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INDONESIA
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.
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Articles 7 Documents
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Search results for , issue "Vol. 7 No. 3: December 2022" : 7 Documents clear
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.
User Experience in Learning Management System: Edmodo versus Google Classroom Hanifah Muslimah Az-zahra; Dini Nurhayati; Admaja Dwi Herlambang
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

Nowadays, Learning Management System (LMS) is widely used to support the learning process. LMS becomes a medium of interaction between students and teachers. Poor usability and user experience (UX) of an LMS can make students spend more time learning the system than learning the educational content. Therefore, usability and user experience evaluation are important for e-learning. Edmodo and Google Classroom are two widely used LMS. This study involved students as inspectors to compare the user experience of Edmodo versus Google Classroom using Technique for User Experience Evaluation in E-learning (TUXEL). Inspectors divided into two groups: one group inspected Edmodo and another group inspected Google Classroom. After completing the inspection, the inspectors were asked to fill three questionnaires: usability inspection, general LMS / pedagogical usability inspection, and user experience. The data then processed and analyzed per category per dimension. The results of the overall general usability and pedagogical usability inspections show fewer problematic aspects in Edmodo (22 items) than Google Classroom (30 items). However, Google Classroom seems to be preferred by students because it is simpler, practical and, more comfortable. Edmodo is recommended for distance learning since it has more features. While Google Classroom is more suitable to be used as a support or complement for a learning course.
Design of Soil Moisture Telemetry System Using cluster-based Wireless Sensor Networks Annisa Widuri Murti Utami; Dany Primanita Kartikasari; Adhitya Bhawiyuga; Reza Andria Siregar; Fariz Andri Bakhtiar
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

Agriculture is an art and science used to cultivate the land, grow crops, and raise livestock. Agricultural land in Indonesia has different soil quality in each region. Soil quality for agriculture can have an impact on crops. Therefore, a Wireless Sensor Network (WSN) was created to make it easier to determine soil moisture. This system can help to monitor the condition of soil moisture content. WSN applies a Cluster-Based Algorithm, and the protocol used in WSN is a Low Energy Adaptive Clustering Hierarchy (LEACH). WSN will search for the cluster head, and then the sensor node will send the results of soil moisture sensing data to the cluster head for further data aggregation. Then, the results of the aggregation data will be sent to the sink node and then forwarded to the cloud. Data aggregation can make the sink stay longer than 30 minutes than the sink node that receives data without aggregation. Sink nodes that do not receive aggregation data also use more load current than sinks that receive aggregation data. The test results of the average response time to find new cluster heads have an average time of 6023.4 milliseconds. The maximum distance between nodes to transmit data to each other is 100 meters.
Development of Electrocardiogram Signal Generator for Fibrillation Detector Ponco Siwindarto; Bill Jason; Adharul Muttaqin; Muhammad Nurrohman; Muhram Muis; Zainul Abidin
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

Fibrillation is one of the abnormalities in the heart where it beats irregularly, which can cause sudden death. Fortunately, these abnormalities can be detected using an electrocardiogram (ECG) fibrillation detector. An ECG can be detected as biopotential body signal that arises as a result of electrical activity of the heart muscle represented by the electrical signals consisting of P, Q, R, S and T waves that carry information about someone’s heart condition through graph pattern. However, a test in humans with the potential for fibrillation is needed to determine whether the fibrillation detector works correctly. Testing this way is ineffective because we cannot predict when and where a person will experience fibrillation. On the other hand, a site called PhysioNet provides various medical records from patients, including ECG signals of normal heartbeats, atrial fibrillations, and ventricular fibrillations. Because of the ineffectiveness of testing a fibrillation detector directly on a living person, this study focused on research to develop an ECG signal generator using microcontroller Arduino Due for reconstructing the heart signal in normal and fibrillated heart conditions collected from the PhysioNet database. The research focused on obtaining an R-peak value and RR interval time that resembled a heart ECG wave. This study compared the reconstructed signal with references from PhysioNet and measured the peak level of R and R-R interval time using an oscilloscope to calculate the accuracy of the ECG signal generator. The generated ECG signal during Atrial Fibrillation and Normal Sinus Rhythm has an overall accuracy of 88.65% for the R-peak level and 97.24% for the RR-Interval time. While Ventricular Fibrillation has been reproduced by achieving amplitude errors of less than 5.63% and 10.22% during first and second samples, respectively.
Cover and Table of Contens Lina Purbosari
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

Cover and Table of Contens

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