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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
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E-Commerce Product Review Sentiment Analysis: A Comparative Study of Naïve Bayes Classifier and Random Forest Algorithms on Marketplace Platforms Hassolthine, Cian Ramadhona; Haryanto, Toto; Adline Twince Tobing, Fenina; Ikhwani Saputra, Muhammad
IJNMT (International Journal of New Media Technology) Vol 12 No 1 (2025): Vol 12 No 1 (2025): 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.v12i1.4246

Abstract

Achieving customer satisfaction and trust is a major challenge for success in the business world. Entrepreneurs must identify problems that arise from reviews given by customers. However, reading and sorting each review is time-consuming and considered inefficient. In order to overcome this, a study was conducted that aims to analyze sentiment on products sold in the Shopee marketplace using the Naïve Bayes Classifier and Random Forest algorithms. The focus of this study is on product reviews from XYZ Store. The main objective of this study is to determine a more accurate and efficient algorithm in classifying review sentiment, which can help companies in marketing strategies and product development. The results of this study can provide insight for companies about consumer responses to marketed products, so that they can be used as a basis for making strategic decisions to improve the quality of services and products. The results of the Random Forest method classification produce superior predictions compared to the Naïve Bayes Classifier method with an accuracy value of 92.5%, precision of 93%, Recall of 92.5% and F1-Score of 90%.
Personalized Restaurant Recommendations: A Hybrid Filtering Approach for Mobile Applications Marvelio, Christopher Matthew; Waworuntu, Alexander
IJNMT (International Journal of New Media Technology) Vol 12 No 1 (2025): Vol 12 No 1 (2025): 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.v12i1.4248

Abstract

Selecting a restaurant that suits your taste can be a major challenge for consumers, especially given the vast array of online dining options. Traditional recommendation systems or simple filtering methods often fail to handle this complexity well. To address these limitations, we developed a mobile app-based restaurant recommendation platform that combines content-based filtering and collaborative filtering methods in a hybrid approach. The application was built using Expo, React Native, Express, and Flask technologies. The evaluation was conducted using the End-User Computing Satisfaction (EUCS) framework, and the results showed a very high user satisfaction rate of 93.9%. This result shows that the recommendation system we developed is effective in providing relevant suggestions and is well received by users.
Monte Carlo Algorithm Applications in Shrimp Farming: Monitoring Systems and Feed Optimization Kurniawan, Vincentius; Herkristito, Atanasius Raditya; Prasetiyowati, Maria Irmina
IJNMT (International Journal of New Media Technology) Vol 12 No 1 (2025): Vol 12 No 1 (2025): 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.v12i1.4301

Abstract

Indonesia is one of the world’s leading maritime nations, ranking second in fishery export value in 2020 [1]. Shrimp stands out as the most lucrative commodity, with an export value of USD 1,997.49 million [2]. Feeding shrimp plays a vital role in their growth and cultivation; however, overfeeding can result in feed residue that negatively impacts the quality of pond water and represents the biggest operational after capital expenditure [3]. The profitability of shrimp farming heavily depends on the feeding cost. This study using the Monte Carlo algorithm to track feed in shrimp and provides an optimal feeding plan. The algorithm can be used to provide feed recommendations for shrimp start from 33 days of cultivation (DoC), with an best range around 85kg to 92kg. The findings show the potential of the Monte Carlo algorithm in enhancing feeding plan in shrimp farming industries. Index Terms— Cultivation; Feeding; Feed Recommendations; Margin; Monte Carlo; Operational Cost; Pond Water; Shrimp Farming
A Development of Learning Media in Fluids in Higher Education Based on Android Negara, Teguh Puja
IJNMT (International Journal of New Media Technology) Vol 10 No 2 (2023): IJNMT
Publisher : Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ijnmt.v10i2.3007

Abstract

The impact of the corona virus pandemic has disrupted all activities in Indonesia, especially in teaching and learning activities in universities. The lecture process has changed, such as the ban on face-to-face meetings, which has an impact on the learning system on campus. Therefore, the government has implemented an online learning system to overcome the massive spread of the virus while maintaining lectures. One of the issues at issue is practicum activities which require students to come directly to the laboratory, so a solution is needed, namely learning media that can support distance learning to remain effective. The learning media in this study used the Multimedia Development Life Cycle (MDLC) method using Frame by Frame, Low-poly modeling and Shader Graph techniques. The results of this study are an Android-based fluid case learning medium, where, in the application, users can try simulations in the form of 3D animations and work on practice questions and post-tests. Thus, users can better understand fluid materials without the need to do practical work in a physics laboratory.
Development of Web-Based Leave Management System for Telkom Delivery Department Crowdsource Employees in PT Sigma Cipta Caraka Sarungu, Cornelius Mellino; Baharizki, Frida; Kamila, Hana; Sugiharto, Via Alviola
IJNMT (International Journal of New Media Technology) Vol 10 No 2 (2023): IJNMT
Publisher : Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ijnmt.v10i2.3191

Abstract

Technology is one of the solutions that can bring automation to a process, with technology all processes can be more time efficient. This is necessary for some processes that were previously done manually. One of them is in Telkom Delivery's division at PT Sigma Cipta Caraka, a company that has some crowdsource employees, who have the right to take leave every year. The current system can still be used because it still sends leave application messages using e-mail, this also indicates that it is not integrated properly. The purpose of designing this leave application information system is to provide a solution to the problem of managing employee leave so that it can run more efficiently. The methods used in the data collection process to obtain user requirements are observation, interviews, and literature study. To support the development of this information system, the author uses several technologies, namely the Laravel framework and MySQL database using certain software development lifecycle (SDLC). This research results in a leave management web application for crowdsource employees in PT Sigma Cipta Caraka.
Examining the Impact of Platform Usage on Online Purchasing in E-commerce Halim, Fransiscus Ati; Djong, Darren Irawan; Usman, Sabrina Fajrul Ula
IJNMT (International Journal of New Media Technology) Vol 10 No 2 (2023): IJNMT
Publisher : Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ijnmt.v10i2.3211

Abstract

With the increasing number of consumers from diverse backgrounds engaging in online purchasing, e-commerce platforms such as Tokopedia, Shopee, TikTok Shop, and others play a significant role. This research aims to examine the influence of e-commerce platform usage on consumer preferences. A descriptive quantitative methodology was employed, utilizing a Google form questionnaire distributed among the researcher's immediate surroundings. The research findings indicate that several factors have a notable impact on users' preferences when making online purchases.
Voice Control Turn-Based Role Playing Game Development Using Unity Speech Recognition Sebastian, Sebastian; Dirgantara, Harya Bima
IJNMT (International Journal of New Media Technology) Vol 10 No 2 (2023): IJNMT
Publisher : Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ijnmt.v10i2.3380

Abstract

This research endeavors to create and develop a turn-based role-playing video game utilizing speech recognition as an innovative means to introduce a novel experience in video games. The game is designed and implemented using the Unity game engine. The game prototype produced in this study is intended to provide a unique experience when playing games, namely using voice recognition to try to beat opponents. The researcher adopts the Extreme Programming methodology, compassing four stages: Planning, Design, Develop and Testing/Release. The culmination of this research is a turn-based role-playing game featuring speech recognition controls intended for Windows computers equipped with a microphone. The game offers players fresh and innovative gameplay by incorporating speech recognition. Based on the closed beta trial on three respondents, the result was that there was an influence from the playing room. Two words are difficult for the game to detect: "molten spear" with an average detection rate of 40% and "chakra magic" with an average detection rate of 33%.
Implementation of Decision Support System Method to Evaluate Posyandu Program In Tangerang Selatan Desanti, Ririn Ikana; Maximus, Jason; Sitorus, Budi Berlinton
IJNMT (International Journal of New Media Technology) Vol 10 No 2 (2023): IJNMT
Publisher : Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ijnmt.v10i2.3451

Abstract

The goal of this study is to develop a decision support system (DSS) using the Technique for Order Preference by Similarity to Solution (TOPSIS) and Simple Multi-Attribute Rating Technique (SMART) approaches to evaluate the Posyandu Program. The case study focuses on Posyandu in Tangerang Selatan Regional. The local government runs Posyandu, an Indonesian public health service facility for women and children. This DSS system uses the TOPSIS approach to employ the ranking function and select the best alternative based on agreed-upon criteria with the local Posyandu. This approach calculates the distance between each option with a positive ideal solution and a negative ideal solution and then computes the relative preference value, which determines how to rank. In addition, the SMART approach assigns weights to each predefined criterion. Using the TOPSIS and SMART approaches to implement DSS at Posyandu helps people make decisions by providing them with the best ranking results based on predefined criteria. Thus, it is believed that the findings of this study would improve the quality of Posyandu services and contribute to the overall health of the community.
Implementation Analytical Hierarchy Process Algorithm for Design and Development Website Hero Mage Recommendation for Mobile Legends Lay, Ferry; Tobing, Fenina Adline Twince
IJNMT (International Journal of New Media Technology) Vol 10 No 2 (2023): IJNMT
Publisher : Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ijnmt.v10i2.3457

Abstract

Mobile Legends is a Multiplayer Online Battle Arena genre game that is currently hot. There are 122 heroes in Mobile Legends which are divided into 6 roles. The currently popular role is mage, where this mage role occupies 3 of the 5 most used in the MPL S11 tournament. Purchasing heroes can be done with a currency called battlepoints amounting to 32,000. The collection of battlepoints is limited to one week, and there is no refund feature for hero purchases, meaning that if the player makes the wrong hero purchase, the player has to collect the currency again to be able to buy another hero. The Mobile Legends mage hero recommendation system is a system that can provide assistance in purchasing heroes that suit user preferences. Recommendation results are provided based on input provided by the user and processed using the Analytical Hierarchy Process method. The evaluation results using the End User Computing Satisfaction method obtained a percentage of 88.64%, which indicates that the system has been well developed and can be used to provide mage hero recommendations for the Mobile Legends game.
The Potential of "GENIUS”: Deep Learning Integrated Application to Fight Obesity Rahadi, Putu Nindya Krisnadewi; Raharja, Ananda Eka; Haidir, Andi Ahmad
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.v11i1.3471

Abstract

Lifestyle changes regarding food consumption and sedentary lifestyle has led to increase prevalence of obesity worldwide, including in Indonesia. Obesity as a risk factor for various diseases has become an urgent issue considering that currently available therapies have not shown optimal results in overcoming this problem. The "GENIUS" application is present as a body types analysis system and program recommendations for obesity therapy. The purpose of writing this paper is to find out the potential, construction mechanism, and operating mechanism of the application. The methodology of writing this paper is literature review, based on secondary data from databases such as Google Scholar, PubMed, and ScienceDirect. The construction mechanism of the application includes process of collecting dataset, creating the application and deep learning system, and launching the application. The technology utilized in the application involves image processing deep learning and recurrent neural networks, enabling it to generate outputs suit to each individual's needs and provide appropriate program recommendations. Through the "GENIUS" application, users can also consult with medical professionals, receive recommendations, and record clinical data progress in a single digital application accessible via smartphones. The application also provides an interesting sub-feature in the form of reward points given to users for using the application's features. The implementation of the application involves the quadruple helix model. The benefits of the application encompass the fields of health and knowledge, aiming to prevent obesity in order to foster an intelligent generation and achieve a healthy Indonesia.

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