Cyber Forensics and Security

DEVELOPING THE TRIPLE HELIX MEASURE AND EXAMINING ROLE IN KNOWLEDGE TRANSFER AND INNOVATION SYSTEMS

Muhammad Sholeh — 2024-01-23

Advancing times and rapidly developing technology put pressure and responsibility on the management of organizations. Organizational ambidexterity is a concept for an organization that can balance profitability with innovation and development. This study examined the relationship between the triple helix and innovation systems mediated by knowledge transfer to give management an advantage in addressing this problem. Quantitative analysis methods using PLS-SEM (Partial Least Square-Structural Equation Modeling) were employed in this study. This study was conducted in Indonesia with 400 respondents participating in the data collection, 360 of which were declared valid after filtering. The results of this study demonstrate that the role of the triple helix in developing innovation systems is significant. The framework for innovation systems presented in this study may be helpful for future research in this field. This study can be further developed for future research, especially by adding new external variables that change over time and focusing more on a specific organization. At the very least, this study is relevant for researchers and practitioners to improve business quality using the concept of the triple helix, innovation systems mediated by knowledge transfer

Development of a Web-Based Automatic Sentiment Analysis Application using Support Vector Machine (SVM) Model

Anas Nasrulloh — 2024-01-31

This research aims to develop a web-based automatic sentiment analysis application using the Support Vector Machine (SVM) model. Through this application, users can easily analyze the sentiment of the text they input through a user-friendly interface. In the initial stage of the research, we conducted a review of various existing techniques for automatic sentiment analysis. From the review, we selected the SVM model as the main model in our application due to its effectiveness in sentiment classification. We used the Streamlit web framework to build a responsive and user-friendly user interface.

The methods we applied include data preprocessing and processing, feature extraction using TfidfVectorizer, and training the SVM model. We involved a labeled dataset to train the model and performed performance evaluation using separate test data. Our evaluation results showed that the implementation of the SVM model in our application provided excellent results in sentiment analysis with an accuracy rate of 94% using 830 data points. Our application interface is designed to be simple yet informative, allowing users to input text and quickly view sentiment analysis results.

In conclusion, we propose that the use of the SVM model in web-based automatic sentiment analysis applications can make a significant contribution to natural language processing. The application we have developed has the potential to be used in various fields such as social media monitoring, product review analysis, and understanding user opinions in general.

APPLICATION OF DESIGN THINKING METHOD FOR PROTOTYPE USER INTERFACE DESIGN AND USER EXPERIENCE TESTING OF DIGITAL VILLAGE WEBSITE

Muh. Hajar Akbar — 2024-01-23

In the ever-evolving digital era, the utilization of information and communication technology (ICT) has become an integral part of daily life, affecting various aspects of society, including rural areas. One indicator of the implementation of a digital village is the existence of a village website. This research explores the application of the Design Thinking method to design a prototype User Interface (UI) and test the User Experience (UX) of the Digital Village Website. This research aims to understand user needs and expectations, create creative solutions, and thoroughly test the user experience. The results showed that the UI/UX design of the Digital Village website using the Design thinking method was able to improve the quality of the user experience in using the Digital Village website. This is evidenced by the results of usability testing which shows an increase in user satisfaction with the Digital Village website. The UI/UX design of the Digital Village website is expected to be the basis for developing further recommendations on the development of other Digital Village websites.

CONFIRMATION MODEL USED FINTECH PAYMENT FOR CONTINUANCE INTENTIONS

Reza Nur Arifin — 2024-01-23

In this research, the aim was to explore the factors that impact users' decision to continue using FinTech
payment applications. To achieve this goal, an online questionnaire was given to 361 individuals who use
FinTech services during the pandemic. The study analyzed the data through the Expectation-Confirmation
Model, which was expanded to include perceived trust, social influence, and functional benefits. The results of
the study indicate that users' decision to continue using the application is influenced by their prior expectation
confirmation and the perceived usefulness of the application after use. Moreover, perceived trust and social
influence also play a positive role in users' decision to continue using the application. These factors can be
strengthened by providing personalized experiences and positive interactions. This research provides significant
insights for researchers and practitioners who are involved in the FinTech payment industry.

OPTIMIZATION OF PARAMETERS K IN THE K-NEAREST NEIGHBOUR ALGORITHM FOR CLASSIFICATION OF DIABETES DISEASE BASED ON PYTHON

Grasberg Nahumarury — 2024-01-31

Diabetes doesn't just cause premature death worldwide. This disease is also a major cause of blindness,
heart disease, and kidney failure. The International Diabetes Federation (IDF) organization estimates
that at least 463 million people aged 20-79 years in the world have diabetes in 2019, or the equivalent of
a prevalence rate of 9.3% of the total population at the same age. The research objective is to optimize
the k parameter in the k-NN algorithm for python-based diabetes classification. This research was
conducted using the experimental method. This experimental method was carried out by researchers by
changing the k parameter with a value of 3, 5, 7, 9, 11, 13, 15, 17, 19, 21, 23, 25, 27, 29, 31, 33, 35, 37,
39, 41, 43, 45, 47, and 49 and getting the research results for optimizing the value of k = 11 having the
highest accuracy of 0.9617.

WINNOWING ALGORITHM FOR MOBILE-BASED THESIS TITLE SIMILARITY DETECTION

Andra Ramadan Pratama — 2024-01-23

Determining a thesis title can be a difficult task for students due to concerns about the similarity of proposed titles and the possibility of plagiarism. Currently, the checking and management of thesis titles in the Informatics Engineering study program at the Institute Informatika dan Bisnis Darmajaya is still done conventionally. This study aims to build a system that can automatically check thesis titles to prevent plagiarism. Title checking is performed using the winnowing algorithm, which is an algorithm for comparing similarities between texts or documents with document fingerprinting techniques. By comparing two very different thesis titles using the winnowing algorithm, a similarity percentage of 6.08% is obtained. System testing is conducted using black box testing methods to test the system's user functions and interface. The result of the system can facilitate students in determining the similarity of titles they will propose early on, and the system can help the academic group supervisors to inventory the thesis titles submitted by students and build a new culture in managing thesis titles digitally.

Fuzzing Protocol Effectiveness in Data Communication Security on RabbitMQ

Ridwan Satrio Hadikusuma — 2024-01-31

The purpose of this research is to assess the efficacy of the fuzzing approach in assessing data transmission security on the RabbitMQ protocol. Middleware software called RabbitMQ is frequently used in data communications, especially in settings where message-based architectures are used. It is crucial to make sure that communication protocols like RabbitMQ are secured from attacks and security weaknesses that could be exploited by attackers in situations that demand high data security. In this work, the RabbitMQ protocol is automatically tested by inserting erroneous and unexpected information using a technique called fuzzing. We carried out a number of experiments with various input variations and examined the RabbitMQ system's reaction to erroneous input in order to comprehend the efficacy of this technique. Additionally, using legitimate and predictable inputs, we contrast the fuzzing findings with real-world situations. The results suggest that the fuzzing technique is effective in revealing security weaknesses in the RabbitMQ protocol. We discovered a number of previously unidentified security problems, such as buffer overflow vulnerabilities, denial-of-service attacks, and possible sensitive information leaks, through a variety of erroneous inputs. Additionally, a comparison with the typical scenario reveals that while the RabbitMQ protocol is fairly robust against valid input, processing invalid input still need refinement.