Jurnal PROCESSOR

V2V Communication in Smart Traffic Systems: Current status, challenges and future perspectives

Fri, 03 May 2024 00:00:00 +0800

Implementing V2V communication in intelligent traffic systems has been a topic of growing interest due to its potential to improve road safety and traffic flow. However, the widespread adoption of V2V communication in intelligent traffic systems could be enhanced by various challenges, such as infrastructure cost, security, and interoperability. These challenges must be addressed to improve the potential benefits of V2V communication. The problem statement of this study is to examine the potential benefits and challenges of V2V communication in intelligent traffic systems and provide insights into the current state of the art in V2V communication research. The proposed approach is to conduct a literature review of recent research on V2V communication in intelligent traffic systems to identify the potential benefits and challenges of V2V communication and the current state of the art in V2V communication research. The study aims to contribute to the field by comprehensively understanding the implementation of V2V communication in intelligent traffic systems and informing potential future research in this area. V2V communication can improve road safety and traffic flow in intelligent traffic systems. However, more research is needed to address the challenges and develop advanced and cost-effective V2V communication systems.

Performance Analysis of Orbital Angular Momentum-Index Modulation 6G Waveform Short Field Communication

Yudi Sutanto Sutanto, Teguh Yoga Putra — Fri, 03 May 2024 00:00:00 +0800

Currently, wireless communication is migrating from 5G to 6G. This is happening due to the new application of Sensory Transmission technology, Intelligent Transportation System (ITS), and Digital Twin. The problems that arise from the implementation of this migration are the band limits referred to in the regulations above, the reliable link range or the distance that communication is successful, and the increase in the number of users to be served. This study uses the performance results of Orbital Angular Momentum-Index Modulation (OAM-IM) compared to Orthogonal Frequency Division (OFDM) for short distance communication for each Bit Error Rate (BER) at the distances mentioned in the general description. The OAM-IM method can produce lower BER values than the OFDM method through descriptive statistical analysis, The simulation results are described in the form of tables and charts and compared to the lower BER of the two methods. The average BER of OFDM is 0.486818 while a lower BER is recorded in the OAM-IM method of 0.314013 for the proposed simulation.

Perancangan Aplikasi Monitoring Bimbingan Tugas Akhir dengan Menggunakan Metode Agile di Perguruan Tinggi

Hendri — Fri, 03 May 2024 00:00:00 +0800

Thesis advisory is an essential process in students' academic journey; however, issues often arise during its implementation, such as the forgery of the advisor's signature and the advisors being unaware of the progress of the thesis.This study aims to investigate the implementation of the Agile methodology in the context of information system development, with a specific focus on the final thesis advisory process within higher education institutions. The Agile methodology, with its iterative approach and active involvement of relevant stakeholders, can provide greater flexibility in dealing with changing requirements, which often arise in the final thesis advisory process. Furthermore, this methodology enables the creation of sustainable information systems and improved testing, which are essential elements in ensuring higher quality and user satisfaction. This research involves an analysis of the enhancement of student thesis monitoring in the higher education environment. The results of this study are expected to provide valuable insights for higher education institutions looking to improve their final thesis advisory processes by leveraging the Agile approach in information system development. Additionally, this research may contribute to a deeper understanding of the effectiveness of the Agile methodology in the higher education environment, aiming to improve efficiency, quality, and satisfaction among users, including program heads, faculty, and students in the final thesis advisory process.

Analisis Penerapan Metode User-Centered Design pada Augmented Reality (AR) dengan Marker Based Tracking

Zainil Abidin, Daniel Arsa, Yolla Noverina — Fri, 03 May 2024 00:00:00 +0800

This research investigates the use of Augmented Reality (AR) technology in the context of higher education faculty promotion. The main focus of this research is to design and test an AR application that uses a marker in the form of a QR-Code placed on the faculty study program brochure. This AR application aims to provide prospective students with an interactive experience in exploring the facilities, study programs and academic potential of the faculty. The location of the research was at the Faculty of Science and Technology, Jambi University. The method for designing faculty promotional tools in the form of AR uses the UCD (User-Centered Design) method. This research includes the design stage, AR application development, as well as functionality testing and application performance evaluation. Performance testing is carried out based on the distance between the user's device and the QR-Code marker. Performance testing aims to understand the extent to which an application can function in various usage situations. The results of this study provide in-depth insight into the potential of AR as a faculty promotion tool, considering the advantages and limitations of marker-based tracking methods. These findings strengthen understanding of how AR technology can add value to prospective student recruitment efforts and guide the development of more effective AR applications in the future

User Experience Game Arknights: Sebuah Penerapan Metode Cognitive Walkthrough

Andri Daviano, Reni Aryani, Daniel Arsa — Fri, 03 May 2024 00:00:00 +0800

Every product requires an optimal user experience to ensure user comfort and effective interaction with the product. This research uses the Cognitive Walkthrough method to evaluate the user experience in the Arknights game, a mobile game that won the "Best Innovative Game" award at the Google Play Best Of 2020 awards. The Cognitive Walkthrough method is a user experience evaluation method where respondents are asked to work on scenario-based tasks that have been prepared by researchers. This method will evaluate step by step in a product, to find problems that make users uncomfortable. This evaluation aims to identify potential issues that may disrupt the user experience, especially for new users. The respondents in this study were 5 people with the main criteria being a gamer but had never played the Arknights game. The evaluation results show that Arknights has a high level of comfort overall, with most problems being minor and not affecting the main functions of the game. The issues identified were mostly related to specific in-game tasks, such as upgrading operators and change assistants, as well as basic in-game features. However, these issues are minor and do not hinder the gaming experience significantly. This evaluation shows that Arknights is a game that is easy to play and enjoy, especially for new users.

Komparasi Metode Naive Bayes dan K-Nearest Neighbors Terhadap Analisis Sentimen Pengguna Aplikasi Zenius

Tegar Abdillah, Ulfa Khaira, Benedika Ferdian Hutabarat — Fri, 03 May 2024 00:00:00 +0800

The purpose of this research is to compare the performance of Naive Bayes and K-Nearest Neighbor (KNN) methods in analyzing user sentiment on the Zenius application. The evaluation is done by checking the precision, precision, recall, and F1-Score scores of both methods as well as visualizing the results of sentiment analysis with one of the methods used. The advantage of this research is a deeper understanding of how Naive Bayes and KNN techniques work in sentiment analysis in the context of the Zenius app. Furthermore, this research aims to evaluate the performance results of two techniques, Naive Bayes and KNN, in sentiment analysis. From the results of testing split data scenarios using Split Validation with training data and testing data 90:10. Naive Bayes accuracy reached 88.41%, while KNN reached 100%. In this study, KNN outperformed Naive Bayes in terms of precision, recall, and F1-Score values. The results of data visualization show that the direction of the sentiment generated tends to be positive. This study not only provides a deeper understanding of the performance of Naive Bayes and KNN techniques in sentiment analysis for the Zenius application, but also provides a comprehensive evaluation of their performance. This research is expected to serve as a guide for developing more effective sentiment analysis methods for similar applications in the future.

Analysis of Student Sentiment Towards The Digital Literacy Curriculum at University of Singaperbangsa Karawang Using Naïve Bayes

Ibtihal Qomariyyah Luthfiyyah, Betha Nurina Sari, Taufik Ridwan — Fri, 03 May 2024 00:00:00 +0800

Implementation of the Digital Literacy Curriculum at University of Singaperbangsa Karawang (Unsika) as a concrete step considering the importance of digital literacy. Curriculum evaluation is an important step in ensuring the effectiveness of learning. Currently there is no mechanism from Unsika to encourage students to provide feedback on curriculum implementation. One way is by sentiment analysis, which requires sentiment analysis using the Naïve Bayes algorithm which contributes to providing feedback on curriculum evaluation. This sentiment analysis process uses the CRISP-DM (Cross Industry Standard Process for Data Mining) methodology. In an effort to obtain student perceptions, a survey was conducted using a questionnaire. The minimum number of respondents determined using the Slovin formula is 388. In this study the amount of data used was 591. There is an imbalance in the data, to overcome this an oversampling technique can be used using ADASYN (Adaptive Synthetic Sampling Approach). The data has been cleaned to produce 347 positive sentiments and 176 negative sentiments. The results of this research show the best model and word frequency in the form of visualization of words that play an important role in each sentiment category for use in curriculum evaluation. Of the eight model scenarios tested, the model trained with the Naïve Bayes algorithm using a division of 90% training data and 10% testing data with the application of ADASYN became the best model with an accuracy of 89%, precision 100%, recall 85%, and f1-score 92%.

Oyster Fungus Plant Disease Detection Expert System Using Web-Based Certainty Factor Method

Rhido Rezwana, Dwinita Arwidiyarti, Hendri Ramdan — Fri, 03 May 2024 00:00:00 +0800

Oyster mushrooms are one of the agricultural commodities in Indonesia. Oyster mushrooms can be processed into various kinds of dishes and snacks so that the need for oyster mushrooms in society is increasing over time. Based on data from the Plantation Plantation Seed and Protection Center of West Nusa Tenggara Province, oyster mushroom production in West Nusa Tenggara Province in 2022 decreased by 28,291 kg when compared to 2021. Various disturbing factors such as pest and disease attacks, climate and errors in maintenance are the cause of decreased production. Farmers' limited knowledge in diagnosing diseases in oyster mushroom plants often results in mistakes that result in crop failure. The aim of this research is to produce an expert system that can diagnose diseases in oyster mushroom plants and provide solutions so that farmers can make prevention and treatment efforts quickly before the disease spreads to other oyster mushroom plants. This expert system was built using the Waterfall software development method. Functional testing used the Black Box Testing Method with 100% valid results, while accuracy testing was carried out using 20 cases which resulted in 19 valid cases (95% accuracy). This expert system uses the web-based Certain Factor Method so that it can be accessed by oyster mushroom farmers or anyone who needs it for free. It is hoped that this expert system can help farmers detect diseases in oyster mushroom plants and increase oyster mushroom production in the community.

Implementation of Mikrotik-API on Mikrotik OS Filter rule using PHP Native for UPT Lab Amikom University Yogyakarta

Muhammad Firdaus Ilhamy, Andika Agus Slameto — Fri, 03 May 2024 00:00:00 +0800

Mikrotik Routeros is a popular network operating System used by network administrators. Equipped with a Firewall feature, managing Filter rules in controlling network access is important. However, the WEB interface or CLI can be difficult and time-consuming. One management alternative is to use the Mikrotik API which allows access through integrated programs or applications. Winbox is a common GUI application for controlling network access, but it has some problems. Users may cause accidental errors, and this app is only available for Windows, not for Mac os or Linux. Other alternatives such as CLI and API can be accessed from various platforms. At Amikom University, Yogyakarta, problems arOSe at the UPT (Technical Implementation Unit) Lab because they were still using Winbox to manage network permissions, especially on Filter rules. Therefore, this research project aims to reduce user errors by using the Mikrotik API. The use of this API enables more efficient and effective management of Filter rules through programs or applications as needed, increasing overall network security.

Analisis Penerapan Metode User Centered Design dengan Pengujian Metode Cognitive Walkthrough

Haezrah Oktavini, Reni Aryani, Edi Saputra, Ulfa Khaira — Fri, 03 May 2024 00:00:00 +0800

The Siginjei Jambi Museum is one of 439 museums in Indonesia which stores and exhibits various collections of historical relics and civilizations from the past and is real evidence of history that has occurred so it is worthy of being used as a source of learning and tourist visits. The management of the Siginjei Jambi Museum is still a traditional museum, so the Siginjei Jambi Museum needs to innovate by implementing information technology in the form of an e-museum or website to increase the number of visitors and can be accessed quickly without space and time constraints. Interface design is an important thing that needs to be considered before creating a website so that the website created can meet user needs. The researcher created the interface design for the E-Museum Siginjei Jambi website using the user centered design method because with this method the interface design is designed based on user input. The results of testing the design that was created using the cognitive walkthrough method with a total of 5 respondents were learnability 97.7%, error 1.77%, and efficiency 94.3%.

Expert System for Diagnosing Human Eye Disease Using the Fuzzy Mamdani Method

Dwinita Arwidiyarti, Juhartini Juhartini, Surni Erniwati — Fri, 03 May 2024 00:00:00 +0800

The medical field has utilized technology in an effort to improve better services in diagnosing diseases, one of which is eye disease in humans. Because the eye is one of the five senses that is important to interact with the surrounding environment. The doctor's work is very busy and busy resulting in delays in serving the community. To overcome this, an expert system is needed to assist patients in diagnosing early eye disease, so that patients can find out the eye disease they are suffering from and its severity. This study discusses the creation of an expert system using the fuzzy mamdani concept to diagnose eye disease. The Fuzzy Mamdani method has been successfully implemented into an expert system for diagnosing eye diseases. This expert system uses the fuzzy mamdani method for diagnosing eye diseases which can provide fast diagnosis results along with the level of certainty for each disease. Expert systems can diagnose diseases based on the trust value of the disease using the Fuzzy Mamdani formula. From the results of the diagnosis calculations performed by the system, it can be seen that the accuracy of the system diagnosis with doctors reaches 93.3%