cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Ni Made Satvika Iswari
Contact Email
satvika@umn.ac.id
Phone
-
Journal Mail Official
ultimatics@umn.ac.id
Editorial Address
-
Location
Kota tangerang,
Banten
INDONESIA
Jurnal ULTIMATICS
Published by Universitas Multimedia Nusantara
ISSN : 20854552     EISSN : 2581186X     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering
Jurnal ULTIMATICS merupakan Jurnal Program Studi Teknik Informatika Universitas Multimedia Nusantara yang menyajikan artikel-artikel penelitian ilmiah dalam bidang analisis dan desain sistem, programming, algoritma, rekayasa perangkat lunak, serta isu-isu teoritis dan praktis yang terkini, mencakup komputasi, kecerdasan buatan, pemrograman sistem mobile, serta topik lainnya di bidang Teknik Informatika. Jurnal ULTIMATICS terbit secara berkala dua kali dalam setahun (Juni dan Desember) dan dikelola oleh Program Studi Teknik Informatika Universitas Multimedia Nusantara bekerjasama dengan UMN Press.
Arjuna Subject : -
Articles 275 Documents
 19   20   21   22   23 
Bacteria Recognition Application Model Using Marker-Based Augmented Reality for Android Mobile Devices Mulyani, Asri; Kurniadi, Dede; Fadillah, Hadi Bagus
ULTIMATICS Vol 15 No 2 (2023): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ti.v15i2.3278

Abstract

This article aims to develop a multimedia application model for bacterial recognition using Marker-Based Augmented Reality (Marker-Based AR) technology for Android mobile devices. Marker-based tracking creates mobile augmented reality markers to increase user interaction in Marker-Based Augmented Reality systems. The software development method uses the Multimedia Development Life Cycle, which consists of 6 phases: concept, design, material collecting, assembly, testing, and distribution. The results of this study are a model of a multimedia application for bacterial recognition using Marker-Based AR, which has a marker-based tracking feature and displays bacterial objects in 3 dimensions along with their explanations and exercise questions. Based on user tests, it shows that the application model developed helps and makes it easier to learn about bacteria independently using Android mobile devices more easily and interestingly. This is proven based on beta testing towards users who got a score of 73.68% is obtained which agrees.
A Comparative Study of Body Motion Recognition Methods for Elderly Fall Detection: A Review Apriantoro, Roni; Setyawan, Muhammad Adriano Khairur Rizky; Lavindi, Eri Eli
ULTIMATICS Vol 16 No 1 (2024): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ti.v16i1.3293

Abstract

To maintain the welfare of the elderly, intensive and effective monitoring is needed to ensure their safety. Conventional elderly activity monitoring has several limitations (i.e., space and time) due to human abilities. This problem can be overcome by applying real-time monitoring methods using Wireless Body Area Networks (WBAN) and Artificial Intelligence (AI). Several methods have been used and tested, including artificial intelligence implementations from sensor data-based to computer vision-based pattern recognition for body motion classification. Several methods that have been studied show accurate results in classifying elderly body motions/gestures. However, the Human Activity Recognition (HAR) method performs better for elderly activity monitoring applications and makes fall classification more accurate.
Design and Development of a Learning Style Identification Application for JPTK Students using the K-Nearest Neighbor Ramadhan, Firdaus Ditio; Liantoni, Febri; Prakisya, Nurcahya Pradana Taufik
ULTIMATICS Vol 15 No 2 (2023): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ti.v15i2.3299

Abstract

Learning styles are crucial for all students, as the chosen learning style can greatly assist them in learning. The data source for this research originates from questionnaire results distributed to JPTK students of the 2019-2021 cohorts, which were used to assess the effectiveness of a learning style product on the students' JPTK website. This study employs the K-Nearest Neighbor approach, which utilizes the principle of nearest neighbors to categorize students' learning styles based on provided features. The data used in this research is derived from the website that students use to input information about their preferred learning styles. Various elements, including visual, auditory, and kinesthetic preferences, are present in the questionnaire on the website. Subsequently, the data is processed and fed into a Python K Nearest Neighbor model to predict students' learning styles and nearest neighbors. The evaluation results indicate that the developed classification model achieves a reasonably high accuracy level of 93%, making it a useful tool for effectively and efficiently identifying students' learning styles. It is hoped that implementing this learning style classification model will benefit the field of education. By understanding students' learning styles, educators can create more tailored lesson plans, enhance learning outcomes, and reduce the likelihood of knowledge loss.
Application of Convolutional Neural Network Using TensorFlow as a Learning Medium for Spice Classification Saputro, Muhammad Naufal Adi; Liantoni, Febri; Maryono, Dwi
ULTIMATICS Vol 16 No 1 (2024): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ti.v16i1.3304

Abstract

The purpose of this research are: (1) To determine the accuracy of the CNN method in the development of a website for classifying spices, (2) To assess the feasibility of the spice classification website as a learning medium, (3) To ascertain user responses to the spice classification website as a learning medium. The method employed in this research is research and development. This study utilizes the ADDIE development method, which comprises 5 stages: (1) Analysis, (2) Design, (3) Development, (4) Implementation, and (5) Evaluation. The research yielded a significantly high accuracy rate. This is demonstrated by the results showing an accuracy of 96%, precision of 97%, and recall of 96%. Moreover, the research found the developed website to be feasible. This is supported by the evaluation using the Learning Object Review Instrument (LORI), resulting in a score of 88% from media experts and a score of 90% from subject matter experts. Additionally, user response was positive. This is evidenced by testing the learning media on 10th-grade culinary students from SMK N 4 Surakarta, which yielded a score of 76% using the System Usability Scale (SUS), indicating a favorable usability assessment. In conclusion, the spice classification website, as a learning medium, can be employed as a suitable educational tool.
REAL-TIME TOMATO QUALITY DETECTION SYSTEM USING YOU ONLY LOOK ONCE (YOLOv7) ALGORITHM Muarofah, Isna Ayu; Vikri, Muhammad Jauhar; Sa’ida, Ita Aristia
ULTIMATICS Vol 15 No 2 (2023): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ti.v15i2.3337

Abstract

Real-time object detection is a crucial aspect of computer vision. With the increasing prominence of the big data field, it has become easier to gather data from various sources. Over the past few decades, computer vision inspection systems have become essential tools in agricultural operations, and their usage has seen a significant rise. Computer vision automation-based technology in agriculture is increasingly being employed to enhance productivity and efficiency. Tomato is a widely utilized crop commodity, finding applications in food, cosmetics, and pharmaceuticals. Consequently, tomato farming continues to evolve and has become one of the nation's export commodities. YOLO is an algorithm capable of real-time object detection and recognition. In this study, the YOLOv7-tiny architecture, which has lower computational overhead, was utilized. For quality detection of tomatoes, they were categorized into three classes: ripe, unripe, and defective. The trained model yielded a recall score of 0.97, precision of 1.0, a PR-curve of 0.838, and an F1-score of 0.81, indicating that the model learned effectively. The research achieved an accuracy of 90.6% on original images with an average IoU of 0.90 and a detection time of 2.7 seconds. In images with added light disturbance, the average accuracy was 91.2%. Images with reduced light yielded an average accuracy of 92%, while images with blur disturbance had an average accuracy of 78.2%. In real-time testing, ripe tomatoes were detected up to a maximum distance of 90cm, unripe tomatoes at 90cm, and defective tomatoes at 70cm.
Comparing Karate Framework with Others for Automated Regression Testing: A Case Study of PT Fliptech Lentera Inspirasi Pertiwi Dayanti, Afina Putri; Tony, Tony
ULTIMATICS Vol 16 No 1 (2024): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ti.v16i1.3397

Abstract

In the rapidly evolving digital era, applications, and software systems increasingly rely on Application Programming Interfaces (APIs) to enable interaction, integration, and functionality extension. However, manual testing of APIs is often inefficient and challenging to reuse when changes occur. To address this, automation testing has become a more effective choice, where test scripts can verify and execute tests repeatedly, easily adapting to API changes. Essentially, automation testing plays a vital role in software maintenance, particularly in regression testing, which tests modified or upgraded software versions to ensure that their core functions remain unchanged and unaffected. One approach to automation testing is employing the Software Testing Life Cycle (STLC), which follows a systematic series of stages conducted by the testing team to ensure software product quality. This paper utilizes PT Fliptech Lentera Inspirasi Pertiwi’s public API to conduct testing on 25 scenarios from two modules. The objective is to utilize the Karate Framework to conduct these automated regression tests, resulting in an impressively short testing duration, averaging only 42.645 seconds, or approximately 1.706 seconds per scenario. A comparison with the Behave framework, using the same scenarios but with differences in steps, reveals that Behave achieves a duration of 18.762 seconds, or 0.750 seconds per scenario, making it 127.295% faster than Karate. However, in terms of the number of steps, Behave covers only 188, while Karate includes 543. This means that Behave requires 0.100 seconds per step, while Karate necessitates 0.079 seconds per occurrence. Karate provides more detailed results by 188.830% per step or 26.582% in terms of step duration. The primary goal is to enhance testing efficiency, expedite issue identification and resolution, provide a clearer testing process, and potentially improve overall software quality.
Educational Game Design For Carbon Emission Using Game Development Life Cycle Method Tresnawati, Dewi; Rahayu, Sri; Maulana, Randi
ULTIMATICS Vol 16 No 1 (2024): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ti.v16i1.3406

Abstract

Carbon emissions are gases that arise from human actions, such as burning fossil fuels and industrial waste. Climate change is currently a problem that is increasingly attracting the attention of the wider community worldwide, including Indonesia. The educational game about carbon emissions applies the Game Development Life Cycle (GDLC) approach, which consists of six stages, including initiation, pre-production, production, testing, beta, and launch. The educational game on carbon emissions is expected to help raise youth awareness about the importance of reducing carbon emissions and provide information about efforts to reduce carbon emissions for the younger generation and the general public.
Sentiment Analysis on Song Lyrics for Song Popularity Prediction Using BERT Agatha, Hana; Putri, Farica Perdana; Suryadibrata, Alethea
ULTIMATICS Vol 15 No 2 (2023): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ti.v15i2.3420

Abstract

The increasingly competitiveness in music industry is giving some musicians disadvantages. Musicians need to pay more attention to the factors that influence the popularity of a song, so their song can be popular and they can gain a lot of profit. One of the various factors that can affect a song popularity is the lyrics. The influence of the lyrics can be explored through sentiment analysis. Sentiment analysis is a computing study that identify sentiments or emotions in a text. By conducting sentiment analysis on the lyrics, song popularity can be predicted. Based on the prediction result, songwriters can evaluate their lyrics, so their song can be popular. Bidirectional Encoder Representations from Transformers (BERT) is an excellent algorithm in terms of sentiment analysis. In this study, a BERT model was developed to predict the song popularity, based on the sentiment analysis of the song lyrics. The popularity class of a song will be predicted, based on the results of lyrics sentiment analysis. The developed model is a model that has been trained with English songs. Based on the experiment, the model that used oversampling method achieved accuracy by 87%, precision by 88%, recall by 87%, and f1-score by 87%.
Implementation of Scrum Method for Designing Website-Based E-commerce Application (Case Study: Putra Prabu Workshop) Wijaya, William; Tobing, Fenina Adline Twince
ULTIMATICS Vol 15 No 2 (2023): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ti.v15i2.3487

Abstract

The internet is a technology that has now become a major necessity in the world. There are many applications designed using the internet to meet daily needs, such as educational, commercial and other applications. according to DataIndonesia.id the number of motorized vehicles in Indonesia, which according to vehicles in Indonesia reached 141.99 million units in 2021. Bengkel Putra Prabu is a workshop that operates in the city of Prabumulih, Putra Prabu has several problems, such as lack of intensive advertising. Scrum is a software engineering method using agile principles that relies on team collaboration, incremental products and an iteration process to realize the final result. The results show user acceptance of the system system was 76.06% for the Perceived Ease Of Use category, 73.51% for the Perceived Usefulness category, 71.53% for the Atitude Toward Using category, and 71.89% for the Behavioral Intentional category. The conclusion of this research the system that has been created is well received by users.
Efficient Order Management: Design and Implementation of a System using Scheduling Algorithms and Expert Validation Surbakti, Eunike Endariahna; Rizky, Nazim; Pane, Ivransa Zudhi; Khouwira, Filbert
ULTIMATICS Vol 15 No 2 (2023): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ti.v15i2.3489

Abstract

This research focuses on the crucial role of system interfaces in enhancing user experience, particularly in the context of an online canteen ordering system. A well-designed interface not only improves user satisfaction but also streamlines the ordering process, addressing issues like queuing in canteens. The study employs Expert Validation to gather valuable insights from experts, ensuring a robust foundation for system development and evaluation. The online canteen ordering system facilitates food orders through an application, eliminating the need for users to physically visit the canteen. This approach not only benefits users but also aids canteen management in efficient order handling.The scheduling algorithms, FCFS (First Come First Served) and SJF (Shortest Job First), are utilized to manage incoming orders. FCFS, chosen for its intuitive handling of queuing problems, complements the SJF algorithm, which excels in efficiently managing numerous orders. The system dynamically switches between these algorithms based on the order load, resulting in an effective queuing structure. Usability testing is conducted to evaluate the system’s user-friendliness, with an impressive average score of 86.6%. This indicates that the system is wellreceived and navigable by users. The website implementation receives an ”good” categorization through UEQ (User Experience Questionnaire) testing, with attractive design and high scores in aspects like Perspicuity, Efficiency, Dependability, Stimulation, and Novelty. These findings collectively affirm the success of the designed interface in delivering a positive user experience for the online canteen ordering system.

Page 21 of 28 | Total Record : 275

 19   20   21   22   23 

Filter by Year

2011 2025


Reset
Filter By Issues
All Issue Vol 17 No 1 (2025): Ultimatics : Jurnal Teknik Informatika Vol 16 No 2 (2024): Ultimatics : Jurnal Teknik Informatika Vol 16 No 1 (2024): Ultimatics : Jurnal Teknik Informatika Vol 15 No 2 (2023): Ultimatics : Jurnal Teknik Informatika Vol 15 No 1 (2023): Ultimatics : Jurnal Teknik Informatika Vol 14 No 2 (2022): Ultimatics : Jurnal Teknik Informatika Vol 14 No 1 (2022): Ultimatics : Jurnal Teknik Informatika Vol 13 No 2 (2021): Ultimatics : Jurnal Teknik Informatika Vol 13 No 1 (2021): Ultimatics : Jurnal Teknik Informatika Vol 12 No 2 (2020): Ultimatics : Jurnal Teknik Informatika Vol 12 No 1 (2020): Ultimatics : Jurnal Teknik Informatika Vol 11 No 2 (2019): Ultimatics : Jurnal Teknik Informatika Vol 11 No 1 (2019): Ultimatics : Jurnal Teknik Informatika Vol 10 No 2 (2018): Ultimatics : Jurnal Teknik Informatika Vol 10 No 1 (2018): Ultimatics : Jurnal Teknik Informatika Vol 9 No 2 (2017): Ultimatics : Jurnal Teknik Informatika Vol 9 No 1 (2017): Ultimatics: Jurnal Ilmu Teknik Informatika Vol 8 No 2 (2016): Ultimatics: Jurnal Ilmu Teknik Informatika Vol 8 No 1 (2016): Ultimatics: Jurnal Ilmu Teknik Informatika Vol 7 No 2 (2015): Ultimatics: Jurnal Ilmu Teknik Informatika Vol 7 No 1 (2015): Ultimatics: Jurnal Ilmu Teknik Informatika Vol 6 No 2 (2014): Ultimatics: Jurnal Ilmu Teknik Informatika Vol 6 No 1 (2014): Ultimatics: Jurnal Ilmu Teknik Informatika Vol 5 No 2 (2013): Ultimatics: Jurnal Ilmu Teknik Informatika Vol 5 No 1 (2013): Ultimatics: Jurnal Ilmu Teknik Informatika Vol 4 No 2 (2012): Ultimatics: Jurnal Ilmu Teknik Informatika Vol 4 No 1 (2012): Ultimatics: Jurnal Ilmu Teknik Informatika Vol 3 No 2 (2011): Ultimatics: Jurnal Ilmu Teknik Informatika More Issue