Tangerang, Indonesia
Tangerang, Indonesia

Universitas Multimedia Nusantara—abbreviated UMN-- is a private university located in Gading Serpong, Tangerang, Banten, Indonesia. The university was founded by Kompas Gramedia Group on 25 November 2005 and officially launched in a ceremony at the Hotel Santika, Jakarta on 20 November 2006. Wikipedia.


Time filter

Source Type

Leonardo B.,Multimedia Nusantara University | Hansun S.,Multimedia Nusantara University
Indonesian Journal of Electrical Engineering and Computer Science | Year: 2017

Plagiarism is an act that is considered by the university as a fraud by taking someone ideas or writings without mentioning the references and claimed as his own. Plagiarism detection system is generally implement string matching algorithm in a text document to search for common words between documents. There are some algorithms used for string matching, two of them are Rabin-Karp and Jaro-Winkler Distance algorithms. Rabin-Karp algorithm is one of compatible algorithms to solve the problem of multiple string patterns, while, Jaro-Winkler Distance algorithm has advantages in terms of time. A plagiarism detection application is developed and tested on different types of documents, i.e. doc, docx, pdf and txt. From the experimental results, we obtained that both of these algorithms can be used to perform plagiarism detection of those documents, but in terms of their effectiveness, Rabin-Karp algorithm is much more effective and faster in the process of detecting the document with the size more than 1000 KB. © 2017 Institute of Advanced Engineering and Science. All rights reserved.


Iswari N.M.S.,Multimedia Nusantara University
Proceedings of 2016 8th International Conference on Information Technology and Electrical Engineering: Empowering Technology for Better Future, ICITEE 2016 | Year: 2016

RSA is an algorithm for public-key cryptography and is considered as one of the great advances in the field of public key cryptography. RSA security lies in the difficulty of factoring large number into prime factors. The inventor of RSA Algorithm suggests prime number that is used to generate the keys have more than 100 digits' length for security reasons. Elgamal algorithm also is one of public key cryptography algorithm. The security of this algorithm lies in the difficulty of calculating discrete logarithm. In this paper, the author proposes key generation algorithm that is considered safe from the combination of the RSA and Elgamal algorithm. Based on the experiment that has been done, the computing time required for the proposed algorithm is relatively short, compared to the original RSA algorithm. © 2016 IEEE.


Hansun S.,Multimedia Nusantara University
Proceedings - 2016 6th International Annual Engineering Seminar, InAES 2016 | Year: 2016

Moving average as one of popular technical indicator used to predict data in time series analysis has grown significantly. There are many researchers who have develop moving average methods resulting in its' many derivatives methods. Two of them are Weighted Exponential Moving Average (WEMA) and Holt's Weighted Exponential Moving Average (H-WEMA) methods. This research aims to conduct a comparative study on WEMA and H-WEMA methods which are said to excel the other conventional moving average methods. Therefore, we will implement both methods to predict Jakarta Stock Exchange (JKSE) composite index data and then calculate the accuracy and robustness level using Mean Square Error (MSE) and Mean Absolute Percentage Error (MAPE) criteria. The results from the experiments taken show that H-WEMA has a better accuracy and robustness levels compared to other moving average methods. © 2016 IEEE.


Tunggawan E.,Multimedia Nusantara University | Soelistio Y.E.,Multimedia Nusantara University
Proceeding - 2016 International Conference on Computer, Control, Informatics and its Applications: Recent Progress in Computer, Control, and Informatics for Data Science, IC3INA 2016 | Year: 2016

This paper describes a Naive Bayesian predictive model for 2016 U.S. Presidential Election based on Twitter data. We use 33,708 tweets gathered since December 16, 2015 until February 29, 2016. We propose a simple way for data preprocessing which can still achieve 95.8% accuracy on predicting sentiments. The predicted sentiments are used to forecast the U.S. Republican and Democratic parties candidacies. The forecast is compared to the poll collected from RealClearPolitics.com with 26.7% accuracy. However, the true forecasting capacity of the method still have to be observed after the election process come to conclusion. © 2016 IEEE.


Kuntarto G.P.,Multimedia Nusantara University | Gunawan D.,Multimedia Nusantara University
2012 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2012 - Proceedings | Year: 2012

Internet is an important component in technology development, including tourism. Tourism is an industry which involves much information needed for traveling. Many tourists search for travel information in the web. Nevertheless, the web often gives irrelevant information. Besides that, a huge size of information in the web and the spread of the information in many different sources make users need more time in searching for information and organizing them from many different sources manually. Semantic web is a solution to solve those problems by providing knowledge based on an ontology. E-tourism is a good domain for implementing the semantic web because there are many information sources and data exchange involved in the e-tourism. In this paper, a knowledge base which is based on an ontology is designed and built using Protégé tool version 3.4.7. The ontology consists of tourism domain-specific information and stores data of accommodation, attraction, and cultural event in Bali which is one of the main travel destinations in Indonesia. Besides that, a search engine application for e-tourism in Bali, which implements the semantic web, is designed and built using RAP-RDF version 0.9.6 and RDF query language: SPARQL so that the search results conform to the ontology. © 2012 Universitas Indonesia.


Catherine C.,Multimedia Nusantara University
2013 International Conference on New Media Studies, CoNMedia 2013 | Year: 2013

Apart from the widely used of manual surveillance system, surveillance system with operator still has many drawbacks. Increased mobility and capability of computing devices require surveillance system that no longer just an intermediary function for observing surveillance area but also serves to facilitate the work of the operator. This paper discuss about implementation of Background Subtraction algorithm on image stream from Web camera to detect any motion. Motion detection without involving human operator aims for automated surveillance system. Intrusion notification will be delivered directly to user's email inbox for any motion occurs. Automated surveillance system and the use of the Web camera could be used as an alternative for low-cost automated surveillance systems. © 2013 Universitas Multimedia Nusantara.


Hansun S.,Multimedia Nusantara University
2013 International Conference on New Media Studies, CoNMedia 2013 | Year: 2013

Moving Average is one of widely known technical indicator used to predict the future data in time series analysis. During its' development, many variation and implementation have been made by researchers. One of its' widely used variation is Exponential Moving Average (EMA). Basically, EMA is an improvement of Weighted Moving Average (WMA) that gives a special weighting to more recent data than the older data, which could not be found in Simple Moving Average (SMA) method. This paper aims to introduce a new approach of moving average method in time series analysis. The approach will combine the calculation of weighting factor in WMA and EMA as the new weighting factor. To test the accuracy and robustness of the proposed method, it will be implemented on Jakarta Stock Exchange (JKSE) composite index data. The result of the proposed method shows a promising result in this preliminary work. © 2013 Universitas Multimedia Nusantara.


Ranny,Multimedia Nusantara University
ICIMSA 2016 - 2016 3rd International Conference on Industrial Engineering, Management Science and Applications | Year: 2016

Voice recognition process is started with voice feature extraction using Mel Frequency Cepstrum Coefficient (MFCC). The purpose of the MFCC method is to get the signal feature that correlate to the human voice. The converted signal from analog to digital is needed in the MFCC method. The digital signal has a time domain and it make the analysis harder. So, the domain time is converted to time domain for make the analysis more accurate. Furthermore, after get the feature, the recognition step is using k Nearest Neighbor (kNN) method with k number is one. Euclidean Distance is used to get the similarity of the data training and data testing. The previous research shows that kNN has a high accuracy if use normal data, but it has lower accurate when using outlier data. Base on this problem, this research develop a new method to handle the outlier data using kNN and double distance measurement. The double distance method is note each distance of each data to the center of the kNN data. The calculation of the distance is used on recognition step. The accuracy of the method is tested on experiment. The experiment is using 11 subjects as data training and data testing. Each voice of subject is recorded three times. The result of the experiment with kNN method with one data center is 84.85% and the experiment result using double distance measurement is 96.97%. The result shows that the double distance method increase the accuracy of voice recognition. © 2016 IEEE.


This essay provides a comparative study on aesthetic between 3D stop-motion animation and 3D Computer graphic animation. These two animation forms produced in different pipelines and outcomes. Highlighting key aesthetic principles of animation and fueled by statements that written by Power who underlines the importance of expressiveness in animation and engagement of viewer's emotion, author draws two clusters for comparing these two animation practices. The first cluster explores physicality and tactility; and the second cluster discusses perfection and imperfection of both animation practices. This essay aimed to contribute insight on comparative study of aesthetic between diverse animation forms from technical, visual and craft perspectives that have not yet explored by academic or practicing animators. © 2015 IEEE.


Hansun S.,Multimedia Nusantara University
Proceedings of 2013 International Conference on Robotics, Biomimetics, Intelligent Computational Systems, ROBIONETICS 2013 | Year: 2013

This paper aims to implement fuzzy time series as a forecasting method in Jakarta Stock Exchange (JKSE) composite index using percentage change as the universe of discourse. Since Chen and Hsu introduced a new method to forecast enrollments in the University of Alabama, a number of methods have been proposed for forecasting the same subject, such as Jilani, Burney, and Ardil, and Stevenson and Porter. In this paper, the approach of Stevenson and Porter is modified and implemented on another subject, i.e. JKSE composite index. The result of this approach in forecasting JKSE composite index, which is an indicator of stock price changes in Indonesia, shows a promising result. © 2013 IEEE.

Loading Multimedia Nusantara University collaborators
Loading Multimedia Nusantara University collaborators