traffic congestion and complex road infrastructure. This study aims to analyze and compare the performance of Dijkstra's and Bellman-Ford's algorithms for optimizing firefighter routes in Praya City. This quantitative research utilized a computational and comparative analysis approach. Road network data from Praya City was obtained from Google Maps and modeled as a static graph consisting of 17 nodes and weighted edges repre-senting actual distances. Dijkstra's and Bellman-Ford's algorithms were implemented in Python to find the shortest routes from a designated starting point (Fire Department office) to all other nodes. Performance was evaluated based on route optimality, completeness, and computation time. Both Dijkstra's and Bellman-Ford's algorithms successfully identified identical optimal shortest routes for all tested origin-destination pairs within the Praya City graph. However, Dijkstra's algorithm demonstrated significantly superior computational efficiency, with an average computation time of 0.5 seconds, compared to Bellman-Ford's 1.5 seconds. For optimizing firefighter routes on the static road network graph of Praya City, Dijkstra's algorithm is recommended due to its combi-nation of optimality and superior speed. This finding provides an empirical basis for developing more efficient emergency response navigation systems. Future research should focus on inte-grating dynamic parameters like real-time traffic data.

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