Muhammad Agreindra Helmiawan
@unsap.ac.id
Fakultas Teknologi Informasi
Universitas Sebelas April
RESEARCH INTERESTS
Computer Science
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
A'ang Subiyakto, Dwi Yuniarto, Aedah Binti Abd. Rahman, Muhammad Agreindra Helmiawan, Mulya Suryadi, and Dani Indra Junaedi
IEEE
Suburban areas become an object of research that attracts researchers in terms of assessing the quality of the Online Course Website. The findings at the beginning of the research regarding the poor quality of information on the Online Course make users feel confused. The purpose of this study is to establish the quality of the Online Course Website using the Webqual Method and to determine what factors affect the quality of the Online Course Website in the Suburban Area during the Post-Pandemic. The researcher reports on the results of the research, that the quality of the Online Course website in the Suburban Area using the Webqual Method is categorized as good, as shown from the results of the analysis on the Usability Quality and Service Interaction Quality variables. While the factors that affect the Quality of the Online Course Website are obtained from proving 3 hypotheses which state that everything is acceptable. The contribution of this research is that it can be used as a reference by further researchers regarding alternative problem solving in making an Online Course website with the Webqual Method. Some of the things that the researcher reports can also be used as material for the Online Course Website Developer. Of course with a different object of research will be very interesting to do.
Esa Firmansyah, Muhammad Agreindra Helmiawan, Irfan Fadil, Fathoni Mahardika, Dian Budiana, and Reny Rian Marliana
IEEE
The current management of higher education cannot be separated from an information system, one of which is an academic information system. Along with the many accesses from various devices, there are obstacles in the form of an unresponsive interface when accessed on a mobile display. The purpose of this study is to assess the user interface of an integrated academic information system in increasing the comfort of the system from the user's point of view. Technology Acceptance Model is a method that can be used to measure user perceptions of the ease and usability of the system. In other words, this research is to assess users' willingness to accept useful facilities and make it easier for users, both in terms of function and appearance. Overall, the academic information system assessment variable is considered good by users, namely, the ease of use factor is worth 1900 smaller than the usefulness factor which is worth 2033, but some indicators have a small total score below 300. Therefore, it is necessary to measure the other criteria in identifying user wants and needs as a whole.
Irfan Fadil, Muhammad Agreindra Helmiawan, Fidi Supriadi, Asep Saeppani, Yanyan Sofiyan, and Agun Guntara
IEEE
In people's daily lives, many things happen such as work, school, and business to buy and sell. In carrying out their activities, the community uses the goods they need and later these community activities will produce waste. This waste should be processed according to the type of waste, but people often equate or collect the waste into a container before it goes into the trash or even throws the garbage into a ditch or river, causing garbage to accumulate in one place because it makes it difficult to sort waste or even waste it to cause flooding because it clogs the drainage channel leading to the river. The aim of the research is to calculate the accuracy of the Naïve Bayes algorithm in classifying waste classifiers. The design of this waste classifier using arduino aims to apply the naive Bayes algorithm in classifying organic, inorganic, and hazardous waste, the naive Bayes algorithm is an algorithm for classification with quite a bit of data training. This tool is designed using Arduino uno r3 with capacitive proximity sensor, $16\\mathrm{x}2$ lcd, and data table to look for opportunities or data training. From the results of the waste classification test carried out using this waste classifier, the application of the naive Bayes algorithm in the waste classification tool using Arduino got 28% accuracy in the first test, 57% in the second test, and 71% in the third test. With these results, the naive Bayes algorithm can function or work well for classifying waste in the design of a waste classifier using Arduino.
Esa Firmansyah, Muhammad Agreindra Helmiawan, Ali Rahman, Pepen Supendi, Sri Bekti Handayani Ningsih, Maya Suhayati, and Aedah Abd Rahman
AIP Publishing
Humankind throughout the world are currently in a state of collapse due to the outbreak of Corona Virus Disease (COVID-19) which began in Wuhan, China. Later on, it was announced as the pandemic situation according to WHO. Overall countries have implemented social distancing, while Indonesia has implemented a policy of learning from home, working from home, and worship at home or better known as work from home (WFH). This study aimed to determine the level of readiness to implement e-learning during WFH due to the pandemic COVID-19 spreads along with the challenges in the 4.0 revolution in millennials. The model that used was the Aydin & Tasci model which measures four main factors namely technology, innovation, people, and self-development. Data collection was conducted online using Google Form, while data processing uses a descriptive statistical method mapped based on the Aydin & Tasci version of the e-learning readiness index. The results showed that the overall e-learning readiness index might indicate that the system was ready to be implemented, but required a slight increase in several factors, namely innovation increase, human, and self-development factors. The results and discussion of the study showed the readiness of e-learning to follow the demands of Revolution 4.0, even though it was done during WFH because of the COVID-19 pandemic outbreak.
Irfan Fadil, Muhammad Agreindra Helmiawan, and Yanyan Sofiyan
IEEE
Bitcoin is a cryptocurrency known to have high price fluctuation. Investment depends on price fluctuations which have a high level of risk. Bitcoin investment has these principles. To avoid losses and gain profits, there needs a method that may be used to make forecasts of the price of bitcoin accurately. In this research, Bitcoin price predictions were deployed based on bitcoin price data obtained in the past (Time Series Forecasting) using the method Support Vector Regression. The data retrieved is weekly Bitcoin price data from January 2018 to March 2020. Bitcoin price data is nonlinear, so a kernel is used Radial Basis Function. Meanwhile, the variables of the Support Vector Regression method are optimized using Grid Search Method. The purpose of the research is to determine the accuracy of the Support Vector Regression method by looking at the result of the Mean Absolute Percentage Error value. The research showed that the Mean Absolute Percentage Error value obtained was equal to 10,74 % with parameter value $\\mathbf{C=5,} \\boldsymbol{\\varepsilon=0.004}$, and $\\boldsymbol{\\gamma=0.07}$. The Mean Absolute Percentage Error value indicates that the prediction results are categorized as a good prediction.
Muhammad Agreindra Helmiawan, Eggi Julian, Yavan Cahyan, and Asep Saeppani
IEEE
Security of data and information in servers connected to networks that provide services to user computers, is the most important thing to maintain data privacy and security in network security management mechanisms. Weaknesses in the server security system can be exploited by intruders to disrupt the security of the server. One way to maintain server security is to implement an intrusion detection system using the Intrusion Detection System. This research is experimenting to create a security system prototype, monitoring, and evaluating server security systems using Snort and alert notifications that can improve security monitoring for server security. The system can detect intrusion attacks and provide warning messages and attack information through the Intrusion Detection System monitoring system. The results show that snort and alert notifications on the security server can work well, efficiently, and can be handled quickly. Testing attacks with Secure Shell Protocol and File Transfer Protocol Brute Force, Ping of Death and scanning port attacks requires a detection time of no more than one second, and all detection test results are detected and send real-time notification alerts to the Administrator.
Muhammad Agreindra Helmiawan, Irfan Fadil, Yanyan Sofiyan, and Esa Firmansyah
IEEE
The use of Cloud Computing has advantages that have the potential to be an extraordinary service in supporting work procedures that can be carried out anywhere via the internet. Through the internet, we can carry out activities anywhere, but it will also cause other problems that will arise because of access via the internet, one of which is from the security side, system and security management on a computer is very crucial for securing a lot of data on it. The purpose of this research is to provide suggestions related to security management in Cloud Computing, especially in the sectors of Integrity, Authority, Privacy, and Confidentiality, also propose the proposed Concepts and Recommendations which are expected to improving security for Cloud Computing security and detection intruders who break into cloud computing systems using Intrusion Detection System and networks using Intrusion Detection System methods. Further research can be implemented and performed for improving security on cloud computing.
Fidi Supriadi, Muhammad Agreindra Helmiawan, Yan Yan Sofiyan, and Agun Guntara
IEEE
Changes in the learning environment have an impact on changing the presentation of the learning process. Learning success can be supported by e-learning. Micro-lectures, as short video-based learning technology, are one of the most widely used models. However, based on several studies, there are weaknesses, namely the tendency of students to only listen to videos compared to accessing other learning components. This paper aims to describe the concept of integrating micro-lectures into a 3D virtual world simulation as an alternative to solve this problem. The DSRM method was chosen to present the concept. This method consists of six stages, including identify problems and motivate, define objectives of a solution, design and development, demonstration, evaluation, and communication. The results of the model implementation show differences in the success in the learning process between the use of micro-lectures and the combination of micro-lectures and 3D Virtual world simulation.
Muhamad Agreindra Helmiawan, Esa Firmansyah, Irfan Fadil, Yanvan Sofivan, Fathoni Mahardika, and Agun Guntara
IEEE
Open Web Application Security Project 10 is a web application security testing framework method that focuses on web application security to find weaknesses in a website. The Open Web Application Security Project 10 aims to ensure the safety of websites in form checklists. Open Web Application Security Project 10 has the ten most dangerous types of website vulnerabilities such as injection, broken authentication, sensitive data exposure, Extensible Markup Language external entities, corrupted access control, security misconfiguration, cross-site scripting, unreliable deserialization, segment exploitation with known weaknesses, and lack of logging and checking. This paper analyzes and tests the security of the web along with six sub-domains with the aim of knowing and assessing the security level of a website, whether additional security is needed, and recommendations on the website. The results of this paper indicate that the web has a security level 80%, web informatics engineering subdomain 60%, information systems 60%, informatics management 60%, integrated academic system 80%, student acceptance 80% and e-learning 80%.
Irfan Fadil, Muhammad Agreindra Helmiawan, and Dani Indra Junaedi
IEEE
The number of applicants entering each department at STMIK Sumedang has increased and decreased from year to year. The data can be used to gain knowledge and learning by searching for stored patterns. One of them is to predict the number of registrants in the following year. STMIK Sumedang doesn't have that system yet. Objectives This study aims to apply and analyze the accuracy of the least square method to predict the number of prospective students. This method is very suitable to be used to predict the magnitude of variables in time series. The number of applicants entering each department is entered based on a period, namely Information Engineering, Information Systems, and Information Management. Existing data amounted to five time periods, consisting of five years of new student admission data. To calculate the error rate, mean absolute deviation, mean square error, and mean absolute percentage error is used. With prediction results for 2020 obtained, are 225 people for Informatics Engineering, 82 Information Systems, and 11 Informatics Management. Besides, the results of the measurement of forecasting suitability with these methods include Informatics Engineering as much as 0.79%, Information Systems 0.8%, and Information Management as much as 3.4%. The results of this study prove that to predict the number of registrants on the admission of new students using the least square method.