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JUTI: Jurnal Ilmiah Teknologi Informasi
Published by Institut Teknologi Sepuluh Nopember Surabaya
ISSN : 24068535     EISSN : 14126389     DOI : http://dx.doi.org/10.12962/j24068535
Core Subject : Health, Science, Education,
Computer Science & IT Dentistry Education Library & Information Science
JUTI (Jurnal Ilmiah Teknologi Informasi) is a scientific journal managed by Department of Informatics, ITS.
Arjuna Subject : -
Articles 389 Documents
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ENHANCEMENT OF DECISION TREE METHOD BASED ON HIERARCHICAL CLUSTERING AND DISPERSION RATIO Setyawan, Dimas Ari; Fatichah, Chastine
JUTI: Jurnal Ilmiah Teknologi Informasi Vol. 18, No. 2, July 2020
Publisher : Department of Informatics, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j24068535.v18i2.a1005

Abstract

The classification process using a decision tree is a classification method that has a feature selection process. Decision tree classifications using information gain have a disadvantage when the dataset has unique attributes for each imbalanced class record and distribution. The data used for decision tree classification has 2 types, numerical and nominal. The numerical data type is carried out a discretization process so that it gets data intervals. Weaknesses in the information gain method can be reduced by using a dispersion ratio method that does not depend on the class distribution, but on the frequency distribution. Numeric type data will be dis-criticized using the hierarchical clustering method to obtain a balanced data cluster. The data used in this study were taken from the UCI machine learning repository, which has two types of numeric and nominal data. There are two stages in this research namely, first the numeric type data will be discretized using hierarchical clustering with 3 methods, namely single link, complete link, and average link. Second, the results of discretization will be merged again then the formation of trees with splitting attributes using dispersion ratio and evaluated with cross-validation k-fold 7. The results obtained show that the discretization of data with hierarchical clustering can increase predictions by 14.6% compared with data without discretization. The attribute splitting process with the dispersion ratio of the data resulting from the discretization of hierarchical clustering can increase the prediction by 6.51%.
IMPLEMENTATION OF BLUETOOTH LOW ENERGY TECHNOLOGY AND TRILATERATION METHOD FOR INDOOR ROUTE SEARCH Rizaldi, Bahri; Pambudi, Doni Setio; Bariyah, Taufiqotul
JUTI: Jurnal Ilmiah Teknologi Informasi Vol. 18, No. 2, July 2020
Publisher : Department of Informatics, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j24068535.v18i2.a897

Abstract

Currently, route search is made easier by the presence of a Global Positioning System (GPS) technology that can be used by using the Maps application on a smartphone. By using the Maps application, people can find out their current location and can find a route to their desired destination. But the level of GPS accuracy will decrease if the user is in a building or in a closed room. This is caused by the satellite signals being sent that are not able to penetrate thick walls or concrete so that the search for routes using GPS is limited to the search for routes outside the building or outdoors. In this research, Bluetooth Low Energy and trilateration are used to determine the location in a room or building and Dijkstra's algorithm for finding the shortest route to the destination location. The proposed method has a location determination error of 0.728 meters with a distance between the user and the beacon less than 10 meters to get a stable signal.
EFFECTIVENESS STUDIES OF THE LEARNING BASIC MATHEMATICAL OPERATIONS ON USERS USING EDUCATION GAMES WITH ESCALATING DIFFICULTY LEVEL IN SEVERAL TYPES OF GAMES Nafis, Ari Mahardika Ahmad; Herumurti, Darlis
JUTI: Jurnal Ilmiah Teknologi Informasi Vol. 18, No. 2, July 2020
Publisher : Department of Informatics, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j24068535.v18i2.a989

Abstract

Mathematic is basic but fundamental knowledge, but in fact many students do not have the motivation to learn it because they think mathematic is boring. Therefore, an innovation is needed to motivate students, one of them is by using an educational game. Racing, shooting and fighting games are the most popular types of games in 2019 according to InvisionCommunity. Shooting game is a genre that used a lot in the educational games for learning math, while racing game and fighting game are not used much for educational games. This research aims to develop and measure the effectiveness of the games from these three genre of games as a means of learning elementary arithmetic at the elementary school level. The effectiveness of an educational game can be observed from the increment in learning outcomes obtained after conducting an experiment. We can know the most effective type of game in this experiment by compare the improvement in learning outcomes after playing all three games. The comparative analysis will be carried out using ANOVA. In this research, we used data from 60 participant with elementary level of education between grade 1 to 3. The results were obtained by calculating the difference in the participants' initial scores obtained from before playing the game and participants’ final scores obtained after playing the educational game. The results show that educational racing games have the highest increase of 6.3% compared to shooter games with 3% increase or fighting games with increase of 4.3%.
EFFICIENCY OF FLOODING BY DEVELOPING RELIABLE SUBNETWORK METHODS ON FIBBING ARCHITECTURE IN THE HYBRID ENVIRONMENT SDN Prakoso, Dino Budi; Ijtihadie, Royyana Muslim; Ahmad, Tohari
JUTI: Jurnal Ilmiah Teknologi Informasi Vol. 19, No. 1, Januari 2021
Publisher : Department of Informatics, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j24068535.v19i1.a1009

Abstract

In the technology world especially in the field of current network of Autonomous Systems connectivity (AS) is indispensable. Especially against the dynamic routing protocols that are often used compared to static routing protocols. In supporting this current network, it takes efficient and effective routing protocols capable of covering a sizable scale. Software Defined Network (SDN) is a technological innovation in the network world that has a separate Control Plane and Data Plane that makes it easy to configure on the Control Plane side. Control Plane is the focal point on a process of bottleneck in SDN architecture. Performance is a critical issue in large-scale network implementations because of the large demand load occurring in the Control Plane by generating low throughput value. This research will be conducted testing on the Hybrid network of SDN by using OSPF routing protocol, based on the Fibbing architecture implemented on the system network Hybrid SDN also able to assist in improving performance, but there are constraints when sending flooding which is used as a fake node forming. Many nodes are not skipped as distribution lines in the formation of a fake node, in which case it will certainly affect the value of throughput to be unstable and decrease. This can be overcome by using the Isolation Domain method to manage the LSA Type-5 flooding efficiency.
IMPERSONATION METHOD ON AUTHORIZATION SERVER USING CLIENT-INITIATED BACK-CHANNEL AUTHENTICATION PROTOCOL Akbar, Rizky Januar; Ariyani, Nurul Fajrin; Azhar, Adistya; Andra, Andika
JUTI: Jurnal Ilmiah Teknologi Informasi Vol. 19, No. 1, Januari 2021
Publisher : Department of Informatics, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j24068535.v19i1.a1022

Abstract

There is an impersonation (login as) feature in several applications that can be used by system administrators who have special privileges. This feature can be utilized by development and maintenance teams that have administrator rights to reproduce errors or bugs, to check specific features in applications according to the specific users’ login sessions. Beside its benefits, there is a security vulnerability that allows administrators to abuse the rights. They can access users’ private data or execute some activities inside the system without account or resource owners’ consents.This research proposes an impersonation method on authorization server using Client-Initiated Back-channel Authentication (CIBA) protocol. This method prevents impersonation without account or resource owners’ consent. The application will ask users’ authentication and permission via authentication device possessed by resource owners before the administrator performs impersonation. By utilizing authentication device, the impersonation feature should be preceded by users’ consent and there is no direct interaction needed between the administrator and resource owners to prove the users’ identities. The result shows that the implementation of CIBA protocol can be used to complement the impersonation method and can also run on the authorization server that uses OAuth 2.0 and OpenID Connect 1.0 protocols. The system testing is done by adopting FAPI CIBA conformance testing.
MODIFIED LOCAL TERNARY PATTERN WITH CONVOLUTIONAL NEURAL NETWORK FOR FACE EXPRESSION RECOGNITION Zulkarnain, Syavira Tiara; Suciati, Nanik
JUTI: Jurnal Ilmiah Teknologi Informasi Vol. 19, No. 1, Januari 2021
Publisher : Department of Informatics, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j24068535.v19i1.a1031

Abstract

Facial expression recognition (FER) on images with illumination variation and noises is a challenging problem in the computer vision field. We solve this using deep learning approaches that have been successfully applied in various fields, especially in uncontrolled input conditions. We apply a sequence of processes including face detection, normalization, augmentation, and texture representation, to develop FER based on Convolutional Neural Network (CNN). The combination of TanTriggs normalization technique and Adaptive Gaussian Transformation Method is used to reduce light variation. The number of images is augmented using a geometric augmentation technique to prevent overfitting due to lack of training data. We propose a representation of Modified Local Ternary Pattern (Modified LTP) texture image that is more discriminating and less sensitive to noise by combining the upper and lower parts of the original LTP using the logical AND operation followed by average calculation. The Modified LTP texture images are then used to train a CNN-based classification model. Experiments on the KDEF dataset show that the proposed approach provides a promising result with an accuracy of 81.15%.
IMPROVED DEEP LEARNING ARCHITECTURE WITH BATCH NORMALIZATION FOR EEG SIGNAL PROCESSING Purnomo, Adenuar; Tjandrasa, Handayani
JUTI: Jurnal Ilmiah Teknologi Informasi Vol. 19, No. 1, Januari 2021
Publisher : Department of Informatics, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j24068535.v19i1.a1023

Abstract

Deep learning is commonly used to solve problems such as biomedical problems and many other problems. The most common architecture used to solve those problems is Convolutional Neural Network (CNN) architecture. However, CNN may be prone to overfitting, and the convergence may be slow. One of the methods to overcome the overfitting is batch normalization (BN). BN is commonly used after the convolutional layer. In this study, we proposed a further usage of BN in CNN architecture. BN is not only used after the convolutional layer but also used after the fully connected layer. The proposed architecture is tested to detect types of seizures based on EEG signals. The data used are several sessions of recording signals from many patients. Each recording session produces a recorded EEG signal. EEG signal in each session is first passed through a bandpass filter. Then 26 relevant channels are taken, cut every 2 seconds to be labeled the type of epileptic seizure. The truncated signal is concatenated with the truncated signal from other sessions, divided into two datasets, a large dataset, and a small dataset. Each dataset has four types of seizures. Each dataset is equalized using the undersampling technique. Each dataset is then divided into test and train data to be tested using the proposed architecture. The results show the proposed architecture achieves 46.54% accuracy for the large dataset and 93.33% accuracy for the small dataset. In future studies, the batch normalization parameter will be further investigated to reduce overfitting.
IMPLEMENTATION OF JOHNSON'S SHORTEST PATH ALGORITHM FOR ROUTE DISCOVERY MECHANISM ON SOFTWARE DEFINED NETWORK Segara, Akbar Pandu; Ijtihadie, Royyana Muslim; Ahmad, Tohari
JUTI: Jurnal Ilmiah Teknologi Informasi Vol. 19, No. 1, Januari 2021
Publisher : Department of Informatics, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j24068535.v19i1.a1011

Abstract

Software Defined Network is a network architecture with a new paradigm which consists of a control plane that is placed separately from the data plane. All forms of computer network behavior are controlled by the control plane. Meanwhile the data plane consisting of a router or switch becomes a device for packet forwarding. With a centralized control plane model, SDN is very vulnerable to congestion because of the one-to-many communication model. There are several mechanisms for congestion control on SDNs, one of which is modifying packets by reducing the size of packets sent. But this is considered less effective because the time required will be longer because the number of packets sent is less. This requires that network administrators must be able to configure a network with certain routing protocols and algorithms. Johnson's algorithm is used in determining the route for packet forwarding, with the nature of the all-pair shortest path that can be applied to SDN to determine through which route the packet will be forwarded by comparing all nodes that are on the network. The results of the Johnson algorithm's latency and throughput with the comparison algorithm show good results and the comparison of the Johnson algorithm's trial results is still superior. The response time results of the Johnson algorithm when first performing a route search are faster than the conventional OSPF algorithm due to the characteristics of the all pair shortest path algorithm which determines the shortest route by comparing all pairs of nodes on the network.
LITERATURE REVIEW IOT SOFTWARE ARCHITECTURE ON AGRICULTURE Junaidi, Junaidi; Bramantya, Amirullah Andi; Pradipta, Bintang Satya
JUTI: Jurnal Ilmiah Teknologi Informasi Vol. 19, No. 1, Januari 2021
Publisher : Department of Informatics, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j24068535.v19i1.a962

Abstract

Context – Internet of Things (IoT) interrelates computing devices, machines, animals, or people and things that use the power of internet usage to utilize data to be much more usable. Food is one of the mandatory human needs to survive, and most of it is produced by agriculture. Using IoT in agriculture needs appropriate software architecture that plays a prominent role in optimizing the gain. Objective and Method – Implementing a solution in a specific field requires a particular condition that belongs to it. The objectives of this research study are to classify the state of the art IoT solution in the software architecture domain perspective. We have used the Evidence- Based Software Engineering (EBSE) and have 24 selected existing studies related to software architecture and IoT solutions to map to the software architecture needed on IoT solutions in agriculture. Result and Implications – The results of this study are the classification of various IoT software architecture solutions in agriculture. The highlighted field, especially in the areas of cloud, big data, integration, and artificial intelligence/machine learning. We mapped the agriculture taxonomy classification with IoT software architecture. For future work, we recommend enhancing the classification and mapping field to the utilization of drones in agriculture since drones can reach a vast area that is very fit for fertilizing, spraying, or even capturing crop images with live cameras to identify leaf disease.
SELENIUM FRAMEWORK FOR WEB AUTOMATION TESTING: A SYSTEMATIC LITERATURE REVIEW Thooriqoh, Hazna At; Annisa, Tiara Nur; Yuhana, Umi Laili
JUTI: Jurnal Ilmiah Teknologi Informasi Vol. 19, No. 2, Juli 2021
Publisher : Department of Informatics, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j24068535.v19i2.a1021

Abstract

Software Testing plays a crucial role in making high-quality products. The process of manual testing is often inaccurate, unreliable, and needed more than automation testing. One of these tools, Selenium, is an open-source framework that used along with different programming languages: (python, ruby, java, PHP, c#, etc.) to automate the test cases of web applications. The purpose of this study is to summarize the research in the area of selenium automation testing to benefit the readers in designing and delivering automated software testing with Selenium. We conducted the standard systematic literature review method employing a manual search of 2408 papers, and applying a set of inclusion/exclusion criteria the final literature included 16 papers published between 2009 and 2020. The result is using Selenium as a UI for web automation, not only all of the app functionality that has been tested, But also it can be applied with added some method or other algorithms like data mining, artificial intelligence, and machine learning. Furthermore, it can be implemented for security testing. In the future research for selenium framework automation testing, the implementation should more focus on finding effective and maintainability on the application of Selenium in other methodologies and is applied with the better improvement that can be matched for web automation testing.

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