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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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Implementation of Model View Controller Architecture in Object Oriented Programming Learning Ester Lumba; Alexander Waworuntu
IJNMT (International Journal of New Media Technology) Vol 8 No 2 (2021): 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.v8i2.2429

Abstract

This study aims to provide an overview of the application of software design patterns, namely Model View Controller (MVC) in object-oriented programming learning. In the software development industry, most application development uses frameworks. MVC architecture is a design pattern that is widely used by various frameworks. Students as prospective programmers or software developers must master and be able to translate object-oriented programming concepts into programming languages. In this study, the Java programming language is used to apply the object-oriented concept and implement the MVC architecture. This research resulted in an increase in students' programming skills and abilities as well as being able to apply the MVC architecture in developing applications using Java.
Application Of Dynamic Segmentation In Stroke Detection Software With ANN Hastie Audytra; Julian Supardi; Abdiansah Abdiansah
IJNMT (International Journal of New Media Technology) Vol 8 No 2 (2021): 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.v8i2.2439

Abstract

One way to find out whether there is a stroke is to do a CT scan . But the results of the examination with a new CT scan can be obtained in quite a long time. In addition, sometimes there are differences of opinion between doctors and radiologists regarding what is seen from the results of the examination. This research was conducted to produce a software that can later be integrated with the existing system on the CT Scan tool so that it can immediately be known whether or not stroke is present from the CT Scan results. In this study, a dynamic image segmentation method is implemented, namely the watershed transformation method which will later produce regions as a feature for the stroke detection process carried out with the backpropagation algorithm. From experiments conducted on CT scan images of the brain, this method can detect stroke well. The results obtained are 100% for training data and 90% for test data.
Prototype Project SCADA on Hemodialysis Mixing Tank Operation Dede Furqon Nurjaman
IJNMT (International Journal of New Media Technology) Vol 8 No 2 (2021): 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.v8i2.2465

Abstract

Pharmaceutical companies are an example of an industrial sector that uses technology-based systems in its production process. In this research the author will develop a SCADA (Supervisory Control Acquisition Data) system as a platform to solve several problems that are present in pharmaceutical production, namely in the drug production process using hemodilysis mixing tanks. The method that the author uses for this research is experimental research and data collection methods, which use the independent variables of the study, water level control and temperature control, while the independent variables related to the system reading results are displayed on the SCADA screen. Based on the results of mathematical calculations, it can be concluded that the production process using the SCADA system produces a more efficient time with a total time difference of 38 minutes/batch. Operations using SCADA technology within 24 hours were able to produce 4 batches of Infusion Bags, while using the conventional system only 3 batches. Operational needs using SCADA technology will generate more benefits in terms of cost and time, creating more effective and efficient work system for the company.
Optimization of Process Variables in 3D Printing on Dimensional Accuracy Using Nylon Filaments Hasdiansah Hasdiansah
IJNMT (International Journal of New Media Technology) Vol 9 No 1 (2022): 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.v9i1.2398

Abstract

Abstract—Manufacturing process over the past 50 years has led to very rapid and continuous progress in the manufacturing industry, one of the manufacturing processes that has progressed is 3D printing technology. The type of filament used in this research is nylon filament. This study aims to obtain optimal process parameters for dimensional accuracy. The method used in this study is the Taguchi L27 OA method. The process parameters used are nozzle temperature, bad temperature, layer thickness, flowrate, printing speed, overlap, infill density, infill speed, wall thickness. The results showed that the optimal process parameters are nozzle temperature(256°C), bad temperature(96°C), layer thickness(0.2mm), flowrate(90%), printing speed(30mm/s), overlap (10%), Keywords: 3D printing; Accuracy; Dimensions; Nylon; Parameter;
The Design of Microcontroller Based Early Warning Fire Detection System for Home Monitoring Hery Hery; Calandra Alencia Haryani; Aditya Rama Mitra; Andree Emmanuel Widjaja
IJNMT (International Journal of New Media Technology) Vol 9 No 1 (2022): 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.v9i1.2405

Abstract

Fire is a type of disaster that can occur anytime and anywhere as a result of any accidental or intentional causes. Without exception, houses are also very vulnerable to fire. To anticipate the catastrophic effects of fire that can destroy houses, advanced technology, such as the Internet of Things (IoT) can be utilized to detect the smoke and fire. This study aims to design an early warning fire detection system for home monitoring using smoke detection sensors based on Arduino microcontroller together with NodeMCU ESP8266. This early warning fire detection system is expected to function by notifying homeowners when detecting the presence of smoke in their homes. With the aid of this detection system, the issue of potential damage, death, or material loss caused by fire can be significantly reduced. The results and testing of the designed system will be discussed in the paper.
Bibliographic Computer Science Indexing Review with Disease Covid 19 Andrianingsih Andrianingsih; Tri Wahyu Widyaningsih; Meta Amalya Dewi
IJNMT (International Journal of New Media Technology) Vol 9 No 1 (2022): 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.v9i1.2509

Abstract

Abstract - Researchers in conducting their research use the search using the homepage of the publication, according to expertise, collaboration in research, and research interests. And at this time the Covid 19 pandemic, became a trending topic for researchers, in various scientific fields. This study classifies based on publications located on the homepage source namely Scopus and Google Scholar, by analyzing the following topics, namely Natural Language Processing, Text Mining, Remote Sensing, and Sentiment Analysis using Name Entity Recognition to detect and classify named entities in text and using occurrence and link strength methods. The results showed science index literature about diseases Covid 19, obtained that Scopus has the most equitable percentage, has a good occurrence and link strength among the five scientific fields, namely Natural Language Processing 23.81%.33%, Text Mining 19.05%%, Remote Sensing 0 %, Sentiment Analysis 57.14 % then Google Scholar Natural Language Processing 51.35%, Text Mining 0 %, Remote Sensing 48.65 %, Sentiment Analysis 0 % Index Terms : Information Extraction; Bibliographic indexing; Disease Covid 19
Implementation of OCR and Face Recognition on Mobile Based Voting System Application in Indonesia Inggrid Fortuna; YAMAN KHAERUZZAMAN
IJNMT (International Journal of New Media Technology) Vol 9 No 1 (2022): 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.v9i1.2658

Abstract

Elections are a form of democratic practice in Indonesia. Every 5 years an election will be held to elect a president. People who have been able to take part in the election will come to the polling station (TPS) to channel their voting rights. However, this conventional method proved ineffective because some people who were unable to attend due to certain situations for example, traveling out of town, did not want to queue, and experienced illness or physical disability. Therefore, this study aims to design an online voting system based on Android as an alternative to conventional elections and digital transformation in the voting method in Indonesia. The system will use Optical Character Recognition technology by firebase ml-kit to read Identification Number on the Identity Card and face recognition technology to compare the faces of voters during registration and during online elections. The Face Recognition system is implemented using Multi-task Convolutional Neural Network to detect faces and using Tensorflowlite to translate the facial model provided by the FaceNet model. Results Research shows the success of the OCR system is 96.67% and the accuracy of face recognition is 100%. The accuracy of OCR ml-kit and face detection using Multi-task Convolutional Neural Network and Face Recognition using tensorflowlite and FaceNet models proved to be 100% successful.
Analysis Sentiment Cyberbullying In Instagram Comments with XGBoost Method Muhamad Riza Kurniawanda; Fenina Adline Twince Tobing
IJNMT (International Journal of New Media Technology) Vol 9 No 1 (2022): 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.v9i1.2670

Abstract

Technological developments make social media widely used by the general public, which causes negative impacts, one of which is cyberbullying. Cyberbullying is an act of insulting, humiliating another person on social media. A system that can detect cyberbullying because of the large amount of information circulating on social media is impossible for humans to visit. One suitable method to solve this problem is Extereme Gradient Boosting (XGBoost). XGBoost was chosen because it can run 10 times faster than other Gradient Boosting methods. The process of changing sentences into vectors uses the TF-IDF method. The TF/IDF method is known as a simple but relevant algorithm in doing words on a document. XGBoost accepts input in the form of vectors obtained from the TF-IDF process. In this research, there are 1452 comments which will be broken down into training data and testing data. By using XGBoost and TF-IDF methods, the accuracy is 75.20%, precision is 71%, recall is 87%, and F1-score is 78%.
Analysis and Design of QR Code Based Information System on Plant Identification Ahmad Syaikhu; Rizky M. L. Soeryaprawira; Yoga A. Daswara; Cornelius Mellino Sarungu
IJNMT (International Journal of New Media Technology) Vol 9 No 2 (2022): 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.v9i2.2570

Abstract

At the location of the environmental service dormitory in RW 04 Tegal Alur sub-district, Kalideres district, West Jakarta, the community cultivate various types of plants and there is a requirement to introduce or educate the public about types of plants and their benefits. The purpose of this research project is to analyze the needs, as well as to design the QR Code-based information system, especially in the process of educating the types of plants and their benefits in the area. The design process uses the object-oriented analysis and design (OOAD) method which explores UML modelling (use case, activity diagram, sequence diagram, class diagram). The analysis will be carried out on to be implemented business processes, then the results of the analysis are poured into the design of a QR code-based information system in the form of web and mobile app that can assist educational activities. Web application will be used by the administrator to manage data to be displayed in mobile app. Mobile app will be used by the user to explore plant species and their benefits based on QR code that installed near the plants.
Implementation of Backpropagation Method with MLPClassifier to Face Mask Detection Model Wendy Hendra Wijaya; Raymond Sunardi Oetama; Fransiscus Ati Halim
IJNMT (International Journal of New Media Technology) Vol 9 No 2 (2022): 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.v9i2.2693

Abstract

Corona Virus Disease 2019 (COVID-19) is a virus that has spread widely and has become a global pandemic. The virus also can be spread through droplets made from coughs or sneezes. The Minister of Health of the Republic of Indonesia has issued a decision regarding this COVID-19 pandemic case, one of which is "Using personal protective equipment in the form of a mask that covers the nose and mouth to the chin”. This research aim is to detect masks on the face using the CRISP-DM framework and the backpropagation neural network method with MLPClassifier. The dataset is using RMFD (Real-World Masked Face Dataset. The dataset contains photos of human faces using mask and human faces without using mask. The result showed that the backpropagation neural network method can be used to detect mask on human faces with 94.4% accuracy. The accuracy from this research is outperform DNN algorithm. This research is expected to broaden the insight regarding the detection of masks to prevent the spread of COVID-19.

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