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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 10 Documents
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Search results for , issue "Vol. 9 No. 1: April 2024" : 10 Documents clear
Simple and Cost-Effective Detection of Carbon Monoxide Gas Setyawati, Onny; Iswanjaya, Septian; Abidin, Zainul; Bahr, Andreas
Journal of Information Technology and Computer Science Vol. 9 No. 1: April 2024
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jitecs.202491567

Abstract

In several major cities throughout Indonesia, the air pollution represents a significant issue. The escalation of motorized vehicle usage yields increased concentrations of carbon monoxide gas, as one of the primary sources of gas pollution. This study introduced a tool designed and implemented for detecting levels of carbon monoxide gas and providing accurate indications. The tool used an MQ-7 gas sensor in combination with a dot matrix display for this purpose.  The detection apparatus was comprised of an IC 74HC595, an ATMEGA16 microcontroller, a BC557 PNP transistor, and a LED dot matrix. The ATMEGA16 microcontroller served as the primary control device of the system. It received input signals from the MQ-7 gas sensor and subsequently converted them into digital format for display on the dot matrix. The IC 74HC595 and transistor BC557 were utilized as the column controller and line controller, respectively, in the 5x8 LED dot matrix.  The gas level measurement at 0 cm exhibited the lowest error of approximately 0.6 %, measuring 300 ppm CO gas levels. On the other hand, at 10 cm, the result showed approximately an error of 6.7 % for a CO gas level of 200 ppm.
Development of Moodle-based Plugin for Automated Essay-Type Grading Pradana, Fajar; Purnomo, Welly; Adillah, Atthoriq; Hanggara, Buce Trias
Journal of Information Technology and Computer Science Vol. 9 No. 1: April 2024
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jitecs.202491573

Abstract

The essay is an exam requiring a more profound understanding of answering and evaluating the answers. However, if the number of questions and participants increases, this will result in a decrease in the quality of the lecturer's assessment. This prompted the development of a software based on the Moodle plugin named Essay Similarity to assess essay answers based on the similarity between the two documents, namely the answers given and the answer key provided. Moodle was chosen because, after the Covid-19 pandemic, many sectors have shifted to working remotely, including the education sector. This resulted in an LMS like Moodle experiencing an increase in users. As of 2020 yesterday, Moodle users have exceeded 190 million users on more than 145,000 websites. In developing this plugin, the method used is the waterfall method using the PHP programming language. The algorithm used to find similarities between the two documents is cosine similarity. Testing the level of similarity between manual and automatic grading was carried out on four models of essay questions. Based on the test results, the average similarity between automatic grading compared to manual grading is 45.44%.
Identifying The Influence of Consumer Purchase Intention Through Live Streaming Shopping: A Systematic Literature Review Mindiasari, Irtiyah Izzaty; Priharsari, Diah; Setiawan, Budi Darma; Purnomo, Welly
Journal of Information Technology and Computer Science Vol. 9 No. 1: April 2024
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jitecs.202491576

Abstract

The rapid development of technology influences some changes in e-commerce. One of them is the emergence of live-streaming shopping, which combines live-streaming technology with e-commerce, social networking, and entertainment. This shopping format allows viewers to interact with the streamer (seller) and instantly make a purchase with just one touch. Consumers who watch live streaming shopping generally are those who initially have an interest in the offered product. According to prior studies, the presence of live shopping can enhance both customer desire to buy and business sales. To investigate the factors influencing purchase intention in live-streaming shopping, a systematic literature review was conducted. A total of 40 factors were found from 13 selected articles containing live-streaming shopping and purchase intention. Based on these factors, 34 had a positive impact, 2 had a negative impact, and 4 had no significant impact on buyer purchase intention.
Comparative Analysis of Machine Learning Techniques for Hand Movement Prediction Using Electromyographic Signals adani, M. Syakhisk N.; Widasari, Edita Rosana; Setiawan, Eko
Journal of Information Technology and Computer Science Vol. 9 No. 1: April 2024
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jitecs.202491577

Abstract

The analysis of electromyography (EMG) signals plays a vital role in diverse applications such as medical diagnostics and prosthetic device control. This study focuses on evaluating machine learning methods for EMG signal analysis, specifically in predicting hand movements and controlling prosthetic hands. In contrast to many existing studies that solely employ a limited set of feature extraction methods, we employ a comprehensive comparison technique that encompasses nine machine learning techniques K-Nearest Neighbor (KNN) , State Vector Machine (SVM ) , Decision Tree, Random Forest, Linear Discriminant Analysis (LDA), XGBoost, Naïve Bayes, Gradient Boosting, and Quadratic Discriminant Analysis (QDA)  and five combination of feature extraction methods (Mean Absolute Value (MAV), Root Mean Square (RMS), Waveform Length, Willison Amplitude, and Skewness). The experimental results demonstrate promising accuracy levels, with the best result method being KNN achieving 96.66% accuracy, SVM achieving 95.83% accuracy, and RF achieving 92.5% accuracy. These findings contribute to advancing the understanding of effective machine learning approaches for EMG signal analysis and provide valuable insights for guiding future research in this field. The study also compares the results with previous studies and showcases the effectiveness of the proposed approach.
Phenomenological Investigation of Social Media Technological Aspects Against Cyberbullying from the Third Person Perspective of Higher Education Students Dhewanty, Civica Moehaimin; Priharsari, Diah; Setiawan, Budi Darma
Journal of Information Technology and Computer Science Vol. 9 No. 1: April 2024
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jitecs.202491578

Abstract

Cyberbullying often occurs among higher education students as they frequently use and easily get access to the internet, especially through social media. However, the awareness of cyberbullying among them is very low. They do not know how to identify cyberbullying and prevent it. This research will discover the characteristics of social media that can help third persons identify and prevent cyberbullying. This research used a qualitative method with a phenomenological approach to study a person’s experience of technology regarding cyberbullying. The data collected in this study were obtained from interviews with higher education students. The data acquired were analyzed using Collaizzi's seven steps descriptive phenomenological analyses. The analysis produced a description of the phenomenon of cyberbullying on social media that have verified by the interviewees. This study found some characteristics of social media to help higher education students identify and prevent cyberbullying and discovers which social media has the most cyberbullying content and the similarities/differences of each social media in helping a third person identify and prevent cyberbullying. And found several technological factors that affect the effort of preventing cyberbullying, such as seeing other people’s activities and personal information on social media, and doing a report or sharing cyberbullying content.
Voice Recognition to Classify “Buka” and “Tutup” Sound to Open and Closes Door Using Mel Frequency Cepstral Coefficients (MFCC) and Convolutional Neural Network (CNN) Laksono, Blessius Sheldo Putra; Syaifuddin, Tio; Utaminingrum, Fitri
Journal of Information Technology and Computer Science Vol. 9 No. 1: April 2024
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jitecs.202491579

Abstract

The consequences of the coronavirus called COVID-19 have been really impactful on society. Many things need to be changed in order to survive this pandemic. People have to avoid physical contact to minimize the probability of getting caught by other people who have been infected. A doorknob has a really big potential to be the medium to spread the virus because the same surface is used by several people. Speech recognition can be used to solve this problem. In this study, Mel Frequency Cepstral Coefficients (MFCC) and Convolutional Neural Network (CNN) are going to be used as the extraction feature and classification method, respectively. We classify the sound signal into two classes (“buka” and “tutup”). People who want to open or close the door just need to say a specific command. This can be helpful to minimize the risk of COVID transmission. A CNN model is developed and fed with an audio file from a curated dataset for training and testing. With this system, we have successfully trained the model with an accuracy of 89% using an epoch of 50 and batch size of 32 as the parameters with a dataset distribution of 8:2 for training and validation. We believe this study will be influential in developing automated door systems using speech recognition, especially in the Indonesian language.
Preliminary Review of Desktop-to-Web System Transformation of Data Input Process in Accounting Information System Diana; Pinandito, Aryo; Pradana, Fajar
Journal of Information Technology and Computer Science Vol. 9 No. 1: April 2024
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jitecs.202491580

Abstract

The accounting information system is an important key to financial management, the information influences the company’s decisionmaking in determining its future strategy. However, before the development of web technology, current systems were usually implemented on desktop platforms. Over time, many obstacles were found during its implementation, which had an impact on time efficiency on staff performance. Therefore, in this study, a preliminary review assessment is made to find out whether the current desktop information system is still good for use or a web-based system is able to provide more performance, especially in terms of time efficiency. According to the results of this study, web information systems have better performance than desktops. With the transformation of the platform in the system, there was an increase in the use of time in carrying out input process activities of 35%.
Bottleneck and Resource Analysis on IT Help Desk with Process Mining Permana, Muhammad Cekas; Prameswari, Anindya; Ginting, Agriva Detta; Asjad, M. Rifadh; Syakurnia, Barajati; Andreswari , Rachmadita
Journal of Information Technology and Computer Science Vol. 9 No. 1: April 2024
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jitecs.202491581

Abstract

This study utilizes data from the help desk log of an Italian company to create a model of the company’s business processes. The primary objectives are to show the benefit of the implementation of process mining to identify bottleneck activites within the process and analyze the workload distribution among resources. The research reveals that the most common bottlenecks occur during the transition from ‘resolve tickets’ to ‘closed’ accounting for 99% of cases, and another activity from ‘assign seriousness’ towards ‘take in charge ticket’ experiences bottlenecks in 91% of cases. Furthermore, a decrease in the number of cases was discovered after October 2012. Prior to this period, the average number of cases per resource was high, leading to a high average number of active resources per day and average number of events per day. However, after October 2012, the average number of cases per resource decreased by approximately 74.6% to 47 cases per resource. The average number of active resources also decreased by 25% to 3 active resources per day. Additionally, the average number of events per resource decreased by 40% to 3 events per resource per day. Regarding the resource workload, the analysis reveals that ‘value 2’ has the highest workload, having worked on 4,235 events. This is followed by ‘value 5’ with 3,748 events, ‘value 1’ with 3,028 events, ‘value 9’ with 2,073 events, and ‘value 13’ with 1,420 events.
Factors Influencing Employee Productivity in Work From Anywhere: A Systematic Literature Review (SLR) Fauziyah, Neyla Neyla Nuril; Priharsari, Diah; Pinandito, Aryo; Pradana, Fajar
Journal of Information Technology and Computer Science Vol. 9 No. 1: April 2024
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jitecs.202491584

Abstract

Many companies have begun to adopt both ways of working simultaneously or commonly referred to as Work From Anywhere (WFA); it is necessary to model business processes used to evaluate and improve the WFA work system in the future. In modelling business processes, it is necessary to carry out a needs analysis, one of which is to find out what factors affect employee productivity when doing their work. Several research journals related to WFA work productivity factors are still scattered in various journal databases, so it is necessary to unify them from various journals. Therefore, it is necessary to research the grouping of factors and theories that affect the productivity of WFA employees in the Systematic Literature Review (SLR) method. Before grouping, the search criteria and journal search process are determined first. The first search is to identify based on keywords, year of publication, and journal quality. Then continued, the use of Cohen's Kappa method for selection based on the field of discussion and language, abstracts, and contents. In improving the reliability of the library screening results, each selection is made twice (or more) and calculates the value of Cohen's Kappa. The SLR method makes the usually subjective literature study more objective to reduce the researcher's bias. The results obtained were a total of 17 screening journals with a total of 11 factors, namely environment, time efficiency, psychology, health, cost efficiency, employee personality, adequate technology, gender, geographical flexibility, salary, and communication.
Optical Character Recognition Mobile App for Address Matching in Integrated Social Welfare Data Verification Process Panjaitan, RE. Miracle; Rahayudi, Bayu; Ratnawati, Dian Eka
Journal of Information Technology and Computer Science Vol. 9 No. 1: April 2024
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jitecs.202491601

Abstract

The Ministry of Social Affairs of the Republic of Indonesia has Integrated Social Welfare Data called Data Terpadu Kesejahteraan Sosial (DTKS) and uses it as a basis for the distribution of Social Fund Assistance, or Bantuan Sosial (BANSOS). The fact that occurred in the field was that there were many BANSOS recipients who were not impoverished and did not qualify to be the target of this program. One of the reasons is that there are weaknesses in the system that have the potential for data manipulation during the verification and validation processes. Therefore, a system improvement is needed to minimize the possibility of the data being manipulated. This study proposes a digital verification system using Optical Character Recognition (OCR) and reverse geocoding to make sure that the registrant provides their own citizen ID card and their own house address that meet the qualifications. These technologies in the developed mobile app perform address matching between address extracted from citizen ID card and address obtained from reverse geocoding. The results of this application trial achieved a success rate of 95.7%.

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