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IJoICT (International Journal on Information and Communication Technology)
Published by Universitas Telkom
ISSN : -     EISSN : 23565462     DOI : -
Core Subject : Science,
Computer Science & IT
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 5 Documents
 1 
Search results for , issue "Vol. 5 No. 2 (2019): December 2019" : 5 Documents clear
Tone Classification Matches Kodàly Handsign with the K-Nearest Neighbor Method at Leap Motion Controller Muhammad Croassacipto; Muhammad Ichwan; Dina Budhi Utami
International Journal on Information and Communication Technology (IJoICT) Vol. 5 No. 2 (2019): December 2019
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21108/IJOICT.2019.52.283

Abstract

Hands can produce a variety of poses in which each pose can have a meaning or purpose that can be used as a form of communication determined according to a general agreement or who communicate. Hand pose can be used as human interaction with the computer is faster, intuitive, and in line with the natural function of the human body called Handsign. One of them is Kodàly Handsign, made by a Hungarian composer named Zoltán Kodály, which is a concept in music education in Hungary. This hand sign is used in interactive angklung performances in determining the tone that will be played by the K-Nearest Neighbor (KNN) algorithm classification process based on hand poses. This classification process is performed on the extracted data from Leap Motion Controller, which takes Pitch, Roll, and Yaw values based on basic aircraft principle. The results of the research were conducted five times with the value of k periodically 1,3,5,7,9 with test data consisting pose of 874 Do', 702 Si, 913 La, 612 Sol, 661 Fa, 526 Mi, 891 Re, and 1004 Do punctuation on 21099 training data. The test results can recognize hand poses with the optimal k value k=1 with an accuracy level of 94.87%.
Basement Flood Control with Adaptive Neuro Fuzzy Inference System Using Ultrasonic Sensor Raden Muhamad Yuda Pradana Kusumah; Maman Abdurohman; Aji Gautama Putrada
International Journal on Information and Communication Technology (IJoICT) Vol. 5 No. 2 (2019): December 2019
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21108/IJOICT.2019.52.482

Abstract

This paper proposes a basement flood management system based on Adaptive Neuro Fuzzy Inference System (ANFIS). Basement is one of the main parts of a building that has a high potential for flooding. Therefore, the existence of a flood control system in the basement can be a solution to this threat. Water level control is the key to solving the problem. Fuzzy Inference System (FIS) has proven to be a reliable method in the control system but this method has limitations, that is, it needs to have a basis or a reference when determining the fuzzy set. When there is no basis or reference, Adaptive Neuro FIS (ANFIS) can be a solution. The Neuron aspect in ANFIS determines fuzzy sets through training data. In terms of the Internet of Things (IoT), this system uses an ultrasonic sensor, Node Red IoT platform, and Matlab Server.  Then the water pump will turn on to control the water level when there is rainfall. By undergoing a comparative test with the FIS method, ANFIS provides a lower Root Mean Square Error (RMSE) and is recommended for use in basement flood management systems.
Study the Best PenTest Algorithm for Blind SQL Injection Attacks Aldebaran Bayu Nugroho; Satria Mandala
International Journal on Information and Communication Technology (IJoICT) Vol. 5 No. 2 (2019): December 2019
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21108/IJOICT.2019.52.268

Abstract

There are several types of SQL injection attacks. One of the most popular SQL Injection Attacks is Blind SQL. This attack is performed by exploiting a gap in the database server when executing query words. If the server responds to an invalid query, the attacker will then reverse the engineering part of the SQL query, which is obtained from the error message of the server. The process of generating a blind SQL injection attack is complicated. As a result, a Pentester often requires a long time to penetrate the database server. This research provides solutions to the problems above by developing the automation of a blind SQL injection attack. The method used in this research is to generate keywords, such as the database name and table name so that the attacker can retrieve information about the user name and password. This research also compares several search algorithms, such as linear search, binary search, and interpolation search for generating the keywords of the attack. Automation of the Blind SQL Injection was successfully developed, and the performance of the keywords generation for each algorithm was also successfully measured, i.e., 1.7852 seconds for Binary Search, 1.789 seconds for interpolation and 1.902 seconds for Linear Search.
Design Recommendation Information Architecture of Hospital Website Using Bottom-Up Approach on Card Sorting Method Risqi Puspa Dewi; Mira Kania Sabariah; Veronikha Effendy
International Journal on Information and Communication Technology (IJoICT) Vol. 5 No. 2 (2019): December 2019
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21108/IJOICT.2019.52.190

Abstract

One of the public facilities that use websites is the hospital. However, there are some shortcomings complained by users related to the hospital website, which is the lack of information, confusing view of the menu, etc. Therefore, we need the information architecture to manage related content and website structure. The build of information architecture is done by using a bottom-up approach in card sorting. There are five stages in the research, which the first stage is a strategy to equalize the goal in the development of the hospital website either from the point of view of the organization or company and the user's point of view of the hospital website. The second stage is a scope to find out what are the needs of the user in order to build the hospital website. The third stage is structure, which is the formation of the initial structure of information architecture by using a bottom-up approach to the card sorting method. The type of card sorting that is commonly used is the open card sorting. The fourth stage is the skeleton stage, which is used to make information architecture model design using wireframe and prototype. The fifth stage is the test using findability testing and usability testing. From the test, the design of information architecture is made to fulfill the desires and needs of users, as proven by the results of findability testing achieved 15.9 seconds, and the results of usability testing achieved 80.33. Hence, by the results of these tests, it can be concluded that the design of information architecture at the hospital website has a good value from findability testing and usability testing.
Wrapper-Based Feature Selection Analysis For Semi-Supervised Anomaly Based Intrusion Detection System Andreas Jonathan Silaban; Satria Mandala; Erwid Jadied Mustofa
International Journal on Information and Communication Technology (IJoICT) Vol. 5 No. 2 (2019): December 2019
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21108/IJOICT.2019.52.209

Abstract

Intrusion Detection System (IDS) plays as a role in detecting various types of attacks on computer networks. IDS identifies attacks based on a classification data network. The result of accuracy was weak in past research. To solve this problem, this research proposes using a wrapper feature selection method to improve accuracy detection. Wrapper-Feature selection works in the preprocessing stage to eliminate features. Then it will be clustering using a semi-supervised method. The semi-supervised method divided into two steps. There are supervised random forest and unsupervised using Kmeans. The results of each supervised and unsupervised will be ensembling using linear and logistic regression. The combination of wrapper and semi-supervised will get the maximum result.

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