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Journal of Information Technology and Computer Science
Published by Universitas Brawijaya
ISSN : 25409433     EISSN : 25409824     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering
The Journal of Information Technology and Computer Science (JITeCS) is a peer-reviewed open access journal published by Faculty of Computer Science, Universitas Brawijaya (UB), Indonesia. The journal is an archival journal serving the scientist and engineer involved in all aspects of information technology, computer science, computer engineering, information systems, software engineering and education of information technology. JITeCS publishes original research findings and high quality scientific articles that present cutting-edge approaches including methods, techniques, tools, implementations and applications.
Arjuna Subject : -
Articles 194 Documents
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Cancer Classification Based on the Features of Itemset Sequence Pattern of TP53 Protein Code Using Deep Miden - KNN Marji Marji; Imam Cholissodin; Dian Eka Ratnawati; Edy Santoso; Nurul Hidayat
Journal of Information Technology and Computer Science Vol. 7 No. 1: April 2022
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jitecs.202271401

Abstract

Cancer is a disease that is still difficult to identify up to today. One of the causes of cancer is genetic modification that because of mutations in p53 gene. Healthy cells have a p53 wild type protein (normal) that is able to manage DNA separation. If DNA mutates, it will be difficult to detect cancer because the composition of the protein has changed. Bioinformatics is a combination of biology and information engineering (TI) that is utilized to manage data. One of the applications of data mining in bioinformatics is the development of pharmaceutical and medical industries. Data mining classification can use variety of methods including K-Nearest Neighbor (KNN), C45, ID3, and several other methods. One of the most reliable data classification methods is KNN. In this study, the development used two algorithms. The first was with the modification of the k-fold method, which divided two data into training data and test data, in which test-1 data and test-2 data were made into slices. The second was by a method for selecting an itemset sequence pattern that had the largest Gain Information, either 2 itemsets, 3 itemsets, and so on (Deep Miden). The best accuracy result of 96.00% was obtained through the process of computation testing in the server based on variations in terms of the number of patterns of Deep Miden itemset sequences and several k values on KNN classification method.
Big Data Review of East Java Community Compliance Index Against the Recommendation of Stay At Home During the Covid-19 Pandemic Firman Afrianto; Annisa Dira Hariyanto
Journal of Information Technology and Computer Science Vol. 7 No. 2: August 2022
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

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Abstract

The Covid-19 pandemic period provides a change in the framework of discovering community mobility patterns as the basis for determining policies to control the spread of the virus. Big Data then becomes one of the indicators in finding mobility patterns because, while doing their activities, the internet and social media users continuously carry out even when staying at home. The Indonesian government controls the spread by issuing the Large-Scale Social Restrictions (PSBB) policy in 2020 and the Enforcement of Restrictions on Community Activities (PPKM) in 2021 and 2022. East Java Province is confirmed to have the highest level of COVID-19 spread in Indonesia, so it requires a pattern of proper handling to control its spread. This study provides information on the compliance index to the stay-at-home recommendations during the PSBB and PPKM periods. Wherefrom the Big Data analysis and Nighttime Light satellite imagery, the highest level of compliance occurred during PPKM in February 2022. Also, in general, the compliance index of the people of East Java is increased.
User Requirements Analysis of Digital-Based Solutions for Supporting Disabilities using User Journey Map (Case Study of PSLD Brawijaya University) Yusriyah Rahmah; Ismiarta Aknuranda; Dian Eka Ratnawati
Journal of Information Technology and Computer Science Vol. 7 No. 2: August 2022
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

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Abstract

Disability is any condition of the body or mind that makes it more difficult for the person with the condition to do certain activities and interact with the world around them. Persons with disabilities need assistance in various fields related to their limitations to improve their quality of life. Either area that needs to be optimized to fulfill the rights of persons with disabilities is inclusive education. Brawijaya University supports inclusive education by establishing an organizational institution called Pusat Studi dan Layanan Disabilitas Universitas Brawijaya (PSLD UB). PSLD UB provides peer tutoring services by involving non-disabled students (volunteers) to assist students with disabilities during academic activities. So far, the process of implementing peer tutoring has often encountered problems due to schedule changes or other unexpected activities, causing schedule mismatches between volunteers and students with disabilities. To fulfill disability rights, it’s necessary to have a digital solution in peer tutoring activities, while to design the solution it’s necessary to analyze the right user requirements. Therefore, the purpose of this research is to analyze user requirements to optimize user experience, so that developers can use it to develop peer tutoring systems. This study applies a User Journey Map to analyze user requirements to know the description of the user's steps in achieving the goal. The selection of respondents was based on purposive sampling technique with the criteria of respondents who had carried out the peer tutoring process. From the results of this study, it was found three main features that suit user requirements are automatic replacement, emergency requests, and list of available volunteers.
Dynamics of Urban Heat Island and Anthropogenic Emissions in Bekasi before and during COVID-19 Pandemic using Landsat 8 and Sentinel-5P Ramanatalia Parhusip; Iqbal Putut Ash Shidiq; Jarot Mulyo Semedi
Journal of Information Technology and Computer Science Vol. 7 No. 2: August 2022
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

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Abstract

The rise in temperature in urban areas resulting in UHI formation is thought to be significantly driven by anthropogenic emissions due to human activities. During the COVID-19 pandemic, the Indonesian government issued the Large-Scale Social Restrictions (PSBB) and Community Activities Restrictions Enforcement (PPKM) policy. Bekasi Regency is part of the Jabodetabek megapolitan that applied strict PSBB and PPKM treatment during the pandemic. The decreasing industrial activity and traffic volume are expected to reduce air pollutants and thermal radiation. The research method uses processed satellite imagery from Sentinel 5P to get anthropogenic emissions concentrations (NO2 and SO2) and Landsat 8 to get land surface temperature (LST). The results showed that Bekasi had a slight decrease in the concentration of anthropogenic emissions during COVID-19 pandemic 2020, then increased during COVID-19 pandemic 2021. The areas affected by urban heat islands increased steadily during the COVID-19 pandemic. Therefore, when the concentration of anthropogenic emissions rises, the UHI ascends.
Qualitative Analysis of the SNS Role in Information Avoidance from the Perspective of S-O-R (Stimulus-Organism-Response) Theory Rahmania Kumalasari; Diah Priharsari; Ismiarta Aknuranda
Journal of Information Technology and Computer Science Vol. 7 No. 2: August 2022
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

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Abstract

Today, many people and organizations use SNS to disseminate information regarding COVID-19. However, information avoidance can still occur if users refuse to receive the information. Although previous research on information avoidance has been conducted, this research brings novelty by showing that the SNS design leads to information avoidance from the opinion and human behavior perspective. Therefore, this study analyzed the role of SNS in information avoidance from the perspective of SOR theory qualitatively. This research was conducted in Indonesia, which has the most significant SNS users on subjects who feel the impact of information overload and anxiety. It aimed to comprehend the phenomenon's effect on SNS users and the factors driving information avoidance. This research provided two contributions from the thematic analysis process. The first was to show the conceptual model of information avoidance related to the factors driving information avoidance and information anxiety from the perspective of SOR theory. The second was to provide knowledge about the impact of SNS on user behavior.
A Study on Sound Analysis Algorithm for Heart Sounds using YOLO Deep Learning Model Hiroki Tamura; Praveen Nuwantha Gunaratne; Hiromu Takeguchi; Hiroyuki Fukumoto; Yoshifumi Hashiguchi
Journal of Information Technology and Computer Science Vol. 7 No. 2: August 2022
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

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Abstract

As Japan’s population ages, the demand for home medical care is increasing. And, as the demand for home medical care increases, the burden on medical personnel becomes a problem. One of the ways to promote home medical care is to spread the use of medical equipment in households. However, since some medical knowledge is required to use basic medical equipment, it is considered difficult to spread the use of medical equipment among general households. Therefore, it demands the necessity to develop a medical device that can give the same decision as a medical doctor by using an algorithm. In this paper, we study the construction of an algorithm for an AI stethoscope that can make the same decisions as a medical doctor. We combine a frequency analysis method using three features and an image processing method using an image that represents the frequency features by wavelet transform. Using the results of each of these methods, we aim to improve the identification rate through machine learning techniques. The Random Forest training yields an identification rate of 94.68 ％ on the dataset of this paper.
Multihop Routing Implementation On Fire And Gas Leakage Detection System Benediktus Kevin Mulia; Mochammad Hannats Hanafi Ichsan; Rakhmadhany Primananda
Journal of Information Technology and Computer Science Vol. 7 No. 2: August 2022
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

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Abstract

Fires in the house occur due to several things, such as an electrical short circuit, and another cause is a gas leak from the LPG cylinder. This fire is caused by a lack of security in the house and public knowledge, the dangers of gas levels leaking from LPG gas cylinders, the presence of small fires, and temperatures too high due to these. Fire detectors and LPG gas leaks are provided in the home environment. This detection includes preventive efforts before a fire occurs and can be extinguished immediately. The method of the fire and gas leak detection prototype using the MQ-6 sensor, fire sensor and DHT-22 temperature sensor is multihop routing. This method was chosen because of the large number of sensors used, and in this prototype, there will be five sensor nodes and one sink node. With multihop routing, the prototype of this tool can be placed in various places and is faster in detecting fires if they occur in homes. This method is also used because it can send detection results from one sensor node to the sink node to the website database and the delivery time between these nodes is very short so that fires can be prevented and handled quickly. The test results of the fire sensor used to detect fire obtained an accuracy of 100%, and the detection distance of the fire was between 20 to 100 cm. In data transmission, the number of nodes is 5. The data delivery result is the closest to the end node, the more considerable the amount of data sent, increasing relatively, from around 3017 milliseconds to 575387 milliseconds.
Early Stunting Detection System for Toddlers Based on Height and Weight Using Backpropagation Neural Network Method Dini Eka Ristanti; Dahnial Syauqy; Barlian Henryranu Prasetio
Journal of Information Technology and Computer Science Vol. 7 No. 3: December 2022
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

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Abstract

Stunting is a chronic nutritional problem characterized by height and weight problems. Toddlers who have height and weight of more than minus 2 standard deviations are at risk of suffering from stunting and require monitoring for 3 to 6 consecutive months. Currently, the system still measures toddlers' height and weight, then matches it with the World Health Organization(WHO) growth data table. Therefore, we proposed to develop a system to detect height and weight as well as the risk of stunting in toddlers using an ultrasonic sensor, load cell, and backpropagation algorithm. In its implementation, the ultrasonic sensor achieves an accuracy of 99%, and the load cell reaches 93%. The system uses backpropagation neural network method, which achieved an R of 0.99845 using 3 inputs, 16 hidden layers,1 layer for re-weighting, and 1 output layer. The mean squared error reaches 0.01 with 2 prediction classes, low risk, and high riskstunting. Overall, the total system accuracy can reach 97.75%.
Analysis of OLSR Routing Protocol Performance Based on Gauss-Markov Mobility and Random Walk in Mobile Ad-Hoc Network (MANET) Heru Nurwarsito; Ervani Sofyana Putra
Journal of Information Technology and Computer Science Vol. 7 No. 3: December 2022
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

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Abstract

MANET is included in the network without infrastructure from a collection of nodes that are interconnected to communicate. Routing protocol performance is a measure of the performance of how the ability of the routing protocol works. A routing protocol is needed where the routing table information must be kept up to date at regular intervals such as Optimized Link State Routing (OLSR). MANET is dynamic, so node mobility increases the risk of node failure. Gauss-Markov and random walk are mobility that has a significant impact on the performance of the routing protocol. This study analyzes the effect of mobility on the OLSR protocol in MANET topology using Network Simulator 3.25 with packet delivery ratio (PDR) parameters, end to end delay and routing overhead. The test scenario is done by varying the number of nodes as many as 20, 40, 60, and 80 nodes as well as the minimum and maximum speed of nodes 0-5 m/s, 5-10 m / s, 10-15 m/s, and 15-20 m/s. PDR results show the highest value on Gauss-Markov with 80 nodes and a minimum and maximum speed of 10-15 m/s of 69.36%. The best end to end delay results is seen in Gauss-Markov with 20 nodes and a minimum and maximum speed of 15-20 m/s of 10.22 ms. The routing overhead results display the best value on a random walk with 20 nodes and a minimum and maximum speed of 0-5 m/s of 8100 packets.
The Effect of Student's Family Environment and Learning Interests on Learning Outcomes in The Computer Programming Subject at Vocational High School's Distance Learning Context Ervyn Vania Riswara; Admaja Dwi Herlambang; Tri Afirianto
Journal of Information Technology and Computer Science Vol. 7 No. 3: December 2022
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

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Abstract

During the Covid-19 pandemic, the learning process was carried out remotely in each home using a learning platform that had been determined by the school. In the current situation to support the quality of the student learning process at home, a good family environment is needed so that students get good learning outcomes. Distance learning can also affect student interest in learning, due to the lack of interaction and lack of socialization between teachers and students, and many other factors affect student interest in learning. So the researcher wants to calculate how the influence of the family environment and student interest in learning during the pandemic period on the learning outcomes of class X RPL students of SMK Negeri 9 Malang in Basic Programming subjects. This study uses quantitative research along with correlational methods with a sample of 101 students of class X RPL SMK Negeri 9 Malang. The research data obtained comes from the results of distributed questionnaires and documentation. The data analysis used is the regression test, correlation test, T-test and F test using SPSS 25 software. From the research that has been done, the results are (1) there is an influence by the family environment on student learning outcomes with a significance value of 0.047 < 0.05 , (2) interest in learning affects learning outcomes with a significance value obtained at 0.001 < 0.05, (3) family environment and interest in learning simultaneously affect student learning outcomes with a significance value of 0.000 < 0.05.

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