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Journal of Information Technology and Computer Science
Published by Universitas Brawijaya
ISSN : 25409433     EISSN : 25409824     DOI : -
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 245 Documents
Evaluation Quality and Success Implementation of Nganjuk Smart City Mobile Application Using Technology Acceptance Model (TAM) and Delone Mclean Model Approach Anisya, Rossa Dini; Herlambang, Admaja Dwi; Rachmadi, Aditya
Journal of Information Technology and Computer Science Vol. 6 No. 3: December 2021
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (946.944 KB) | DOI: 10.25126/jitecs.202163322

Abstract

Nganjuk Smart City is an android-based mobile application that was created to help Nganjuk citizen obtain public information and services. This research uses Technology Acceptance Model (TAM) and Delone & Mclean in order to determine quality and success implementation condition of Nganjuk Smart City. Data retrieval was conducted by sharing online and offline questionnaires to 175 respondents and used purposive sampling techniques to determine research samples. The result of this research is quality condition implementation of Nganjuk Smart City based on Technology Acceptance Model (TAM) falls into high category and get 71.4% score, while successful condition implementation of Nganjuk Smart City based on Delone & McLean model falls into the high category and get 69.4% score. There are 4 variables and 18 indicators that get improvement recommendations because they get scores lower than the total average scores.
Sentiment Anlysis On Customer Reviews Using Support Vector Machine and Usability Scoring Using System Usability Scale Azpiranda, Novira; Supianto, Ahmad Afif; Setiawan, Nanang Yudi; Suryawati, Endang; Yuwana, R. Sandra; Febriandirza, Arafat
Journal of Information Technology and Computer Science Vol. 6 No. 3: December 2021
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jitecs.202163330

Abstract

Al-Ghiff Steak is a restaurant located in Cirebon City that offers quality steaks at affordable prices. For maintaining a competitive Al-Ghiff Steak advantage and reputation, it is important to build a good relationship with customers and have a business strategy that considers customer opinions. However, in its implementation, Al-Ghiff Steak has difficulty when collecting and processing customer review data manually. Therefore, it is necessary to conduct sentiment analysis by utilizing Google Reviews to determine customer perspectives regarding Al-Ghiff Steak products and services. This analysis was conducted on 968 Google Review reviews from 2016 to 2020 using the Support Vector Machine (SVM) and Term Frequency-Inverse Document Frequency (TF-IDF) methods. Classification testing is done with a confusion matrix against four parameters: accuracy, precision, recall, and f1-score. SVM with TF-IDF gets accuracy value 83%, precision 64%, recall 60% and f1-score 59%. The sentiment classification result is then visualized in the form of a dashboard. We utilize the System Usability Scale (SUS) for usability testing, which produces a value of 77.5. This result achieve the Acceptable category and an Excellent rating.
A Literature Review of Knowledge Tracing for Student Modeling : Research Trends, Models, Datasets, and Challenges Am, Ebedia Hilda; Hidayah, Indriana; Kusumawardani, Sri Suning
Journal of Information Technology and Computer Science Vol. 6 No. 2: August 2021
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (900.101 KB) | DOI: 10.25126/jitecs.202162344

Abstract

Modeling students' knowledge is a fundamental part of online learning platforms. Knowledge tracing is an application of student modeling which renowned for its ability to trace students' knowledge. Knowledge tracing ability can be used in online learning platforms for predicting learning performance and providing adaptive learning. Due to the wide uses of knowledge tracing in student modeling, this study aims to understand the state-of-the-art and future research of knowledge tracing. This study focused on reviewing 24 studies published between 2017 to the third quarter of 2021 in four digital databases. The selected studies have been filtered using inclusion and exclusion criteria. Several previous studies have shown that there are two approaches used in knowledge tracing, including probabilistic and deep learning. Bayesian Knowledge Tracing model is the most widely used in the probabilistic approach, while the Deep Knowledge Tracing model is the most popular model in the deep learning approach. Meanwhile, ASSISTments 2009–2010 is the most frequently tested dataset for probabilistic and deep learning approaches. In the future, additional studies are required to explore several models which have been developed previously. Therefore this study provides direction for future research of each existing approach.
Go Story: Design and Evaluation Educational Mobile Learning Podcast using Human Centered Design Method and Gamification for History Biabdillah, Fajerin; Tolle, Herman; A. Bachtiar, Fitra
Journal of Information Technology and Computer Science Vol. 6 No. 3: December 2021
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (889.512 KB) | DOI: 10.25126/jitecs.202163345

Abstract

Technological developments, especially in the field of education, can help students learn more effectively and help the learning process. The learning method used in high school for history learning still uses conventional methods. The use of this conventional method often experiences problems such as students being less motivated in learning. One of the solutions proposed in this article is to design an android-based learning media that can support the activities of the learning process named go-story. Interface design for students as application users and (UI/UX) based on human centered design methodology and the concept of gamification. The human centered design approach and the concept of gamification will be used in the analysis and design process to maximize the usability and engagement of the application. The application will be implemented and tested on students to measure its effectiveness. The trials that have been carried out show the results of improvements
Mastery of Technological Pedagogical And Content Knowledge (TPACK) Prospective Teacher In ICT Expertise Brawijaya University Latifah, Luluk; Herlambang, Admaja Dwi; Wijoyo, Satrio Hadi
Journal of Information Technology and Computer Science Vol. 6 No. 3: December 2021
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1153.904 KB) | DOI: 10.25126/jitecs.202163350

Abstract

The Information Technology Education (ITE) study program, Faculty of Computer Science, Universitas Brawijaya requires its students to take part in Pengenalan Lapangan Persekolahan (PLP) 2 according to Permenristekdikti No. 55 of 2017 in order to be able to produce prospective teachers who have the competence of educators. This study describes the gap in mastery of competencies with the TPACK framework based on the results of PLP 2 activities which are compared with standard values using a discrepancy evaluation model. The results of the gap are mapped using the method Importance Performance Analysis (IPA) to determine the priority scale for improvement of variables according to positions in certain quadrants. Through the IPA method, the variables that are prioritized to improve their mastery are TPK and PCK because they have very small gaps. Recommendations are given for the TPK variable to be given a pretest and posttest on the material for preparing teaching tools and training in the preparation of lesson plans. For the PCK variable, should be given pretest and posttest to the study material for theoretical and practical learning scenarios, the activities are needed lesson study which is carried out at least twice.
Sentiment Visualization of Covid-19 Vaccine Based On Naive Bayes Analysis Putri Aprilia, Nabilah; Pratiwi, Dian; Barlianto Ariwibowo, Anung
Journal of Information Technology and Computer Science Vol. 6 No. 2: August 2021
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1487.403 KB) | DOI: 10.25126/jitecs.202162353

Abstract

COVID-19 is one of the topics that is being discussed intensively. The virus which was declared a global pandemic on March 11 by WHO caused around 2.09 million Indonesians to be infected with the COVID-19 virus. To overcome this, the government carried out a vaccination program. The data taken for this study is public opinion about the COVID-19 vaccine written on Twitter. The number of opinions written on Twitter requires classification according to the sentiments they have, whether they tend to be negative opinions or positive opinions using lexicon-based The idea of this research is to classify the covid vaccination dataset using the naive Bayes classifier method and visualization using word cloud. Crawling to obtain the dataset from Twitter, text pre-processing and labelling to determine the positive and negative classes, TFIDF feature extraction, data splitting with a percentage of 80% for train data and 20% for data testing, and finally classification using nave Bayes are the stages in this research The system's sentiment analysis research yielded significant results, the accuracy value is 73.1%, the precision value is 73% and the recall value is 83%.
Development of an Intelligent Smart Home Automation System Akinyede, Raphael
Journal of Information Technology and Computer Science Vol. 6 No. 2: August 2021
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1053.455 KB) | DOI: 10.25126/jitecs.202162360

Abstract

Generally speaking, security has been a major concern in every nook and cranny of our nation -Nigeria. Recently, cases of vandalisation, stolen vehicles, and related issues have been on the increase. The security personnel has done lots of work to curb this menace but most of their actions have not yielded the expected results. Therefore, there is need to use technology to create a safer society. Such technology will use GSM and camera for detections. The technology is not going to replace the security personnel and usage of appliances such as gates, and doors locks, electric wires, etc, but it will be used as an alternative method for prevention/detection. Based on this background, a digital light-dependent resistor (LDR) sensor coupled with a microcontroller, relay, camera, and GSM technology was used to develop a smart home security system for automatic detection. The LDR sensor converts the light intensity to a digital format for the microcontroller to control the security lights automatically by using the relay as a switch. The passive infrared motion sensor perceives human movement and converts it to digital format for the microcontroller to trigger the GSM module and alert the user for live streaming of what is happening on the mobile app by establishing a connection between the camera and android smart device. The capturing and videoing are done on the mobile android device.
Developing A Supply Chain Of Apple Processed Product Traceability Information System Based On Smart Packaging And Digital Business Ecosystems Kurniawan, Miftakhurrizal; Amalia, Faizatul; Setiyawan, Danang
Journal of Information Technology and Computer Science Vol. 6 No. 3: December 2021
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1157.413 KB) | DOI: 10.25126/jitecs.202163362

Abstract

Apples are one of the fruits that much post-harvest processing can do. Apples can be processed into drinks or snacks. The need for information about nutritional content is needed by consumers. Therefore, a traceability information system is needed that can enable consumers to know the nutritional content involved. This research uses the Waterfall model information system development method and the Unified modeling language (UML). This method allows for the sequential development of information systems. The results of this research will be in the form of an information system that has been tested using the Requirement Traceability Matrix (RTM) and Response for a Class (RFC) method. The resulting Response for a Class (RFC) value is 5.17, meaning that this information system will be easy to adapt later
Comparison between SAW and Knowledge based SAW in Recipe Recommendation System Dewi, Ratih Kartika; Brata , Komang Candra; Afirianto, Tri; Candra , Ersya Nadia
Journal of Information Technology and Computer Science Vol. 6 No. 3: December 2021
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1081.349 KB) | DOI: 10.25126/jitecs.202163363

Abstract

Recipes are used as a reference in processing cooking ingredients to meet personal nutritional needs, considering the ingredients used to make food sold freely that is not necessarily guaranteed in nutritional quality and safe to consume, especially during the pandemic as it is today. So cooking itself becomes a better alternative for the community. With a large number of food recipe options available for various media, the role of a Decision Support System is needed by people who will get food recipe recommendations. Research related to recipe recommendations that have been done are using SAW only and some add experts as a source of knowledge to provide value on the variable time and complexity of cooking recipes. Therefore, in this study, a comparison between the research of recipe recommendations with SAW only and research that added a subsystem of knowledge management derived from experts to support the decision support system of food recipe recommendations was conducted by using correlation testing. The results is there is a strong correlation between knowledge based SAW and user preference to the value of 0.9774. The result is better than SAW only and user preference with the value of 0.7262.
Development of Telegram Bot for Flipped Learning Chemistry Class with UCD Approach Muniroh, Amirotul; Rizdania
Journal of Information Technology and Computer Science Vol. 6 No. 3: December 2021
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (924.609 KB) | DOI: 10.25126/jitecs.202163370

Abstract

The need for media that supports online learning is increasing along with the Covid-19 pandemic that is spreading in the world. The learning media is expected to be in the form of media that is easy to use and does not require additional costs incurred by students. One application that is widely used today is Telegram. The application provides a telegram bot facility that can assist teachers in delivering the material they are taught. By using the telegram bot, students can easily use applications on their mobile phones without installing additional applications. This study discusses the development of online learning methods using telegram bots as a medium for delivering material to students using the approach of UCD. This study used usability testing to evaluate the Telegram bot as the media for flipped learning. There are five indicators measured in the usability evaluation we used in this research. The result of the assesment is 83.56%.