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Engineering, Mathematics and Computer Science Journal (EMACS)
Published by Universitas Bina Nusantara
ISSN : -     EISSN : 26862573     DOI : https://doi.org/10.21512/emacs
Core Subject : Science, Education, Engineering,
Civil Engineering, Building, Construction & Architecture Computer Science & IT Engineering Industrial & Manufacturing Engineering Mathematics
Engineering, MAthematics and Computer Science (EMACS) Journal invites academicians and professionals to write their ideas, concepts, new theories, or science development in the field of Information Systems, Architecture, Civil Engineering, Computer Engineering, Industrial Engineering, Food Technology, Computer Science, Mathematics, and Statistics through this scientific journal.
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 171 Documents
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The Role of Network Security in Class Conference During COVID-19 Pandemic Ivan Sebastian Edbert; Julio Pramaitama; Kevin Tio; Muhammad Rizky; Alvina Aulia
Engineering, MAthematics and Computer Science (EMACS) Journal Vol. 4 No. 3 (2022): EMACS
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/emacsjournal.v4i3.8634

Abstract

Security is crucial for the network. But there are still system leaks, especially in class conferences during the pandemic. Because of a lot of data exchange and data entry, some viruses are difficult to identify. So, the role of network security is vital. Many viruses spread through links, and others can access cases of misuse of links; the issue is called Zoom bombing. So, from managing the instability of data in and out of conference classes during this pandemic, many activities are carried out online that awareness of more comprehensive network security. With the COVID-19 pandemic, class conferences are prevalent in today’s world. Millions of people use it for various reasons, and one of them is for education. However, there are issues related to the network’s security where users’ data was stolen and impersonated or network trafficking, which will cause fault and disruption in the network. This research have 3 methodologies include Systematic Literature Review, Research Questions (identify the focus of the literature review, which helps process the data more clearly), Result Finding (the study of an existing paper with specific keywords to answer the research questions). As the result, it can be concluded that there are many ways to prevent attacks by improving the network’s security such as network security defense mechanisms and firewall. So that everything can be petrified in terms of comfort in meet conferences so that class conferences activities can run safely.
A Systematic Literature Review: Limitation of Video Conference Rezki Yunanda; Ian Jeremiah Cahyadi; Bryan Theophilllus; Jason Oei; Ivan Sebastian Edbert; Alvina Aulia
Engineering, MAthematics and Computer Science (EMACS) Journal Vol. 4 No. 3 (2022): EMACS
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/emacsjournal.v4i3.8635

Abstract

The Covid-19 pandemic that has hit the world has resulted in limited human activities. Video conferencing is one solution for carrying out activities. Video conferencing helps people reduce the spread of Covid-19 and connects people. With video conferencing, people can meet without being limited by space and time. However, video conferencing still has various drawbacks, such as the inability to interact. Because we only see the video, the lack of technology due to video conferencing requires us to use technology such as computers or cell phones that a stable and fast internet network must support to ensure smooth video conferencing. In this paper, the researcher conducted a literature study to determine the limitations of video conferencing. The results show the various reasons for video conferencing restrictions. Some of these reasons are experienced by lecturers, students, or the lack of infrastructure. Students are challenged to improve their level of study due to the lack of technological support that supports only using video conferencing.
Pengembangan “INDOLATURE”: Aplikasi Website Bertemakan Kebudayaan Sastra Indonesia Dion Darmawan; Wishnu Wijaya; Christian Surjanto; Ngakan Made Prakasa Judha; Muhammad Dana Paramita
Engineering, MAthematics and Computer Science (EMACS) Journal Vol. 4 No. 3 (2022): EMACS
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/emacsjournal.v4i3.8655

Abstract

Indonesian literature is a field of science that studies poetry, prose, stories, novels, scripts, rhymes, and other literary works. Along with the development of the era and technology, interest in reading and interest in making Indonesian literature is decreasing. Along with the development of communication and information technology, the dissemination of information becomes faster and wider, for example through the use of the internet. Based on the results data from the research, the authors developed a website-based application that can publish Indonesian literary works with an attractive and interactive display for makers and readers in order to preserve and increase public interest in Indonesian literary culture. The research method used for data collection is using observation techniques, questionnaires, and interviews. As for the development of this website-based application using the Agile Development approach, with the Kanban method. The programming language used is JavaScript using the React.js and Express.js libraries and frameworks, as well as MongoDB for data storage. The results of this research, it is hoped that with the rapid advancement of science and technology, we want to combine technology and Indonesian literature by creating a web application that can help connect readers with other literary writers and reintroduce Indonesian literary culture more. We hope that this application can increase public interest in Indonesian literary culture. In addition, it is hoped that the wider community can access Indonesian literary works more quickly, easily, and comfortably.
Comparing SVM and Naïve Bayes Classifier for Fake News Detection Nurhasanah Nurhasanah; Daniel Emerald Sumarly; Jason Pratama; Ibrahim Tan Kah Heng; Edy Irwansyah
Engineering, MAthematics and Computer Science (EMACS) Journal Vol. 4 No. 3 (2022): EMACS
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/emacsjournal.v4i3.8670

Abstract

Fake news has been evolving into a problem that is getting even more challenging. Technology has been misused to spread false information about many things, such as war, pandemics, and the stock market. Unfortunately, this issue is not a big deal for some people without conscious consumption of that news. Hence, being part takes a role in combating the spread of false information using the advancement of technology. This study proposed two methods of machine learning model, Support Vector Machine (SVM) and Naïve Bayes, to classify fake news. Furthermore, to assert the applicability of models by examining news articles dataset which contain two labels, reliable and unreliable news. The higher accuracy is 0.96 using the SVM model
Prediction of Heart Disease UCI Dataset Using Machine Learning Algorithms Anderies Anderies; Jalaludin Ar Raniry William Tchin; Prambudi Herbowo Putro; Yudha Putra Darmawan; Alexander Agung Santoso Gunawan
Engineering, MAthematics and Computer Science (EMACS) Journal Vol. 4 No. 3 (2022): EMACS
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/emacsjournal.v4i3.8683

Abstract

Heart disease is inflammation or damage to the heart and blood vessels over time. the disease can affect anyone of any age, gender, or social status. After many studies trying to overcome and learn about heart disease, in the end, this disease can be detected using machine learning systems. It predicts the likelihood of developing heart disease. The results of this system give the probability of heart disease as a percentage. Data collection using secret data mining. The data assets handled in python programming use two main algorithms for machine learning, the decision tree algorithm, and the Bayes naive algorithm which shows the best of both for heart disease accuracy. The results we get from this study show that the SVM algorithm is the algorithm with the most excellent precision. and the highest accuracy with a score of 85% in predicting heart disease using machine learning algorithms.Heart disease is inflammation or damage to the heart and blood vessels over time. the disease can affect anyone of any age, gender, or social status. After many studies trying to overcome and learn about heart disease, in the end, this disease can be detected using machine learning systems. It predicts the likelihood of developing heart disease. The results of this system give the probability of heart disease as a percentage. Data collection using secret data mining. The data assets handled in python programming use two main algorithms for machine learning, the decision tree algorithm, and the Bayes naive algorithm which shows the best of both for heart disease accuracy. The results we get from this study show that the SVM algorithm is the algorithm with the most excellent precision. and the highest accuracy with a score of 85% in predicting heart disease using machine learning algorithms.
Designing IoT-Based Smarthome System With Chatbot Muhamad Keenan Ario; David Leon; Muhammad Rizki Pratama; Gentrya Wirya Pamungkas
Engineering, MAthematics and Computer Science (EMACS) Journal Vol. 4 No. 3 (2022): EMACS
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/emacsjournal.v4i3.8787

Abstract

Smart home system aim to maximize surveillance, monitoring, and security. This system is integrated with telecommunications and control systems from the microcontroller to create the Internet of Things (IoT). Nowadays, home appliances are integrated with the Smart System that connected to the internet. On the other hand, messenger applications now integrated with chat bot with Artificial Intelligence to make user easier to communicate. This trend made a possibility to implement a system where a home appliance can be operated by only using a messenger application. In this research, a Smart home system designed with a client-server system based on Raspberry Pi as microcontroller and Telegram Messenger as interface that perform the control communication. The process separated into three stages: design, implementation, and result. The design consists of designing the server, interface, and Smart Home control system. To test the performance, the Messenger Bot are compared with other direct controller application. The result show that the Telegram Messenger application is suitable and more convinient for being the IoT controller.
Operasi Dasar Baris/Kolom Matriks Secara Interaktif Dengan Menggunakan R I Gusti Agung Anom Yudistira; Rinda Nariswari
Engineering, MAthematics and Computer Science (EMACS) Journal Vol. 5 No. 1 (2023): EMACS
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/emacsjournal.v5i1.9206

Abstract

The linear algebra applications available today usually only provide the result. So, it is a challenge to overcome this, and innovation is needed in the computing aspect. One of the popular and open-source programming languages ​​is R. The computational innovation in R needs to be explored further, to explore the R programming logic. The creation of a function environment with the list function and the involvement of local and global variables/objects has received little attention. Based on the problems formulated, this study proposes two objectives, namely (1) developing an R program that is able to provide interactive and step-by-step solutions, to obtain a solution of a system of linear equations, and (2) to explore R’s ability to create and handle global variables. An R program is created, starting with creating a function environment. This function environment is filled with four related functions, namely “exchange”, “multiply”, “fold”, and “yield”. These four functions are connected to each other through a global object. Users can type in each function to perform row/column operations, interactively and step by step. The environmental function in this program, is named OBE. The OBE function accepts input in the form of a coupling matrix derived from a system of linear equations. The final result of this interactive process chain is given by the “result” function. The result function will display two matrices, namely the Original Matrix which is the input and the Equivalent Matrix.
Breast Cancer Classification Using Outlier Detection and Variance Inflation Factor Budi Juarto
Engineering, MAthematics and Computer Science (EMACS) Journal Vol. 5 No. 1 (2023): EMACS
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/emacsjournal.v5i1.9223

Abstract

In terms of malignant tumors, breast cancer is one of the most prevalent. Breast cancer is a form of cancer that develops in the breast tissue when the surrounding, healthy breast tissue is overtaken by the uncontrollably growing cells in the breast tissue. Several features or patient conditions can be used in a machine learning approach to predict breast cancer. Machine learning will be utilized in these situations to determine if the cancer is malignant or benign. The Wisconsin Breast Cancer (Diagnostic) Data Set, which contains 32 characteristics and 569 collected data, was the dataset used in this research.. Feature selection in this study is done by eliminating outliers using the upper and lower quartile of each feature then feature selection is also carried out on features that have features that have a high variance inflation factor. The machine learning methods used in this research are Logistic Regression, Random Forest, KNN, SVC, XG Boost, Gradient Boosting, and Ridge Classifier. The selection of this method is based on the target that will be predicted by 2 labels, namely benign cancer, and malignant cancer. The result obtained is that the selection of features using the variance inflation factor increases the accuracy of the previous Logistic Regression and Random Forest methods from 98.25% to 99.12%. The method that has the highest level of accuracy is the Logistic Regression and Random Forest methods which have a value of 99.12%. The next research will be developed by trying other optimization techniques for hyperparameter tuning.
Improve Learning Programming through Small Private Online Course and Virtual IDE Muhammad Taufiq Zulfikar
Engineering, MAthematics and Computer Science (EMACS) Journal Vol. 5 No. 1 (2023): EMACS
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/emacsjournal.v5i1.9234

Abstract

In learning programming languages ​​there are some technical problems such as the difficulty of installing IDE applications and tend to be heavy, cannot be used on various operating system platforms and there are no programming tutorials. By providing online and open learning content for certain organizations or often called SPOC (Small Private Online Course) and Virtual IDE to support SPOC, it can help students to improve programming skills. The purpose of this research is to create a SPOC LMS that has a Virtual IDE as a learning support. The Quantitative Method was used as a research method in this study to make a conclusion from the experimental results. The results of this study concluded that LMS SPOC and Virtual IDE can help students understand language programming.
IoT Based Vehicle Safety Controller Using Arduino Said Achmad; Raditya Adinugroho; Nur Safii Hendrawan; Thomas Franklin
Engineering, MAthematics and Computer Science (EMACS) Journal Vol. 5 No. 1 (2023): EMACS
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/emacsjournal.v5i1.9251

Abstract

Several people try to break into vehicles and steal vehicles left by their owners, sometimes even without the owner's knowledge. There are still various ways that can be done to a turn on the vehicle without the key from the vehicle so that the vehicle can be stolen easily. Due to the ease of break-in from some vehicles, several additional security implementations can be installed. One of these ways is to implement IoT and RFID. There are several implementations of IoT as an extra device for safety and tracking vehicles. RFID can be Implemented as an additional key or access. IoT and RFID can be combined to provide additional safety for vehicles and prevent vehicle theft. This research aims to propose a device that uses IoT technology and RFID to keep the vehicle safe and track the use of the vehicle. This research use Arduino, RFID, and GPS module. The proposed device was tested under various conditions of RFID use and the level of accuracy of the GPS module used. The test results show that the proposed tool can work well for security and tracking needs.

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