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
ultimainfosys@umn.ac.id
Editorial Address
-
Location
Kota tangerang,
Banten
INDONESIA
International Journal of New Media Technology
Published by Universitas Multimedia Nusantara
ISSN : 23550082     EISSN : 25811851     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering
International Journal of New Media Technology (IJNMT) is a scholarly open access, peer-reviewed, and interdisciplinary journal focusing on theories, methods, and implementations of new media technology. IJNMT is published annually by Faculty of Engineering and Informatics, Universitas Multimedia Nusantara in cooperation with UMN Press. Topics include, but not limited to digital technology for creative industry, infrastructure technology, computing communication and networking, signal and image processing, intelligent system, control and embedded system, mobile and web based system, robotics.
Arjuna Subject : -
Articles 175 Documents
 11   12   13   14   15 
Implementation of Support Vector Machine Method for Twitter Sentiment Analysis Related to Cancellation of u-20 World Cup in Indonesia Armanda, Muhammad; Tobing, Fenina Adline Twince
IJNMT (International Journal of New Media Technology) Vol 11 No 1 (2024): IJNMT (International Journal of New Media Technology)
Publisher : Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ijnmt.v11i1.3673

Abstract

The cancellation of the U-20 world cup in Indonesia in 2023 has become a hot debate among the Indonesian people because the reasons for the cancellation are still unclear. The number of pro and con opinions uploaded by the Indonesian people on twitter social media makes these opinions can be used as data to assess opinions which are divided into three categories, namely positive, negative and neutral. After being divided into three categories, sentiment analysis will then be carried out using the SVM method and comparing linear, polynomial and rbf kernels to get the best performance of existing kernels in the support vector machine method. By using confusion matrix to measure the performance of the classification, accuracy, precision, recall and f1-score can be assessed. It was found that the 80:20 data ratio had the highest accuracy of the linear, polynomial, rbf kernel and the rbf kernel had better results than the linear and polynomial kernels, namely Accuracy 78.15%, F1-Score, 76.30%, Precision 77.37% and Recall 75.58%. In addition, the data obtained also succeeded in analyzing Indonesian texts that were input externally and categorized into positive, neutral and negative. From the results that have been obtained, the support vector machine method has been successfully implemented in sentiment analysis of the U-20 world cup cancellation in Indonesia in 2023 on twitter social media
Avia Saga: A Gamified Mobile-Based Learning Management System Oswald, Putra Aldo; Gunawan, Dennis
IJNMT (International Journal of New Media Technology) Vol 11 No 1 (2024): IJNMT (International Journal of New Media Technology)
Publisher : Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ijnmt.v11i1.3675

Abstract

The usage of Learning Management Systems (LMS) has increased since the Covid-19 pandemic. LMS have drawbacks despite the advantages they provide. To fully support the advantages they provide, students must be motivated and involved. Adding gamification to the LMS is one way to potentially solve this issue. The MDA framework and Octalysis are combined in this research's gamification approach. The application, named Avia Saga, was designed and built using Flutter and Spring Boot as a mobile application. A trial of the application was conducted with 38 students majoring in Informatics. The evaluation of the application was done using the Hedonic-Motivation System Adoption Model (HMSAM) with a Likert scale. The research results revealed a 7% increase in the behavioral intention to use category, suggesting a greater inclination for reusing the application, and an 11.7% increase in the immersion category, indicating elevated sentiments of users being carried away by the ambiance while using the application.
The Effect of Using the Al-Mumtaz Application on Student Learning Outcomes UIN Mahmud Yunus Batusangkar Hidayat, Rahmat; Abidin, Munirul; Hilmi, Danial
IJNMT (International Journal of New Media Technology) Vol 11 No 2 (2024): Vol 11 No 2 (2024): IJNMT (International Journal of New Media Technology)
Publisher : Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ijnmt.v11i2.3614

Abstract

Abstract— In today's digital era, the utilization of technology in the learning process is becoming increasingly important. Online learning applications such as Al-Mumtaz have the potential to overcome the limitations of conventional learning methods and increase student interest and motivation to learn. However, the effect of using the Al-Mumtaz application on student learning outcomes at Mahmud Yunus State Islamic University Batusangkar has not been widely studied. This study aims to identify and analyze the effect of using the Al-Mumtaz application on student learning outcomes at UIN Mahmud Yunus Batusangkar and provide evidence-based recommendations regarding the effectiveness of digital learning applications. This study used a quantitative pre-experiment design with a sample of Arabic language education students who used the Al-Mumtaz application. Data were collected through initial and final tests, and analyzed using validity, reliability, normality, homogeneity, and paired t tests. The analysis showed that 10 out of 15 questions were valid and reliable. The data were normally distributed and met the assumption of homogeneity of variance. The paired t-test revealed a significant mean difference between the pre-test (62.50) and post-test (89.00) scores after the use of Al-Mumtaz application, with an increase of 23.50.The use of Al-Mumtaz application in Arabic language learning at UIN Mahmud Yunus Batusangkar provides significant results.This study confirms the positive effect of Al-Mumtaz application on student learning outcomes and highlights the importance of technology in improving the effectiveness of learning in the academic environment.
The Effect of Video Games Towards the Students' Academic Performance Lala, Yohanes Brian Caesaryano; Oetama, Raymond Sunardi; Lvina, Kimberly
IJNMT (International Journal of New Media Technology) Vol 11 No 2 (2024): Vol 11 No 2 (2024): IJNMT (International Journal of New Media Technology)
Publisher : Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ijnmt.v11i2.3638

Abstract

Video games have remained popular ever since the video game industry boom in the 1980s. It has remained popular, especially for children, teenagers, and adults. However, video games have also sparked controversies among the population. Concerns have been raised regarding the harmful effects of video games, particularly regarding addictions. Video games have been accused by many of being the cause of lowering academic performance. Therefore, this study aims to explore the relationship between video games and the overall academic performance of university students in depth. We applied several statistical methods using a questionnaire, which 100 university students filled out. The insights uncovered from this study may help determine if and how much video games affect the academic performance of university students.
Approach Convolutional Neural Network LeNet-5 for Interactive Learning of Korean Syllables (Hangul) Al Fitra Yudha, Vasyilla Kautsar; Kurniasari, Arvita Agus; Arifianto, Aji Seto; Afriansyah, Faisal Lutfi
IJNMT (International Journal of New Media Technology) Vol 11 No 2 (2024): Vol 11 No 2 (2024): IJNMT (International Journal of New Media Technology)
Publisher : Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ijnmt.v11i2.3705

Abstract

The increasing popularity of South Korean culture among Indonesian society has led to a growing interest in gaining a deeper understanding of the country, including a desire to master the Korean language. However, learning the Korean alphabet (hangul) often presents challenges due to its characters being unfamiliar to the Indonesian people. Therefore, engaging and interactive learning media are needed to assist in the learning process. Within this endeavor, a learning website called Learn Hangul was developed, focusing on two main features: learning hangul characters and their arrangement, as well as practicing writing syllables using Korean letters. This website was developed using the Convolutional Neural Network (CNN) LeNet-5 to facilitate learning, with black box testing results indicating good functionality. Model performance evaluation yielded satisfactory values, with model accuracy at 89.2%, precision at 89.7%, recall at 88.8%, and an F1-score of 89.2%. Direct testing with users also showed a high success rate, with 80% of respondents experiencing an increase in their knowledge of Korean characters (Hangul) after trying to learn them on the Learn Hangul website. Thus, the Learn Hangul website serves as a useful learning tool for those interested in studying the Korean alphabet (hangul).
Ensemble Learning - Random Forest Algorithm to Classify Obesity Level Abigail, Tesalonika; Overbeek, Marlinda Vasty
IJNMT (International Journal of New Media Technology) Vol 11 No 2 (2024): Vol 11 No 2 (2024): IJNMT (International Journal of New Media Technology)
Publisher : Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ijnmt.v11i2.3709

Abstract

Obesity is one of the serious global health problems caused by excessive accumulation of body fat. According to the World Health Organization (WHO), the prevalence of obesity has tripled in the last 40 years, with 650 million out of 1.9 billion overweight adults suffering from obesity. Obesity is a non-communicable disease that increases the risks of more dangerous diseases, such as heart disease and cancer. Therefore, early detection of obesity level is crucial. Currently, Body Mass Index (BMI) serves as a measurement indicator, but it tends to overestimate obesity for those with high muscle mass and vice versa, making it ineffective as it only relies on height and weight, without considering body composition and daily activities. To solve this, the best Random Forest model has been developed, selected based on the results of model selection after comparisons using feature selection and hyperparameter tuning. The selected model successfully improved accuracy by 1.4%, which then implemented into a web-based system to classify obesity levels. Evaluation of the model resulted in Precision, Recall, F1-Score, and Accuracy of 97%, 97%, 97%, and 96.8% respectively. Based on these evaluation results, it can be concluded that this system is highly effective in classifying obesity levels.
IMPLEMENTATION OF HEURISTIC EVALUATION METHOD FOR EVALUATION AND RECOMMENDATIONS UI/UX DESIGN IMPROVEMENTS ON THE CINEPOLIS WEBSITE Aristawati, Cindy; Tobing, Fenina Adline Twince; Surbakti, Eunike Endariahna; Peranginangin, Jimmy; Pinem, Anjar
IJNMT (International Journal of New Media Technology) Vol 11 No 2 (2024): Vol 11 No 2 (2024): IJNMT (International Journal of New Media Technology)
Publisher : Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ijnmt.v11i2.3736

Abstract

UI/UX is one of the most important elements of a website. One of the tasks of UI/UX is to make it easier to achieve a goal that the user wants. Cinépolis is a cinema that has been established in Indonesia since 2014. Cinépolis then launched its own website to make it easier for users to view movie information and order tickets. Based on the questionnaires that have been distributed and calculated using the System Usability Scale or SUS method, the Cinépolis website gets a score of 54.03 and is below the SUS standard of 68. The predicate obtained from the Cinépolis website is grade D with the predicate Poor. Heuristics are methods for finding interface problems to improve usability and user experience. The joint evaluation of 2 evaluators showed that there were 20 problems on the Cinépolis website based on 10 heuristic principles, while the evaluation of the Cinépolis website improvement prototype with 1 other evaluator found 5 problem findings based on 10 heuristic principles on the Figma prototype. The prototype that has been implemented gets a final score of 88.01 using the SUS calculation based on the questionnaire data that has been distributed. The final predicate obtained from the Cinépolis repair website is grade A with the predicate of Excellent.
Data Quality Issues : Case Study of Claim and Insured in Indonesia Insurance Company Solontio, Chris; Hidayanto, Achmad Nizar
IJNMT (International Journal of New Media Technology) Vol 11 No 2 (2024): Vol 11 No 2 (2024): IJNMT (International Journal of New Media Technology)
Publisher : Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ijnmt.v11i2.3755

Abstract

Data has become an asset for insurance companies that have many benefits and management needs to realize the importance of data quality to avoid the impact of poor data quality. In this study, data quality measurement will be carried out by observation to see the total amount of invalid data from data dimensions, namely, accuracy, completeness and consistency of the relationship between claim data and insured, and findings from each data fields in this case study. In addition, researchers conducted interviews to find out the obstacles faced by IT, Customer Retention, Operational, and Actuary teams where they are directly related to data flow and data processing. From the results of the analysis, there is invalid data that will affect the analysis and cause obstacles faced by users according to the interview results. In the conclusion, management needs to form a data govenance team to avoid poor data quality that has responsibility for data flow and maintains data quality in order to provide a positive impact such as providing the right data accuracy in data analysis and user time to be more effective in data processing, assisting in making data warehouses, applying AI and digital transformation as a form of improvement in the services provided.
Evaluating the Impact of Particle Swarm Optimization Based Feature Selection on Support Vector Machine Performance in Coral Reef Health Classification Bastiaans, Jessica Carmelita; Hartojo, James; Pramunendar, Ricardus Anggi; Andono, Pulung Nurtantio
IJNMT (International Journal of New Media Technology) Vol 11 No 2 (2024): Vol 11 No 2 (2024): IJNMT (International Journal of New Media Technology)
Publisher : Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ijnmt.v11i2.3761

Abstract

This research explores improving coral reef image classification accuracy by combining Histogram of Oriented Gradients (HOG) feature extraction, image classification with Support Vector Machine (SVM), and feature selection with Particle Swarm Optimization (PSO). Given the ecological importance of coral reefs and the threats they face, accurate classification of coral reef health is essential for conservation efforts. This study used healthy, whitish, and dead coral reef datasets divided into training, validation, and test data. The proposed approach successfully improved the classification accuracy significantly, reaching 85.44% with the SVM model optimized by PSO, compared to 79.11% in the original SVM model. PSO not only improves accuracy but also reduces running time, demonstrating its effectiveness and computational efficiency. The results of this study highlight the potential of PSO in optimizing machine learning models, especially in complex image classification tasks. While the results obtained are promising, the study acknowledges several limitations, including the need for further validation with larger and more diverse datasets to ensure model robustness and generalizability. This research contributes to the field of marine ecology by providing a more accurate and efficient coral reef classification method, which can be applied to other image classifications.
Enhancing Support Vector Machine Classification of Nutrient Deficiency in Rice Plants Through Particle Swarm Optimization-Based Feature Selection Hartojo, James; Bastiaans, Jessica Carmelita; Pramunendar, Ricardus Anggi; Andono, Pulung Nurtantio
IJNMT (International Journal of New Media Technology) Vol 11 No 2 (2024): Vol 11 No 2 (2024): IJNMT (International Journal of New Media Technology)
Publisher : Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ijnmt.v11i2.3762

Abstract

The research focuses on the classification of nutrient deficiencies in rice plant leaves using a combination of Support Vector Machine (SVM) and Particle Swarm Optimization (PSO) methods for feature selection. Image features are extracted using Histogram of Oriented Gradients (HOG), which is then optimized with PSO to select the most relevant features in the classification process. Indonesia is one of the largest rice producers in the world, with food security as a major issue that requires sustainable solutions, especially in the agricultural sector. The growth and yield of rice plants are highly dependent on the availability of nutrients such as Nitrogen (N), Phosphorus (P), and Potassium (K). However, traditional observation methods to detect nutrient deficiencies in plants become inefficient as the scale of production increases. The dataset used includes images of rice leaves showing nitrogen (N), phosphorus (P), and potassium (K) deficiencies. Experiments show that the SVM model optimized with PSO provides a classification accuracy of 83.19% and a runtime of 129.63 seconds with 1150 best feature combinations out of 2303 extracted features, which is higher accuracy and faster runtime than the model that does not use PSO. These results show that the integration of PSO in the feature selection process not only improves the accuracy of the model, but also reduces the required computation time. This research makes an important contribution to the development of an automated system for the classification of nutrient deficiencies in crops, which can be implemented in large farms or other agricultural fields.

Page 13 of 18 | Total Record : 175

 11   12   13   14   15 

Filter by Year

2017 2025


Reset
Filter By Issues
All Issue Vol 12 No 2 (2025): Vol 12 No 2 (2025): IJNMT (International Journal of New Media Technology) Vol 12 No 1 (2025): Vol 12 No 1 (2025): IJNMT (International Journal of New Media Technology) Vol 11 No 2 (2024): Vol 11 No 2 (2024): IJNMT (International Journal of New Media Technology) Vol 11 No 1 (2024): IJNMT (International Journal of New Media Technology) Vol 10 No 2 (2023): IJNMT Vol 10 No 1 (2023): IJNMT Vol 9 No 2 (2022): IJNMT : International Journal of New Media Technology) Vol 9 No 1 (2022): IJNMT (International Journal of New Media Technology) Vol 8 No 2 (2021): IJNMT (International Journal of New Media Technology) Vol 8 No 1 (2021): IJNMT (International Journal of New Media Technology) Vol 7 No 2 (2020): IJNMT (International Journal of New Media Technology) Vol 7 No 1 (2020): IJNMT (International Journal of New Media Technology) Vol 6 No 2 (2019): IJNMT (International Journal of New Media Technology) Vol 6 No 1 (2019): IJNMT (International Journal of New Media Technology) Vol 5 No 2 (2018): IJNMT (International Journal of New Media Technology) Vol 5 No 1 (2018): IJNMT (International Journal of New Media Technology) Vol 4 No 2 (2017): IJNMT (International Journal of New Media Technology) Vol 4 No 1 (2017): IJNMT International Journal of New Media Technology More Issue