Authors:Ivana Lucia Kharisma, Kamdan, Asep Rizki Firdaus, Rizki Haddi Prayoga , Fakhriyal Riyandi Yasin, Mutiara Annisa Tresna Ati Pages: 1 - 12 Abstract: The Indonesian railway system is currently experiencing a lot of developments in terms of technology. The Indonesian railway system has been integrated with technology 4.0, where all transaction processes, whether payment, ordering tickets or monitoring trains, can be monitored via electronic media. Of course, this technology must be supported by adequate infrastructure, one of which is the railroad crossing. In Indonesia, several railroad lines have been constructed, and many portal or crossbar railroads have also been constructed. The railroad gate is part of the railway system which has a very important role, especially in regulating the safety of train travel. The rail gateway has been a problem and a source of accidents in recent years. This is because there are no security facilities at any rail portals, causing drivers to continue to break traffic laws. The making of this automatic railroad doorstop uses the Prototype method, namely a simulation that uses Arduino UNO R3, servo motors, HC-SR04 ultrasonic sensors and other components that can support the manufacture of this railroad doorstop prototype. The prototype of this automatic train doorstop is equipped with many sensors that works automatically according to what is ordered, so that its use can be easily controlled and implemented in real life. This automatic railroad crossing system is expected to optimize the task of the railroad crossing guard by providing automation for the process of opening and closing the railway door and providing additional warning information for the community around the railway door location so as to reduce the potential for accidents caused by drivers or people who break traffic laws. PubDate: 2023-05-27 DOI: 10.31849/digitalzone.v14i1.13584 Issue No:Vol. 14, No. 1 (2023)
Authors:Nindian Puspa Dewi, Ubaidi Ubaidi, Ulin Najah Ismail Moadz Pages: 13 - 27 Abstract: Village Fund Direct Cash Assistance (BLT-DD) is cash assistance provided by the government to eligible residents through Village Officials whose recipients are determined based on many criteria. The process determine who is the most eligible citizen to be the recipient of BLT-DD takes a long time because of the large number of residents and the existence of several criteria used. There is a need for a decision support system that can assist village officials in choosing who is entitled to receive BLT-DD assistance. In this study, the application uses the Analytical Hierarchy Process (AHP) and Simple Multi Attributee Rating Technique (SMART) methods. The criteria used are, get assistance, income, floor area, type of floor, type of wall, and education. By using the AHP method, it is possible to optimize the weighting of the criteria and the SMART method to produce a ranking of residents who are entitled to receive BLT-DD. The results of the study indicate that this application can be used to provide recommendations to village officials in determining BLT-DD recipients. PubDate: 2023-05-27 DOI: 10.31849/digitalzone.v14i1.13165 Issue No:Vol. 14, No. 1 (2023)
Authors:Khairul Fuady, Eva Zulisa Pages: 28 - 42 Abstract: One of the causes of the high Maternal Mortality Rate (MMR) and Infant Mortality Rate (IMR) in Aceh is the delay in handling cases of at risk pregnancies due to the lack of availability of easily accessible and well-documented information about conditions during pregnancy. So far, manual reporting through data recapitulation report was difficult to access quickly if there are cases maternal and infant mortality. Fuzzy logic can be used as an alternative for classifying pregnant women at risk with supporting data when examining pregnant women. Data related to pregnancy checks will be analyzed with a Fuzzy Inference System (FIS) to obtain information on pregnancy risks. The results of this study indicate that FIS can determine the risk of pregnancy more detailed range than using a manual scoring card. The results of the defuzzyfication value will describe the final decision related to pregnancy risk which can be categorized into low risk, high risk and very high risk. The problem solving steps in this study can be used for algorithms in the development of application programming for risky pregnancy early detection systems based on programming languages. PubDate: 2023-05-27 DOI: 10.31849/digitalzone.v14i1.12423 Issue No:Vol. 14, No. 1 (2023)
Authors:Sulistiadi, Muhammad Salman Pages: 43 - 56 Abstract: Ransomware is a dangerous malware that blocks access to data through encryption, and it exploits device vulnerabilities to perform chain attacks from one system to another. This study results in modeling the threat of ransomware attacks using Bayesian Network. The structure of the model is created using device vulnerabilities that can be exploited. As the basis for calculating the probability of the model, the EPSS vulnerability score is used. The risk exposure rating is calculated through the joint probability distribution formulation based on attack scenarios. Our model shows that ransomware attacks are most likely to exploit the chain of vulnerabilities CVE-2021-26855, CVE-2021-26857, CVE-2021-27065, CVE-2021-36942, and CVE-2017-0144 which has a probability value of 0.046534. In addition, the use of the EPSS also makes the risk assessment more factual, accurate, and effective. The threat modeling method can help in identifying ransomware attacks through a chain of vulnerabilities, making risk assessment more precise. PubDate: 2023-05-27 DOI: 10.31849/digitalzone.v14i1.13788 Issue No:Vol. 14, No. 1 (2023)
Authors:Novem Uly, Hendry Hendry, Ade Iriani Pages: 57 - 67 Abstract: This research aims to implement deep learning in determining Covid-19 or normal cases using X-Ray imagery. The method used is CNN (ResNet50) and RNN (LSTM). The research phase begins with data collection, data preprocessing, method modeling, method testing and method evaluation. The data was taken from the kagle.com site with the amount of data used 1.000 images where 500 covid data and 500 normal data, the data is divided into 80% training data, 10% validation data and 10% test data. The results of the evaluation by calculating the ResNet50-LSTM confusion matrix have a value of 95% accuracy, 96% precision, 94% recall and 95% F1-score. At the method testing stage, the researcher got the results of the proposed method experiencing overfitting seen by the comparison of the loss values in the validation data which were not as good as the loss values of the training data. From the results of evaluation and method testing, research can be used as a recommendation in cases of Covid-19 or normal. PubDate: 2023-05-27 DOI: 10.31849/digitalzone.v14i1.13668 Issue No:Vol. 14, No. 1 (2023)
Authors:Agus Hermawan, Wilda Susanti*, Gusrio Tendra, Yermias Duha Pages: 68 - 76 Abstract: The Corona Virus (Covid-19) outbreak has had an impact on the education sector. This impact affects the delay in the student learning process. Because of this situation, technology that has developed significantly can be directed to make exams online, replacing conventional exams. Carrying out conventional exams requires time, effort and paper. Teachers cannot make assessments quickly and precisely, this will hinder the ranking of grades and of course affect the ranking of students in class. Exams in the form of paper allow cheating by students. Therefore, an online-based exam system was built. The online exam is designed using the Linear Congruent Method (LCM). The method used in the online exam system is the Linear Congruent Method (LCM). The built online exam can generate numerical randomization (modulo) from the process of students taking the exam in LCM calculations so that each student will get a different order of questions. Students will get the results of the answers automatically after completing the problem. The results of this study were tested by working on 50 questions at the Dharma Loka High School, with an accuracy rate of up to 100% using the randomization calculation process (modulo). PubDate: 2023-05-28 DOI: 10.31849/digitalzone.v14i1.13658 Issue No:Vol. 14, No. 1 (2023)
Authors:Basrul, Zuhra Sofyan Pages: 77 - 87 Abstract: This research was conducted to identify and analyze the factors that lead to the use of pirated software among lecturers at UIN Ar-Raniry Banda Aceh and to determine the impact of using pirated software. The research method used is of quantitative type with factor analysis techniques. The study sample was 114 people. The sampling technique used is convenience sampling. The data was obtained through the distribution of questionnaires to respondents, which were further analyzed using the factor analysis method. The Kaiser Meyer Olkin Measure of Sampling test results were 0.801, and the Bartlett test was equal to 153. The next stage applies the principal component analysis method to obtain four new formation factors. They are named the motivation factor consisting of 9 variables; the attitude factor consisting of 4 variables; the legal factor consisting of 2 variables; and the quality & price factor consisting of 3 variables. The results achieved can be a reference and consideration for the campus in digital transformation using original software. The research implications contribute to a paradigm shift for lecturers to use licensed software. Socially, compliance with the regulation of the use of licensed software creates a favorable academic environment and has an impact on increasing lecturer productivity. PubDate: 2023-05-28 DOI: 10.31849/digitalzone.v14i1.13176 Issue No:Vol. 14, No. 1 (2023)
Authors:Novia Lestari, Ozzy Secio Riza, Reno Ardinal Pages: 88 - 102 Abstract: Classification of text documents can be managed manually by using human-made classification rules. However, as many text document files exist today, the application of machine learning can help to classify the documents more effectively and the structured. Data mining with the Naïve Bayes algorithm can help the process of searching for a set of patterns or characteristics that explain and separate a classification of data based on the aim that the model can used to predict and classify the the data that has been used. This study uses text mining and pattern discovery techniques with the naïve Bayes algorithm used in the Indonesian language online news classification process with an accuracy test result of 63.9 and a low error rate of 41.02%. PubDate: 2023-05-28 DOI: 10.31849/digitalzone.v14i1.13596 Issue No:Vol. 14, No. 1 (2023)
Authors:Fladinand Alfando, Arya Sanjaya Pages: 103 - 114 Abstract: Campus marketing through photos and videos may only have a limited impact, but with the virtual reality campus tour, it is hoped that it can provide an interactive campus virtual reality experience for prospective students. This application is a web-based campus virtual tour application prototype that can be run on any device. The application was developed using the 3D Vista application and photos will be captured using a 360 camera. The prototype uses three collective rooms on campus with different descriptions to provide information about the campus environment and testing is carried out using the System Usability Scale method on 30 people. The results of this study are that a virtual reality campus tour application developed using the 3D Vista application has the potential to provide an innovative and attractive marketing tool for campuses. The evaluation results of SUS gave a score of 73 which means this application is relatively easy to use. This application has the potential to support campus marketing efforts PubDate: 2023-05-28 DOI: 10.31849/digitalzone.v14i1.13944 Issue No:Vol. 14, No. 1 (2023)
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