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INDONESIA
MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer
Published by Universitas Bumigora
ISSN : 18584144     EISSN : 24769843     DOI : 10.30812/matrik
Core Subject : Science,
Computer Science & IT
MATRIK adalah salah satu Jurnal Ilmiah yang terdapat di Universitas Bumigora Mataram (eks STMIK Bumigora Mataram) yang dikelola dibawah Lembaga Penelitian dan Pengabadian kepada Masyarakat (LPPM). Jurnal ini bertujuan untuk memberikan wadah atau sarana publikasi bagi para dosen, peneliti dan praktisi baik di lingkungan internal maupun eksternal Universitas Bumigora Mataram. Jurnal MATRIK terbit 2 (dua) kali dalam 1 tahun pada periode Genap (Mei) dan Ganjil (Nopember).
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 20 Documents
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Search results for , issue "Vol. 22 No. 1 (2022)" : 20 Documents clear
Tuberculosis Extra Pulmonary Bacilli Detection System Based on Ziehl Neelsen Images with Segmentation Bob Subhan Riza; Jufriadif Na'am; Sumijan Sumijan
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 22 No. 1 (2022)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v22i1.1939

Abstract

Tuberculosis Extra Pulmonary (TBEP) is one of the infectious diseases that can cause death. The bacterium Mycobacterium tuberculosis is the cause of this disease. Patients suffering from this disease must be treated quickly. Currently, patients need a long time and a large cost in detecting the bacteria that cause this disease. The technique used is to take the patient's lung fluid by biopsy and given Ziehl Neelsen chemical dye and then observed using a microscope. This study aims to help detect bacteria quickly and precisely by processing the image produced by the microscope. The technique used is to develop the segmentation method. The segmentation process carried out is to develop a Hue Saturation Value (HSV) color space transformation technique with Active Contour, Edge Detection, and Otsu techniques. The images used in this research are 51 images taken from H. Adam Malik Hospital, Medan and have been validated by an expert. Of the several segmentation methods used in this study, the maximum or best result in detecting Tuberculosis Extra Pulmonary (TBEP) bacilli is the Otsu method. So the method developed is very helpful in accelerating the detection of TBEP.
Model Dynamic Facility Location in Post-Disaster Areas in Uncertainty lili Tanti; Syahril Efendi; Maya Silvi Lydia; Herman Mawengkang
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 22 No. 1 (2022)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v22i1.2095

Abstract

Indonesia has many disaster-prone areas, natural disasters that occur in Indonesia in 2021 are 5,402 disasters. For disaster management in post-disaster areas, logistical planning is needed in the distribution of logistical assistance, it is estimated that the logistics costs of disaster assistance reach approximately 80% of the total costs in disaster management so that logistical assistance is an expensive activity of disaster relief. However, so far the process of distributing logistical assistance to disaster posts has not been evenly distributed. One of the causes of the unequal distribution is the inappropriate selection of distribution post locations. The facility location model is dynamic and has the objective function of minimizing the distance between emergency posts and refugee posts in terms of distribution of disaster relief goods in one cluster group. For grouping unsupervised learning data using a machine learning clustering algorithm, k-means. Model validation has been carried out using max run and max optimization 1000 times with results reaching 90%. This proves that the emergency facility location model can be used to determine the location of the emergency center, where the determination of the location of the emergency center has the closest distance to the request point/post shelter for disaster victims
Automated University Lecture Schedule Generator based on Evolutionary Algorithm yusri ikhwani; Khairan Marzuki; As’ary Ramadhan
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 22 No. 1 (2022)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v22i1.2215

Abstract

university is a complicated work so in the implementation it have violation of the constraints and it also takes a lot of time since it is created manually. In this paper evolutionary algorithm (EA) is used to create an effective and feasible schedules based on the real data input that is obtained from each department. The objective functions in EA contribute in gaining the fitness function to solve the constraints problem in the schedule by applying weighting for each hard constraints. The objective function is gained from the total of infringement in each soft constraints addition by score weighting. The genetic operator used in EA is stochastic variation Operator. As far as the reproduction operator is concerned, the tournament selection was used with size 3. Crossover operator is conducted after selection process with crossover probability equal to 0.05 and mutation rate is 0.1. The size of population was set to 9 and stopping criteria algorithm was left run for fitness value = 1. The simulation result shows that EA can create lecture schedules efficiently and feasibly. Moreover, it is also faster with the execution time of the proposed EA is less than 30 and easier than creating manually.
Comparison of Naive Bayes and Dempster Shafer Methods in Expert System for Early Diagnosis of COVID-19 Nurdin Nurdin; Erni Susanti; Hafizh Al-Kautsar Aidilof; Dadang Priyanto
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 22 No. 1 (2022)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v22i1.2280

Abstract

COVID-19 is a respiratory infection disease caused by the corona virus. Transmission of this virus can spread very quickly so that the number of cases of the corona virus continues to grow and becomes an epidemic that spreads not only in Indonesia but also in other countries in the world. The purpose of this study is to build an expert system that is able to diagnose Covid-19 early by using a comparison of the Nave Bayes method and the Dempster Shafer method. The amount of data used in this study is 550 data, consisting of 500 training data and 50 testing data. While the variables used are symptoms related to COVID-19 as many as 17 symptoms consisting of G01, G02, G03, G04, G05, G06, G07, G08, G09, G10, G11, G12, G13, G14, G15, G16, G17. The diagnostic data consists of Suspected (PDP), Non-Suspected, and Close Contact (ODP). The results of the percentage test by comparing system diagnoses with expert diagnoses, for the nave Bayes method it has an accuracy of 96% with 48 diagnoses according to expert diagnoses from 50 tested data. Meanwhile, the Dempster Shafer method has an accuracy of 40% with 20 diagnoses according to expert diagnoses from 50 tested data. Based on the results of this study, the Naive Bayes and Dempster Shafer methods can be applied to an expert system for early diagnosis of COVID-19, from the results of the system testing the Naive Bayes method has better accuracy than the Dempster Shafer method.
Implementation of Single Linked on Machine Learning for Clustering Student Scientific Fields Saiful Nur Arif; Muhammad Dahria; Sarjon Defit; Dicky Novriansyah; Ali Ikhwan
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 22 No. 1 (2022)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v22i1.2337

Abstract

Machine Learning in classifying scientific fields according to the competence of students. Currently STMIK Triguna Dharma is quite difficult to map the scientific fields that will be used by students in submitting titles, so that the results of the thesis made are less than optimal. For this reason, it is necessary to map this concentration to assist students in completing theses through specialization classes. The Mechanical Learning technique used in solving this problem is to use the Single Linkage Technique. The process of testing the method begins with determining the standard data used and then looking for the proximity value using Euclidean so that later cluster results will be obtained from mapping scientific fields. From the Single Linkage Technique process that has been carried out, several cluster results will be obtained, namely clusters that map groups of STMIK Triguna Dharma students who have competence and clusters that map groups of STMIK Triguna Dharma students who lack competence. From the results of this grouping, the institution will make specialization classes according to the resulting cluster. Thus creating a specialization class that is in accordance with the competencies possessed by STMIK Triguna Dharma students
Automatic Door Access Model Based on Face Recognition using Convolutional Neural Network Tjut Awaliyah Zuraiyah; Sufiatul Maryana; Asep Kohar
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 22 No. 1 (2022)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v22i1.2350

Abstract

Automatic door access technology by utilizing biometrics such as fingerprints, retinas and facial structures is constantly evolving. The use of masks during the Covid-19 Pandemic and post-pandemic has become an obligation wherever humans are active. The study aimed to create an automated door access model using Convolutional Neural Network (CNN) algorithms and Amazon Rekognition as cloud-based software. The CNN algorithm is applied to classify faces wearing masks or not wearing masks. The CNN architecture model uses sequential, convolution2D, max polling 2D, flatten dan dense. The hardware includes the Raspberry Pi, USB Webcam, Relay, and Magnetic Doorlock. The test results were obtained from the results of the accuracy plot on the Convolutional Neural Network model with an accuracy rate of 99% at an epoch value of 8 with a learning time of 67 seconds.
Game for Sasak Script Based on Knuth Morris Pratt Algorithm and ADDIE Model Muhammad Tajuddin; Ahmat Adil; Andi Sofyan Anas
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 22 No. 1 (2022)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v22i1.2363

Abstract

Knowledge of the Sasak script is very few Sasak people are interested in learning it. The writing system of the Sasak script is in danger of becoming extinct, so the local government must carry out literacy education so that the Sasak script does not become extinct from the face of the Lombok earth and must be applied to elementary and junior high schools, not only in the learning and teaching process. Directing children can be done by introducing them to the game-based Sasak baluk olas script. The Sasak script game based on KMP (Knuth Morris Pratt) Algorithm and ADDIE (Analysis, Design, Development, Implementation, Evaluation) which integrates game thinking and game elements has proven helpful in learning new knowledge. For this reason, the purpose of this study is to discuss how to develop applications for the Sasak Baluk Olas script on smartphones based on the Android system. designed based on the famous visual novel concept that combines multimedia elements including audio, animation, graphics, and images to make it more interesting and lively. All of these elements combine with gamification elements such as quizzes, rewards, badges, and feedback to make it a gamification application. Based on all the abilities of the Sasak Baluq Olas script, it can help potential users, especially elementary and junior high school students in Mataram City to increase the level of understanding and awareness of the Sasak script so that it does not become extinct
Support vector machine with a firefly optimization algorithm for classification of apple fruit disease Wikky Fawwaz Al Maki; Amien Jafar Makrufi
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 22 No. 1 (2022)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v22i1.2365

Abstract

Fruit diseases became one of the serious problems that the farmer faced because it could threaten their economic outcome. The main focus of this study is apples. Apple fruit is very susceptible to disease, in general diseases that usually attack the apple are blotch apple, rot apple, and scab apple. In this study, the author is classifying these three apple diseases and normal apples. Classification is a process that we can do manually by human power, which costs a lot of fortune, takes a long time, and it's also very vulnerable to false identification. This study takes advantage of computer vision technology and machine learning to overcome the classification problem. By using the SVM method and parameter FA optimization algorithm, we can get the highest result only in the first experiment and also with 94% accuracy.
User Interface and Exprience Gamification-Based E-Learning with Design Science Research Methodology Viva Arifin; Velia Handayani; Luh Kesuma Wardhani; Hendra Bayu Suseno; Siti Ummi Masruroh
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 22 No. 1 (2022)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v22i1.2427

Abstract

In 2020, the Islamic Elementary Teacher Working Group (KKG MI) held an E-Learning Training for Islamic Elementary School Teachers in DKI Jakarta about one of the gamification applications, Quizizz. According to observation, many teachers are still perplexed when utilizing the Quizizz program. This is due to the application’s design and different functionalities, which still appear complicated to some teachers who aren’t used to using it. The existing gamification application is also considered not to meet the learning needs at Islamic elementary schools in Jakarta. This study intends to analyze and design User Interface (UI) and User Experience (UX) designs for gamification-based e-learning applications as solutions to the problems found. Data collection begins with an observation and also a literature study, questionnaires, and interviews. For the design, Design Science Research Methodology (DSRM) is used, which consists of six stages: Problem Identification & Motivation, Define the Objective for a Solution, Design & Development, Demonstration, Evaluation and Communication. The results of the evaluation of the gamification-based e-learning design designed with the User Experience Questionnaire (UEQ) and Task Success show that the e-learning design is considered attractive and users can interact with e-learning effectively and easily.
Infrastructure as Code for Security Automation and Network Infrastructure Monitoring Wahyu Riski Aulia Putra; Agus Reza Aristiadi Nurwa; Dimas Febriyan Priambodo; Muhammad Hasbi
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 22 No. 1 (2022)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v22i1.2471

Abstract

The Corona Virus (COVID-19) pandemic that has spread throughout the world has created a new work culture, namely working remotely by utilizing existing technology. This has the effect of increasing crime and cyber attacks as more and more devices are connected to the internet for work. Therefore, the priority on security and monitoring of network infrastructure should be increased. The security and monitoring of this infrastructure requires an administrator in its management and configuration. One administrator can manage multiple infrastructures, making the task more difficult and time-consuming. This research implements infrastructure as code for security automation and network infrastructure monitoring including IDS, honeypot, and SIEM. Automation is done using ansible tools to create virtual machines to security configuration and monitoring of network infrastructure automatically. The results obtained are automation processes and blackbox testing is carried out and validation is carried out using a User Acceptance Test to the computer apparatus of the IT Poltek SSN Unit to prove the ease of the automation carried out. Based on the results of the UAT, a score of 154 was obtained in the Agree area with an acceptance rate of 81.05% for the implementation of infrastructure as code for the automation carried out

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