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INDONESIA
International Journal on Information and Communication Technology (IJoICT)
Published by Universitas Telkom
ISSN : 23565462     EISSN : -     DOI : -
Core Subject : Science,
International Journal on Information and Communication Technology (IJoICT) is a peer-reviewed journal in the field of computing that published twice a year; scheduled in December and June.
Arjuna Subject : -
Articles 44 Documents
Improving Network Security - A Comparison of Open Source DPI Software Satrya, Gandeva Bayu; Nugroho, Faiizal Eko; Brotoharsono, Tri
International Journal on Information and Communication Technology (IJoICT) Vol 2, No 2 (2016): December 2016
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21108/IJOICT.2016.22.77

Abstract

The classification of data traffic in a firewall using parameters such as port number, IP address, and MAC address is not sufficient. For example, currently, many applications can be used without a port number meaning they can easily circumvent a firewall. Firewalls inspecting up to only layer four could allow malicious data to pass. Next-generation deep packet inspection (DPI) is a method that can be used for firewalls as a method of classification up to layer seven in data traffic control.This research recommends the use of nDPI and L7-filter by network administrators on existing open source firewalls. Eleven internet applications were used to test and analyze nDPI and L7-filter which are capable of detecting traffic based on the data signature. nDPI and L7-filter were tested for accuracy and speed. We conclude that the development of next-generation deep packet inspection is important for the future of system and network security.
Usability Improvement based on Hierarchical Task Analysis (Case Study on i-Caring) Muttaqy, Muhammad Zafif; Kurniati, Angelina Prima; A.W, Yanuar Firdaus
International Journal on Information and Communication Technology (IJoICT) Vol 1, No 1 (2015): December 2015
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21108/IJOICT.2015.11.5

Abstract

i-Caring (IT Telkom i-Gracias Collaboration and e-learning) is an LMS (Learning Management System)-based e-learning integrated in i-Gracias own by IT Telkom Bandung. This application is being used to facilitate the implementation of learning activities supporting the face-to-face discussion in class. I-Caring supports some functionalities, such as instructional material storage, assignment, quizzes, and communication through chats and forum. But the great functionalities are not supported by an interactive interface, which is not comply to QUIM (Quality in Use Integrated Measurement) standard. This paper explains our research results of evaluation and recommendation process. This research is using Hierarchical Task Analysis (HTA) which has some indicators to analyze the behavior of a sample lecturers and students which are randomly selected. Based on the questionnaires answers, we analyze the relations of each points on HTA principles using SPSS Statistics 20 tools. The recommendations are then formulated to improve i-Gracias user interface quality.
Indonesian Vehicles Number Plates Recognition System Using Multi Layer Perceptron Neural Network and Connected Component Labelling Sitompul, Andre; Sulistiyo, Mahmud Dwi; Purnama, Bedy
International Journal on Information and Communication Technology (IJoICT) Vol 1, No 1 (2015): December 2015
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21108/IJOICT.2015.11.1

Abstract

In recent years, the amount of vehicle in Indonesia has been increasing rapidly. This surely, if it is conducted conventionally, challenges the upholder in recognizing and detecting the lawbreakers vehicle. The objective of this research aims to create the system which can automatically recognize vehicles number plates. This is also expected to be able to assist the upholder to take an action against the lawbreaker. The method used are sliding concentric windows and connected component for detecting and segmenting each of character on vehicles number plates. Further, multi-layer perceptron neural network classification model is used to identify each of character on it.The system has been tested using variety of vehicles number plate images and succesfully recognize 180 of 224 characters images (80.35%). Based on the computation of each character, the accuracy of the system, throughout tested vehicles number plate images, can reach 95.69% (1509 of 1577 characters can be identified).The tested system has shown prospective results, thus the technique used on this research can be implemented through vehicles number plate recognition system in Indonesia.
Brain Tumor Detection and Classification in Magnetic Resonance Imaging (MRI) using Region Growing, Fuzzy Symmetric Measure, and Artificial Neural Network Backpropagation Muhammad, Lugina; Dayawanti, Retno Novi; Rismala, Rita
International Journal on Information and Communication Technology (IJoICT) Vol 1, No 1 (2015): December 2015
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21108/IJOICT.2015.11.2

Abstract

Brain tumor is one type of malignant tumors that occurs because there is an abnormal and uncontrolled cell division activity. There are several ways to diagnose brain tumors, for example use MRI images. Through the MRI images, the radiologist can see the brain anatomy without performing surgery. However, this process is still done manually and could lead to misdiagnose. In addition, the different characteristics of brain tumor makes the diagnose more difficult. Therefore, we need a system of Computer-Aided Diagnostic (CAD) that will help radiologist in identifying brain tumors. In general, the CAD system consists of two major processes, namely image segmentation and feature extraction and classification. One example of segmentation is Region Growing that will classify the pixels based on certain criteria. However, the manual selection of seed point is a drawback of this method. The examples of feature extraction methods are Fuzzy Symmetric Measure (FSM), and First and Second Order Statistics. FSM values can be used to calculate the symmetry of the image brain, while the first and second order to represent feature in the image. As for the classification process, Artificial Neural Network Backpropagation method is widely used for its ability to resolve nonlinear dan complex problems.This research implements CAD system that uses Region Growing, Symmetric Fuzzy Measure, and Backpropagation Neural Network for detecting and classifying the brain tumors. In addition, the modification of converging square is conducted to select a seed point automatically. After testing, the system generates a 100% accuracy and BER is 0 in the case of distinguishing between normal and tumor brain. Besides, the average accuracy in classifying the types of brain tumors achieved 89.72% , the BER 0.1 for training data, and the average accuracy of 84.44%, BER 0.16 for the testing data.
Analysis and Implementation of Metode Collaborative Analysis Methods of Requirement and Design (CARD) on E-commerce Website in Indonesia Anggit K, Oktariantoro; Prima K, Angelina; Guslinar P, Erda
International Journal on Information and Communication Technology (IJoICT) Vol 1, No 1 (2015): December 2015
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21108/IJOICT.2015.11.3

Abstract

The development of internet in recent years caused a major prospect in online business. One of the businesses is e-commerce. E-commerce is an activity of selling and buying information through computer network. Website is a medium that can be used in e-commerce implementation. E-commerce website becomes an important part in supporting the companys success. Yet, there are many e-commerce websites that are not understandable by the user since the user cannot find out what they want. In addition, e-commerce website is still difficult to use. The users who cannot find what they want in e-commerce website will surely decrease the usability of the website. As a result, there must be a design planning which can be comprehended by the users to find the expected product easily. The Collaborative Analysis of Requirement and Design method can be used to solve the design problem. The method is one of the techniques in user centered design. The method focuses on users because in its process it involves the users, and the users are the the information source of this method. The information that is gained from the users can be taken form interview, questionairre and experimentation with component order. The result of this research gives contribution to the websites, that is advise to improve the website design so that the users can understand the working system and the design more comprehensively.
Electronic Product Feature-Based Sentiment Analysis Using Nu-SVM Method Juita S, J. Ratna; Hidayati, Hetti; Gozali, Alfian Akbar
International Journal on Information and Communication Technology (IJoICT) Vol 1, No 1 (2015): December 2015
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21108/IJOICT.2015.11.4

Abstract

Sentiment in a product online review is useful and influence decision-making a person may take in buying any product as well as that of organization in determining the number of product to produce. In an opinion, reviewer may provide positive and negative reviews at the same time that can be ambiguous. This is because opinion targets are often not the product as a whole; instead they are only part of a product called as feature, which have advantages and disadvantages based on the reviewers point of view. In this paper, the goal is to produce sentiment of a mobile phone opinion based on its feature. Opinion data used in this thesis are in English taken from www.cnet.com. Feature extraction is conducted by searching for phrases that match the dependency relation template, which is followed by feature filtering. The sentiment identification, positive and negative probability value, as well as target class label of the data preparation become the Nu SVM classifier input parameters. In the study of NU SVM, some data are treated as unlabeled data. The evaluation towards sentiment identification obtained from the study shows F1 Measure of 86.25% for positive class and 77.71% for negative class. The accuracy for feature identification, however, is 82%.
Sliced Coordinate List Implementation Analysis on Sparse Matrix-Vector Multiplication Using Compute Unified Device Architecture fitriyani, fitriyani
International Journal on Information and Communication Technology (IJoICT) Vol 2, No 1 (2016): June 2016
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21108/IJOICT.2016.21.71

Abstract

Matrices are one of the most used data representation form from real-world problems. Lot of matrix was formed very big but sparse, hence information inside the matrix is relatively small compared to its size. This caused into heavy computational resources needed to process those matrices within short time. One of the solutions to do an efficient process to the sparse matrix is to form it into a specialized form of sparse matrix, such as Sliced Coordinate List (SCOO). SCOO format for sparse matrix has been developed and combined within an implementation using Compute Unified Device Architecture (CUDA). In this research, performance of SCOO implementation using GPU – CUDA will be compared to the other sparse matrix format named Coordinate List (COO) based on its memory usage and execution time. Results obtained from this research show that although SCOO implementation for sparse matrix use memory 1.000529 larger than COO format, its serial performance is 3.18 faster than serial COO, besides that, if SCOO implementation is conducted parallel using GPU – CUDA then its performance can be achieved around 123.8 faster than parallel COO or 77 times faster than parallel COO using one of the available library for CUDA, named CUSP.
Comparative Study between Parallel K-Means and Parallel K-Medoids with Message Passing Interface (MPI) Nhita, Fhira
International Journal on Information and Communication Technology (IJoICT) Vol 2, No 2 (2016): December 2016
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21108/IJOICT.2016.22.86

Abstract

Data mining is a combination technology for analyze a useful information from dataset using some technique such as classification, clustering, and etc. Clustering is one of the most used data mining technique these day. K-Means and K-Medoids is one of clustering algorithms that mostly used because it’s easy implementation, efficient, and also present good results. Besides mining important information, the needs of time spent when mining data is also a concern in today era considering the real world applications produce huge volume of data. This research analyzed the result from K-Means and K-Medoids algorithm and time performance using High Performance Computing (HPC) Cluster to parallelize K-Means and K-Medoids algorithms and using Message Passing Interface (MPI) library. The results shown that K-Means algorithm gives smaller SSE than K-Medoids. And also parallel algorithm that used MPI gives faster computation time than sequential algorithm.
Sentiment Analysis on Twitter about the Use of City Public Transportation Using Support Vector Machine Method effendy, veronikha
International Journal on Information and Communication Technology (IJoICT) Vol 2, No 1 (2016): June 2016
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21108/IJOICT.2016.21.85

Abstract

Traffic jams that occur in big cities in Indonesia due to the increased use of private vehicles. One solution to overcome this problem is to increase the use of public transport. But, the existing public transport is still not much in demand by the community. Some people express their opinions regarding the use of city public transportation via Twitter.  The opinions can be processed as a sentiment analysis to determine the positive opinions and negative opinions. The opinion will then be analyzed to determine factors that are the main cause of the ineligibility use of public transport as well as the factors that make the public choose to use this type of transport. By upgrading of facilities and services based on the results of sentiment analysis, it is expected that people will switch to use city public transportation, which would reduce the traffic jam.  This research used SVM method to process sentiment analysis. The result has shown SVM accuracy reaches 78.12%, which indicates that the results of this reserach deserve to be considered.
CO2 Monitoring System Prototype using Wireless Sensor Network Wisesa, Hanif Arief
International Journal on Information and Communication Technology (IJoICT) Vol 2, No 2 (2016): December 2016
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21108/IJOICT.2016.22.127

Abstract

An abstract of no more than 200 words should state the purposes of the study, procedures, findings and conclusions. It should be written in Times New Roman with font size of 9. Abstract should be followed by four to eight key words to assist cross-indexing. The key words should be ordered alphabetically and separated by commas. For your paper to be published in the journal, you must use this document as both an instruction set and as a template into which you can type your own text. If your paper does not conform to the required format, you will be asked to fix it. In the paper, authors are suggested to present their articles in the sections structure: Introduction - Previous Study/Literature Review - The Proposed Method/Algorithm/Procedure specifically designed (optional) - Research Method Results and Discussion - Conclusion. Authors may present complex proofs of theorems or non-obvious proofs of correctness of algorithms after introduction section (obvious theorems and straightforward proofs of existing theorems are not needed).