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Adi Widarma
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CESS (Journal of Computer Engineering, System and Science)
Published by Universitas Negeri Medan
ISSN : 25027131     EISSN : 2502714X     DOI : https://doi.org/10.24114/cess
Core Subject : Science,
Computer Science & IT
CESS (Journal of Computer Engineering, System and Science) contains articles on research results and conceptual studies in the fields of informatics engineering, computer science and information systems. The main topics published include: 1. Information security 2. Computer security 3. Networking & Data communication 4. Cloud & grid computing 5. Mobile Computing & Applications 6. Artificial Intelligence 7. Decision Support System 8. Data Minig 9. Other topics related to information technology
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 21 Documents
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Search results for , issue "Vol 8, No 1 (2023): January 2023" : 21 Documents clear
Sentiment Analysis on COVID-19 Vaccine using Naive Bayes Classifier, Support Vector Machine and K-Nearest Neighbors Monika Rani; Dian Prawira; Nurul Mutiah
CESS (Journal of Computer Engineering, System and Science) Vol 8, No 1 (2023): January 2023
Publisher : Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24114/cess.v8i1.40158

Abstract

Procurement of the COVID-19 vaccination has led to diverse opinions among Indonesian people on Twitter. Sentiment analysis on Twitter can be carried out to find out public opinion, especially among Twitter users. The data was used in the form of tweets with the topic of the COVID-19 vaccine using the keywords covid 19 vaccine, covid vaccine, AstraZeneca, Sinovac, Moderna, Pfizer, Novavax and Sinopharm. analysis of the performance of the Naive Bayes Classifier, Support Vector Machine and K-Nearest Neighbors algorithms to determine the results of the accuracy level between the algorithms. The highest classification test is using the Support Vector Machine with an accuracy rate of 0.701. The results of the comparison of algorithms tested using tweet data on the topic of the COVID-19 vaccine found that the Support Vector Machine was better than the Naive Bayes Classifier and K-Nearest Neighbors. From the classification test carried out using COVID-19 vaccine tweet data with 2500 data. The amount of data after going through the data processing process is 1052 data. Neutral sentiment results in as many as 645 positive sentiments as many as 250 and negative sentiments as many as 157.
Transaction Data Security Using AES and RC4 Puji Sari Ramadhan; Muhammad Syahril; Rini Kustini; Hendryan Winata; Robin Darwis Gea
CESS (Journal of Computer Engineering, System and Science) Vol 8, No 1 (2023): January 2023
Publisher : Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24114/cess.v8i1.41212

Abstract

This study discusses the effectiveness of using AES (Advanced Encryption Standard) and RC4 (Rivest Chipper 4) as digital data security algorithms to prevent and protect transaction data from irresponsible parties. This needs to be done because the development of sales transactions or other services has used digital technology a lot. This situation causes the need to secure digital data from existing transactions, so that transaction data can be stored safely. Transaction data security is carried out by changing data into ciphers or codes that are difficult to read using the AES (Advanced Encryption Standard) and RC4 (Rivest Cipher 4) algorithms. This research begins by collecting existing transaction data and then transforming it into ASCII code. The results of the transformation will be used to perform calculations using the AES algorithm. After completing the calculation process using the AES algorithm, then do the calculations using RC4. These results will be stored in the database so that the transaction data that has turned into these codes cannot be known by other parties. The combination of the AES and RC4 algorithms is carried out to strengthen data encryption because there are more and more rotation systems and double security is carried out so that digital data is not easily read and misused. With the presence of this research, it can be shown that the AES and RC4 algorithms are capable of encrypting existing transaction data with multiple levels of security. 
Application of Point Tracking Technology in 360 Degree Panorama Virtual Tour Applications for Introduction to Siliwangi University Campus Muhammad Adi Khairul Anshary; Cecep Muhamad Sidik Ramdani; Euis Nur Fitriani Dewi; Andi Nur Rahman; Rezi Syahriszani
CESS (Journal of Computer Engineering, System and Science) Vol 8, No 1 (2023): January 2023
Publisher : Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24114/cess.v8i1.39363

Abstract

Most of the campus area introduction media use brochures to provide information to prospective students. This media among teenagers is no longer attractive. Most prospective students prefer information through multimedia such as short videos. Due to the limited time of video media, very little content is provided so that delivery will be very less. The use of Virtual Tour 360 multimedia technology will help to provide clear information in the form of text and the application of Point tracking technology will make it easier for users to feel like they are in a campus environment. The methodology used in making this application is the Luther-Sutopo version of the Multimedia Development Life Cycle (MDLC). The 360 Degree Panorama Virtual Tour Application Introduction to the Siliwangi University Campus is expected to make it easier to convey information that can be easily accepted by users. This application can see a real environment simulation on the Siliwangi University campus by representing information in the form of 360° panoramic images making it easy to display information visually. The test results obtained from the alpha test of the application of Point tracking can make it easier for users to run the application and the beta test results that the application functions very well get a score of 83.75%. 
Comparasion KNN, Decision Tree and Naïve Bayes for Sentimen Analysis Marketplace Bukalapak Elisa Nathania Halim; Baenil Huda; Anggi Elanda
CESS (Journal of Computer Engineering, System and Science) Vol 8, No 1 (2023): January 2023
Publisher : Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24114/cess.v8i1.41385

Abstract

The number of platforms currently makes it easier for users to provide reviews, one of which is the Bukalapak application on the Google Play Store. While both negative and positive reviews can influence the value of the app, users can also be affected by the app's sentiment reviews. Therefore it is necessary to carry out sentiment analysis to classify negative and positive reviews. This research uses review data of 1000 reviews and then classifies them using the RapidMiner application using three methods, namely KNN, Naive Bayes, and also the Decision Tree. The results of the KNN method obtained accuracy values of 85.03%, precision of 84.98%, and recall of 100.00%, then for the Naive Bayes method obtained accuracy values of 73.95%, precision of 100.00%, and recall of 69.26%, and for the Decision Tree method obtained 89.12% accuracy value, 88.62% precision, and 100.00% recall. this can prove that the Decision Tree method is superior to the KNN method and also the Naive Bayes method.
Activation Control System in Motorized Vehicles Using the Global Positioning System (GPS) Aris Budiyarto; Abdur Rohman Harits Martawireja; Mohammad Harry Khomas Saputra; Gun Gun Maulana
CESS (Journal of Computer Engineering, System and Science) Vol 8, No 1 (2023): January 2023
Publisher : Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24114/cess.v8i1.39663

Abstract

In Indonesia, the theft rate is still quite high. According to Bappeda data, cases of theft still tend to be high. In 2019, there were 362,000 cases of theft. CCTV use is still ineffective because at the time of the theft of goods, we only know the goods taken and the perpetrators. In order to catch the perpetrators and return the goods, it is necessary to process them first and find the location of the perpetrators themselves. Therefore, we propose an idea entitled "Activation Control System in Motorized Vehicles Using GPS". Where this tool will detect the position of a vehicle so that this vehicle remains in a restricted area. When this vehicle leaves the restricted area, the GPS system will send a signal explaining that the vehicle is leaving the area. So, if there is a theft, when the vehicle has moved away from about 50 meters from the area that has been locked, a notification will appear which will be displayed on the web application. The research stages that we will work on are first identifying the equipment and systems that will be used and conducting a study of the technology literature that will be developed, then identifying the theoretical and empirical system design and knowing the basic elements. Then master and understand the characterization of components and analyze the main functions so that they can work properly. Then do modelling and simulation and ensure that the components to be developed can work properly. And the final stage is to ensure that the system equipment is valid and reliable. Based on the results of the study, it shows that the system is active when the actual position away from the locked position/area as far as 100 meters has successfully functioned. Where the information changes to "Out of reach" from the previous "Within Reach" and there are notifications in the form of sound and vibration to increase security from theft.
Application of Virtual Assistant in Information System for Student Practicum Case Study Laboratory Informatics Department Siliwangi University Cecep Muhamad Sidik Ramdani; Andi Nur Rachman; Euis Nur Fitriani Dewi
CESS (Journal of Computer Engineering, System and Science) Vol 8, No 1 (2023): January 2023
Publisher : Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24114/cess.v8i1.39365

Abstract

Practical activities are carried out in an orderly and timely manner and require systematic recording of activities. The implementation of practicum activities takes place in the Siliwangi University laboratory, to create conducive conditions for practicum activities, a system must be able to support academic success. Not only that, due to the COVID-19 pandemic, previous practicum lectures were held offline and campus policy required online learning. These problems can be overcome by building a logbook information system that can record and keep records of laboratory activities automatically. This information system was created using the Extreme Programming system development method. Starting from database design, system design with UML, system development with Visual Studio. NET 2021. This technology can be used by universities for practical activities at the Siliwangi University Laboratory. The application will remind students to complete each activity in each session by displaying notifications in each practicum schedule, rewards, announcements, and other information related to practicum activities. All activities must be recorded in the application. Based on the results of black box testing, the system can run according to the system test design that the response from each student to the application used is 75.68% which can be concluded that the application of virtual assistant is in the interesting category.  
Implementation of the Association Rule Method using Apriori Algorithm to Recognize The Purchase Pattern of Pharmacy Drugs “XYZ” Fadhila Putri Utami; Arief Jananto
CESS (Journal of Computer Engineering, System and Science) Vol 8, No 1 (2023): January 2023
Publisher : Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24114/cess.v8i1.40377

Abstract

XYZ Pharmacy is a Special Health Service Point for employees and retirees of the XYZ company. This pharmacy carries out the process of buying and selling drugs by providing various types of drugs. The number of sales transactions in each day, resulting in sales data will increase over time. If the data is left alone, the pile of data will only become archives that are not utilized. By carrying out the data mining process, this data can be used to produce information that can be used to increase sales transactions at XYZ Pharmacy. The method used in this study is the Association Rule which functions to analyze the most sold and purchased drugs simultaneously, this analysis will be reviewed from drug sales transaction data at the XYZ Pharmacy. The application of the a priori algorithm in this study succeeded in finding the most item combinations based on transaction data and then formed an association pattern from the item combinations. By knowing the types of drugs that are often purchased together through identification of purchasing patterns, it is very useful for the XYZ Pharmacy to maintain the availability of the drugs.
Forecasting COVID-19 Cases in Indonesia, Malaysia, Philippines, and Vietnam Using ARIMA and LSTM Marina Wahyuni Paedah; Fergyanto E. Gunawan
CESS (Journal of Computer Engineering, System and Science) Vol 8, No 1 (2023): January 2023
Publisher : Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24114/cess.v8i1.41209

Abstract

COVID-19 has severely impacted the global economy, including ASEAN countries. Various plans and strategies are still needed during the pandemic-to-epidemic transition period to minimize the risk of COVID-19 transmission. The research focuses on the total number of confirmed cases of COVID-19 in Indonesia, Malaysia, the Philippines, and Vietnam, which are among the ASEAN countries with the highest number of cases in Southeast Asia. Those countries have cultural similarities, where gathering with friends and family is an important part of social life. This research evaluates the ability of ARIMA and LSTM to predict COVID-19 cases in each country, using daily data from January 23, 2020 to October 22, 2022. Datasets published by Johns Hopkins University (JHU) and Our World in Data (OWID) are used, which are accessible through Github. Compared to ARIMA with  R2 of 0,8883 for Indonesia, 0,8353 for Malaysia, 0.97291 for the Philippines, and -3.105 for Vietnam, LSTM model can predict better in the four sampled ASEAN countries, with an R2 of 0.9996 for Indonesia, 0.9707 for Malaysia, 0.97291 for the Philippines, and 0.9200 for Vietnam.
SARS-CoV-2 Detection from Lung CT-Scan Images Using Fine Tuning Concept on Deep-CNN Pretrained Model Simeon Yuda Prasetyo
CESS (Journal of Computer Engineering, System and Science) Vol 8, No 1 (2023): January 2023
Publisher : Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24114/cess.v8i1.40897

Abstract

The problem of the spread of COVID-19 (SARS-CoV-2) is spreading fleetly and worldwide. Beforehand discovery and opinion of complaint is veritably important to ensure the right remedy so that it needs to be enforced through various practical approaches. In former studies, complaint discovery through medical imaging has started to appear and get a good delicacy of around 80 to 90 percent using machine learning. In the deep learning era, some trials get better accuracy of 95 percent using the traditional deep learning approach. Now, deep learning has developed more fleetly, especially for image classification. therefore, it's necessary to experiment with a pretrained model approach to medical images. In addition, the fine tuning approach will also be an aspect of the approach that will be carried out in this trial to be compared and to find out its effect, specifically on CT-Scan images of the lungs for the discovery of COVID 19. The results of this experiment showed that the pretrained model approach can get high accuracy. Relatively high accuracy, the smallest testing accuracy in this trial reached 94.78 percent of the Xception without fine tuning phase, this result has beaten the machine learning approach which is didn't reach 90 percent of accuracy. The best experiment testing accuracy get 97.59 percet on the VGG 16 by applying fine tuning. The results of this trial also show that the fine tuning stage (for the top 10th layers) can increase the accuracy of the model.
Implementation of Digital Libraries in Book Management and Donation in the Nyala Aksara Community Saut Pintubipar Saragih; Mesri Silalahi
CESS (Journal of Computer Engineering, System and Science) Vol 8, No 1 (2023): January 2023
Publisher : Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24114/cess.v8i1.41698

Abstract

Web Based Applications has been implemented to organize bookstore and it is reuired to handle a wider library system, especially in a non-profit organization such as Nyala Aksara community library in Batam City. All library sources especially book collections come from donations from the community or charity, with this situation it is expected for the commitee to be able provide a system to reach more people to donate with easiness. The E-library Web application is expected to be able to provide solutions for the Nyala Aksara organization management. The main problems is the donations systems that have not been systematically organized, and then borrowing and returning system for users. E-library application will be built using web-based programming like HTML PHP, MySQL database and designing method with UML Method. The e-library will provide services for those who want to donate books, this application will also provide a system that is able to manage borrowers and how to process the book returning. The results of this research is producing a solution for the organization called E-libarary which is a web-based library management.

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