//jcrinn.com/index.php/jcrinn/issue/feed Journal of Computing Research and Innovation 2022-03-31T00:00:00+00:00 Chief Editor (attn: Arifah Fasha Rosmani) editor@jcrinn.com Open Journal Systems <p><strong>Journal of Computing Research and Innovation (<em>eISSN : 2600-8793</em>)</strong> is a double-blind peer-reviewed, open access journal which is published bi-anually in March and September. JCRINN is managed by Computer Science Department, Faculty of Computer and Mathemathical Sciences, Universiti Teknologi MARA, Perlis Branch, MALAYSIA.</p> <p><strong>Frequency of Publication</strong> : Twice a year (March and September)</p> <p><strong>Manuscript Language:</strong> English</p> <p><strong>Abstracting and Indexing</strong></p> <p><strong>- </strong><a href="https://myjurnal.mohe.gov.my/public/browse-journal-view.php?id=882">MyJurnal</a><br />- <a href="https://essentials.ebsco.com/search/eds/details/journal-of-computing-research-and-innovation?query=journal%20of%20computing%20research%20and%20innovation&amp;requestCount=0&amp;db=edsdoj&amp;an=edsdoj.676564d0ed974f01a6451b392ae51667&amp;isbn">EBSCO</a><br />- <a href="https://scholar.google.com/scholar?hl=en&amp;as_sdt=0%2C5&amp;q=site%3Acrinn.conferencehunter.com">Google Scholar</a><br />- <a href="https://journal.uitm.edu.my/ojs/#:~:text=The%20Journal%20of%20Computing%20Research,the%20fields%20of%20Computer%20science.">UiTM Journal</a><br />- <a href="https://tinyurl.com/crinndoaj">Directory of Open Access Journals (DOAJ)</a><br />- <a href="https://search.crossref.org/?q=+2600-8793&amp;sort=year&amp;from_ui=yes">CrossRef</a><br />- <a href="https://www.scilit.net/journal/6136300">Scilit</a><br />- <a href="https://www.worldcat.org/search?qt=worldcat_org_all&amp;q=jcrinn">OCLC WorldCat</a><br />- <a href="https://journals.indexcopernicus.com/search/details?id=121879">Index Copernicus</a></p> //jcrinn.com/index.php/jcrinn/article/view/283 E-Complaint System for UiTM Perlis College Embedded with Gamification 2022-03-23T04:21:09+00:00 ‘Afifah Najibah Arif honeymsofea@gmail.com Mahfudzah Othman mahfudzah1978@gmail.com Nurzaid Muhd Zain nurzaid@uitm.edu.my Zulfikri Paidi fikri@uitm.edu.my <p><em>Even though people can make complaints through a computerized system, some places still use the manual system. The manual system is inconvenient for the complainant because they must visit the respective counter to channel the complaints. In addition, the form provided usually consists of long instructions for the complainant to read before channelling the complaint. This paper discusses the development of an e-Complaint System for UiTM Perlis colleges embedded with gamification. In this system, there are three gamification elements included, which are the progress bar, leaderboard, and Avatar selection for personalization. Two tests were conducted, which are functionality and usability testing through various platforms such as YouTube, 000webhost, and Google Form. There were 33 respondents for the usability testing consisting of students and staff of UiTM Perlis. While the functionality testing was conducted with UiTM Perlis lecturers who have experienced teaching IT subjects. From the responses obtained from the respondents through PPSUQ Survey, most of the respondents agreed that the developed system helped them in channelling complaints and updating the status of their complaints compared to the existing system. The system developed does include some gamification elements which can ease the users to use the e-complaint system in the future. Via this system, users were guided on how to lodge complaints via step-by-step process instead of reading long instructions which could lead them to confusion.</em></p> 2022-03-30T00:00:00+00:00 Copyright (c) 2022 Journal of Computing Research and Innovation //jcrinn.com/index.php/jcrinn/article/view/282 Integrated Network Monitoring using Zabbix with Push Notification via Telegram 2022-03-23T01:41:25+00:00 Mohd Faris Mohd Fuzi farisfuzi@uitm.edu.my Nur Fatin Mohammad Ashraf nurfatinashraf@gmail.com Muhammad Nabil Fikri Jamaluddin nabilfikri@uitm.edu.my <p><em>The world is becoming increasingly dependent on online services. To offer a service, a network must be in good health and free of any attacks. An attack happens when the confidentiality, integrity, or availability of a service is compromised. Network monitoring is a solution capable of maintaining these network devices from their usage up to detecting attacks. A denial of service (DoS) attack on a network can affect the network performance and can cause serious damage. Zabbix is an open-source network monitoring tool that is versatile and can be used to monitor hosts on a network. The purpose of this project is to detect possible ping and SYN flooding attempts on a server and send alerts to the administrator via Telegram. This project uses Zabbix to monitor a server for potential ping and SYN flooding attacks. Tcpdump is used to log the pings received by the server. When the server continuously receives 10 or more pings per second, an alert will be automatically generated and sent to the administrator via Telegram. Similarly, a SYN flood attack is detected by using netstat’s SYN_RECV flags. When the server continuously receives more than 10 SYN packets without an ACK packet, Zabbix will generate alerts that are sent via Telegram and update the dashboard to show a problem. Zabbix was able to accurately detect all ping flooding attempts on the server. However, SYN flooding attacks were not as accurately detected. The use of Zabbix can be implemented in small businesses or networks for an automated monitoring system. Future work can include more DDoS attacks and adding countermeasure actions when detecting attacks by blocking the IP or port associated with the attack. SYN flooding detection needs to be improved because only two out of three attacks were able to be caught.</em></p> 2022-03-30T00:00:00+00:00 Copyright (c) 2022 Journal of Computing Research and Innovation //jcrinn.com/index.php/jcrinn/article/view/281 The Design and Implementation of Web-Based Multimedia Learning Content Management System for Arabic Vocabulary Pronunciation 2022-03-23T01:40:47+00:00 Mohd Nizam Osman nizamos@gmail.com Mushahadah Maghribi mohdnizam@uitm.edu.my Nur Shazlena Sarif Puddin mohdnizam@uitm.edu.my Khairul Anwar Sedek khairulanwarsedek@uitm.edu.my Nor Arzami Othman arzami@uitm.edu.my <p><em>Arabic vocabulary is one of the important knowledge areas in learning Arabic language. In fact, that in the current world, almost 80% of Muslim are non-native speaker of Arabic language. Some people found that Arabic vocabulary is difficult and confusing to learn and subsequently failed to master the knowledge. Besides, most of the higher education in Malaysia has been introduce Arabic subject in their curriculum or plan of study. On the other hand, learners faced difficulties in learning Arabic vocabulary, especially the pronunciation due to limited hours of learning in the class and less attractive of teaching materials. The purpose of this study is to design and develop a web-based multimedia learning content management system (LCMS) to enhance the learning of Arabic vocabulary pronunciation. The proposed system was developed using Articulate Storyline for implementing interactive learning which all multimedia elements can be blended in the system. The development process follows the System Development Life Cycle (SDLC) as a methodology. Then, the proposed system is evaluated using expert reviews by distributing questionnaires among five expert users, and User Acceptance Test (UAT) contributed thirty respondents to determine the effectiveness of the system. The result from the Expert Review shows that the proposed system is suitable to use but still needs some improvements. While the result from the UAT indicates that the proposed system has a positive impact and to be well accepted by the majority of the users. Therefore, the most significant potential is the ability of the proposed system to help, assist, enhance and enrich the experience of learning Arabic vocabulary pronunciation more effective and efficient. </em></p> 2022-03-30T00:00:00+00:00 Copyright (c) 2022 Journal of Computing Research and Innovation //jcrinn.com/index.php/jcrinn/article/view/279 Shift Scheduling with the Goal Programming Approach in Fast-Food Restaurant: McDonald’s in Kelantan 2022-03-23T01:39:28+00:00 Diana Sirmayunie Mohd Nasir dianasirmayunie@uitm.edu.my Nur Darina Aimi Sabri dianasirmayunie@uitm.edu.my Nor Hayati Shafii norhayatishafii@uitm.edu.my Suzanawati Abu Hasan suzan540@uitm.edu.my <p><em>A major fast-food restaurant chain, such as McDonald's, must perform well to maintain its credibility with customers and dominance over other competitors. A fair and balanced shift schedule of workers must be generated to ensure that the workers provide the best service and production for the restaurant. Consequently, this study proposed a fair and efficient workforce schedule at a McDonald's restaurant in Kelantan, Malaysia. Furthermore, the goal programming method and the LINGO software are used in this study to develop the best schedule for the workers over a 28-day period. Five hard constraints and three soft constraints are identified. The primary goal of this study, which demanded the same total workload for each worker, was met. However, the other two goals are not fully achieved but have little impact on the workers due to the 18-hour operation and rotation of schedules among workers. Finally, the generated schedule pattern has been shown to provide a better schedule in terms of having the same total number of shifts for each worker and giving each worker the same total number of off days.</em></p> <p><em> </em></p> 2022-03-30T00:00:00+00:00 Copyright (c) 2022 Journal of Computing Research and Innovation //jcrinn.com/index.php/jcrinn/article/view/278 Designing Fish Optic Mobile Application for Fish Disease Identification 2022-03-14T07:55:46+00:00 Romiza Md Nor romiza@uitm.edu.my Muhammad Amin Abdullah darqfirephoenix@gmail.com Nurul Syafiqah Aminuddin miezanor03@gmail.com Nur Shahidatul Shaurah Sharifunizam ie_za@yahoo.com Aliaa Zafirah Zainal iriz0605@gmail.com Huzaifah A Hamid huzaifahhamid@uitm.edu.my <p><em>The signs and symptoms of fish disease can be traced by checking on the eye surface which is the cornea of fisheye. The Fish Optic mobile application aims to help students study the fisheye anatomy and to trace the symptoms of diseases on fish. The Fish Optic user mobile application uses Human-Centered System Development Life Cycle (HCSDLC) which consists of four phases which are project selection and planning, analysis, design and implementation. As HCSDLC emphasizes on user involvement throughout all phases, an interview was conducted, and a post task walkthrough was performed. User Acceptance Test formative evaluation was then conducted by distributing questionnaire. Some recommendations are also discussed for future works to improve and refine the design of the Fish Optic mobile application to enhance user experience. I</em><em>t can be concluded that using HCSDLC method throughout the design of Fish Optic mobile application contributes to a </em><em>well-defined systems requirement to support user needs and to accommodate the lack of human understanding that frustrates users in their daily routines.</em></p> 2022-03-30T00:00:00+00:00 Copyright (c) 2022 Journal of Computing Research and Innovation //jcrinn.com/index.php/jcrinn/article/view/277 Enhancing Sign Language Learning with Augmented Reality 2022-03-14T07:58:19+00:00 Hawa Mohd Ekhsan hawame@uitm.edu.my Mohamad Daniel Muhamad Khairi nell4614@gmail.com Jiwa Noris Hamid jiwa_noris@uitm.edu.my <p><em>Sign language is the communication language used by people with disabilities, especially deaf and hearing-impaired people. The communication between normal and disabled people using sign language will help them carry out their daily activities. Unfortunately, normal people are not aware of the importance of sign language because they are not directly dealing with disabled persons. Besides, some normal people found that sign language is difficult to learn. This study focuses on developing a mobile application for sign language with augmented reality features. This application is targeted at normal people as a sign language learning tool, and augmented reality will make the learning process effective and exciting. The methodology for this study is the ADDIE model that consists of five</em><em> phases, namely Analysis, Design, Development, Implementation, and Evaluation. This application will assist the users in learning sign language interactively and interestingly. The evaluation of the application was done by the expert in the related background and the normal people. The usability test result revealed that the sign language application is usable for normal people to know and learn the basic sign language. In conclusion, the sign language application is an interesting application for normal people to use and learn sign language.</em></p> 2022-03-30T00:00:00+00:00 Copyright (c) 2022 Journal of Computing Research and Innovation //jcrinn.com/index.php/jcrinn/article/view/275 Library Reservation System Using Face detection 2022-03-07T13:54:34+00:00 Nik Ruslawati Nik Mustapa nrnm@uitm.edu.my Nur Athikah Fatehah Rosli nrnm@uitm.edu.my <p><em>Today, Covid-19 has completely changed our way of life. The new generation has made people stay at home, instead of going on vacation. The users are not allowed in a close place, especially in a building or room. The library that used to be packed with people reading books, studying, and using the computer is now becoming empty. The room in the library has been limited only to a certain number of people to prevent any dangerous situation regarding the Covid-19 virus to spread. The room needs to be reserved beforehand for the user to use. This situation has become a problem for users as the user’s desired room may be occupied by other users. Thus, Reservation System using face recognition for the library was developed to overcome this situation. In this paper, the researcher will use the Haar Cascade Algorithm to scan the face and MySQL as a database to detect the room and time slot for a reservation. Phyton language and Visual Studio Code were used to develop the system. The limitation of this project is that the face registration took a long time for some users because of the lightning that makes it the system hard to recognize the face. The recommendations for future work are to use a high technology camera to scan the face and construct an admin page because the system does not have an admin page.</em></p> 2022-03-30T00:00:00+00:00 Copyright (c) 2022 Journal of Computing Research and Innovation //jcrinn.com/index.php/jcrinn/article/view/274 An Analysis of Intrusion Detection Classification using Supervised Machine Learning Algorithms on NSL-KDD Dataset 2022-03-07T13:56:53+00:00 Sarthak Rastogi 19103201@mail.jiit.ac.in Archit Shrotriya 19103195@mail.jiit.ac.in Mitul Kumar Singh 19103182@mail.jiit.ac.in Raghu Vamsi Potukuchi prvonline@yahoo.co.in <p><em>From the past few years, Intrusion Detection Systems (IDS) are employed as a second line of defence and have shown to be a useful tool for enhancing security by detecting suspicious activity. Anomaly based intrusion detection is a type of intrusion detection system that identifies anomalies. Conventional IDS are less accurate in detecting anomalies because of the decision taking based on rules. The IDS with machine learning method improves the detection accuracy of the security attacks. To this end, this paper studies the classification analysis of intrusion detection using various supervised learning algorithms such as SVM, Naive Bayes, KNN, Random Forest, Logistic Regression and Decision tree on the NSL-KDD dataset. The findings reveal which method performed better in terms of accuracy </em><em>and running time</em><em>.</em></p> 2022-03-30T00:00:00+00:00 Copyright (c) 2022 Journal of Computing Research and Innovation //jcrinn.com/index.php/jcrinn/article/view/270 Measuring Students' Perception on Mathematics Learning Using Fuzzy Conjoint Analysis 2022-03-07T02:24:27+00:00 Zurina Kasim zkas@uitm.edu.my Nur Liyana Muhamad Sukri yanasukri1998@gmail.com <p><em>Mathematics courses are widely applied in the overall sector because mathematics is not only about the calculation or formulation, but also help in solving problems using mathematical modelling</em><em>. Students need to have a good understanding of the theory of mathematics in order to produce the best results. In the world of digitization, subjects in science, technology, engineering and mathematics have become Malaysia’s agenda in the preparation to compete globally. Empowering in these subjects enable the creation of innovators of the future, hence create job opportunities in the digitization world. However, the academic institutions have been facing a critical problem in potential growth of achieving the mission and vision in enhancing the students’ performance when it is related to the students’ interest. This study focuses on students’ perception toward mathematics learning among 60 undergraduate management mathematics major’s students at UiTM Perlis using fuzzy set conjoint analysis. The attribute in each dimension is ranked according to the highest similarities values. The finding showed that students were rated neutral toward the preparation before class (student’s attitude); strongly agree that the lecturers are knowledgeable and well prepared before class (lecturer’s role); and rated neutral on female students are more qualified mathematician and their passion toward mathematics but strongly agreed that mathematics is difficult to understand in short period of time (student’s perspective).</em></p> <p> </p> 2022-03-30T00:00:00+00:00 Copyright (c) 2022 Journal of Computing Research and Innovation //jcrinn.com/index.php/jcrinn/article/view/267 Fuzzy Logic to Evaluate Significant Factors Affecting Students’ Academic Performance Through Online Distance Learning 2022-03-07T02:22:05+00:00 Mohd Fazril Izhar Mohd Idris fazrilizhar@uitm.edu.my Khairu Azlan Abd Aziz khairu493@uitm.edu.my Muhammad Haiman Aminuddin haiman836@gmail.com <p class="Abstract" style="margin-bottom: 0cm;"><em><span lang="EN-US" style="font-size: 11.0pt; font-weight: normal;">Online distance learning is becoming more and more popular and more preferred among students. In order to develop efficient strategies and solutions for introducing online distance learning, higher education institutions should be aware of the needs and expectations of their students. In the current study, students from University of Technology MARA will investigate which factors that affect the execution of online distance learning for academic performance. Time management, learning environment, internet connection, and learning method are among the factors under consideration, as determined by a literature review. The information was gathered through an online survey of 331 students whose academic performance is affected by online distance learning. An expert system based on fuzzy logic has been developed to determine which factors have the greatest influence on students' academic performance in online distance learning. According to the results obtained using the MATLAB software, one of the most important factors influencing students' academic performance in online distance learning is time management. The findings of this study will help students to improve time management in order to improve students’ academic performance.</span></em></p> 2022-03-30T00:00:00+00:00 Copyright (c) 2022 Journal of Computing Research and Innovation //jcrinn.com/index.php/jcrinn/article/view/266 Analysis of Chinese Patents associated with Incremental Clustering Algorithms: A Review 2022-01-22T17:05:30+00:00 Archana Chaudhari chaudhari.archana12@gmail.com Preeti Mulay preeti.mulay@sitpune.edu.in Amit Kumar Tiwari meettiwari@gmail.com <p><em>With the advent of Internet-of-Things (IoT) and overall Information-Technology world, an enormous amount of data is getting generated dynamically and in real-time mode, in almost all domains of research and application systems. Such huge data has embedded patterns and hidden information to extract and learn. This learning is incremental in nature for all involved entities and users, as the data is growing exponentially in real-time. To achieve learning from such dynamic data sources, incremental clustering algorithms are used mandatorily. This mandate has given rise to increased patents related to incremental clustering concept, which is primarily a significant part of Machine Learning field. In this paper, we contribute to the in-progress discussion on the use of intellectual property resources, particularly patents related to machine learning, incremental clustering, incremental learning with a special focus to country China. Due consideration of the prior art search, the author found that China the country of registration of the application extensively contributes to the intellectual property related to incremental clustering domain hence felt the need to undertake this detailed patent analysis about this topic. We hope all readers, research scholars will be benefited with the latest research presented in this paper pertaining to various patents in the advanced areas of computer engineering. </em></p> 2022-03-30T00:00:00+00:00 Copyright (c) 2022 Journal of Computing Research and Innovation //jcrinn.com/index.php/jcrinn/article/view/264 Artificial Neural Network (ANN) to Predict Mathematics Students’ Performance 2022-01-14T02:00:41+00:00 Norpah Mahat norpah020@uitm.edu.my Nor Idayunie Nording nuridayunie98@gmail.com Jasmani Bidin jasmani@uitm.edu.my Suzanawati Abu Hasan suzan540@uitm.edu.my Teoh Yeong Kin ykteoh@uitm.edu.my <p><em>Predicting students’ academic performance is very essential to produce high-quality students. The main goal is to continuously help students to increase their ability in the learning process and to help educators as well in improving their teaching skills. Therefore, this study was conducted to predict mathematics students’ performance using Artificial Neural Network (ANN). The secondary data from 382 mathematics students from UCI Machine Learning Repository Data Sets used to train the neural networks. The neural network model built using nntool. Two inputs are used which are the first and the second period grade while one target output is used which is the final grade. This study also aims to identify which training function is the best among three Feed-Forward Neural Networks known as Network1, Network2 and Network3. </em><em>Three types of training functions have been selected in this study, which are Levenberg-Marquardt (TRAINLM), Gradient descent with momentum (TRAINGDM) and Gradient descent with adaptive learning rate (TRAINGDA). Each training function will be compared based on Performance value, correlation coefficient, gradient and epoch. MATLAB R2020a was used for data processing. The results show that the TRAINLM function is the most suitable function in predicting mathematics students’ performance because it has a higher correlation coefficient and a lower Performance value. </em></p> 2022-03-30T00:00:00+00:00 Copyright (c) 2022 Journal of Computing Research and Innovation //jcrinn.com/index.php/jcrinn/article/view/262 Investigating the Factors of Committing Crime by Foreign Workers Using Fuzzy Techniques 2021-12-31T01:30:31+00:00 Nur Syuhada Muhammat Pazil syuhada467@uitm.edu.my Norwaziah Mahmud norwaziah@uitm.edu.my Siti Hafawati Jamaluddin hafawati832@uitm.edu.my Nur Aisyah Maslin norwaziah@uitm.edu.my <p><em>Criminal activities have a huge detrimental impact on society and the country. Foreign workers are among the contributors to the crime rate in Malaysia. Crime rate will not decrease if the factors that influence foreign workers to commit crimes remain unclear and unexplored. Many factors are affecting the foreign workers to commit crime. This research aims to determine the ranking for the factors of committing crimes by foreign workers. The Fuzzy Technique for Order Preference with Similarity to Ideal Solution (TOPSIS) was applied to rank the factors. The alternative of this research is the factors of committing crimes by foreign workers, which are lack of facilities, poverty, wage discrimination, fraud by employment agents, alcohol and drug abuse, and poor education level. The criteria chosen are ex-criminal, desperate individual, legal immigrant and illegal immigrant. Three decision-makers which are police officers must assess the factors in this research using linguistic variables ranging from "very poor" to "very good". The alternatives that would be chosen have the shortest distance to Positive Ideal Solution (PIS) and the farthest distance to Negative Ideal Solution (NIS). Finally, this study demonstrates that the highest ranking for the factors of committing crime by foreign workers is wage discrimination with a closeness coefficient value of 0.5305. The minor contributing factor with a closeness coefficient value of 0.2744 comes from poverty. Many personnel may benefit from the findings of this study.</em> <em>This study provides information about the factors of committing crime most associated with foreign workers, allowing employers to be aware of the risk they come with. This requires them to be more responsive to their employees, such as monitoring employee movement to track their daily activities (e.g., installing security cameras the housing facilities). Besides, employers should fairly deal with their employees and keep the workforce motivated to avoid criminal cases. A future study might broaden the scope of the project by including various sorts of criteria and alternatives.</em></p> 2022-03-30T00:00:00+00:00 Copyright (c) 2022 Journal of Computing Research and Innovation //jcrinn.com/index.php/jcrinn/article/view/258 Data Driven Mathematical Models for Forecast of Covid-19 Disease in Nigeria 2021-11-08T12:52:57+00:00 Oludare Adedire dharenss@gmail.com Yahaya Sadiku yasforest10@gmail.com Olufemi. O Adedire defemzz@yahoo.com Kambai Collina talk2nev@yahoo.com Afolabi. O Oladejo folabiola60s@gmail.com G.K Sikiru meeksikgben@gmail.com <p><em>In this research, two mathematical models are proposed for investigation of laboratory confirmed daily COVID-19 disease incidence and total active daily infectious COVID-19 cases using data obtained from Nigeria Centre for Disease Control. Due to the observed patterns in the raw data, Autoregressive Integrated Moving Average(ARIMA) method is used on the data which covered a period of 521 days (27 February, 2020- 1st August 2021). While diagnostic check of ARIMA(11,1,0) indicate Ljung-Box Q(18) statistics value of 12.544 with p-value of 0.084, diagnostic check of ARIMA(1, 1, 1) indicate Ljung Box Q(18) statistics value of 22.420 with p-value of 0.130. Furthermore, stationary R- squared values are 0.803 and 0.858 at 95% confidence bound for ARIMA (11, 1, 0) and ARIMA (1, 1, 1) respectively which are indicative of good models. Results from ARIMA (11, 1, 0) forecast show a slightly moderate upward trend in confirmed daily COVID-19 incidence in Nigeria and results from ARIMA(1, 1, 1) indicate significant upward trend in total active daily infectious COVID-19 cases in Nigerian population. Therefore, the developed models can be adopted by presidential taskforce and other agencies in health sector regarding future vaccination towards prevention of the spread of COVID-19 disease in Nigeria provided that the present general prevailing conditions of disease spread remain fairly the same.</em></p> 2022-03-30T00:00:00+00:00 Copyright (c) 2022 Journal of Computing Research and Innovation