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Brilliance: Research of Artificial Intelligence
Published by Information Technology and Science
ISSN : -     EISSN : 28079035     DOI : https://doi.org/10.47709
Core Subject : Science, Education,
Decision Sciences, Operations Research & Management Mathematics Other
Brilliance: Research of Artificial Intelligence is The Scientific Journal. Brilliance is published twice in one year, namely in February, May and November. Brilliance aims to promote research in the field of Informatics Engineering which focuses on publishing quality papers about the latest information about Artificial Intelligence. Submitted papers will be reviewed by the Journal and Association technical committee. All articles submitted must be original reports, previously published research results, experimental or theoretical, and colleagues will review. Articles sent to the Brilliance may not be published elsewhere. The manuscript must follow the author guidelines provided by Brilliance and must be reviewed and edited. Brilliance is published by Information Technology and Science (ITScience), a Research Institute in Medan, North Sumatra, Indonesia.
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 544 Documents
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Application of the C 4.5 Algorithm to Classify Customer Characteristics at PT. Bayer Indonesia Siswandi, Arif; Anwar, M. Syaibani; Susilo, Arif; Hasibuan, Sultan
Brilliance: Research of Artificial Intelligence Vol. 4 No. 1 (2024): Brilliance: Research of Artificial Intelligence, Article Research May 2024
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v4i1.4174

Abstract

PT. Bayer Indonesia is a company engaged in drug production. In running its business, companies need to know customer characteristics in determining what actions to take next. This research aims to apply the C 4.5 algorithm in classifying customer characteristics at PT. Bayer Indonesia. The C 4.5 algorithm is a decision tree algorithm that is often used in data mining for classification purposes. This research was conducted to make it easier to find out customer characteristics. Starting with collecting data, then selecting the attributes that will be used. Then the data is separated using split data, the initial comparison used is 60% train data and 40% test data. Then training data is carried out using the C4.5 algorithm. Next, the classification results were evaluated using the confusion matrix method. The data used was 200 data with 9 attributes, obtained an accuracy of 86.25%, precision of 86.25% and recall of 54.55%. Then change the data split parameters to 70% : 30%, 80% : 20% and 90% : 10%. The best accuracy is 100%. The research results show that the C 4.5 algorithm has good performance in classifying the characteristics of PT customers. Bayer Indonesia. The resulting model can be used by companies for more effective marketing strategies and personalized customer service.
Association Rule to Increase Sales Using the Apriori Algorithm Method Ermanto, Ermanto; Halim Anshor, Abdul; Arwan Sulaeman, Asep; Winarni, Sri
Brilliance: Research of Artificial Intelligence Vol. 4 No. 1 (2024): Brilliance: Research of Artificial Intelligence, Article Research May 2024
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v4i1.4185

Abstract

The Apriori algorithm is a data mining technique used to find relationship patterns between items in a transaction dataset. In this context, the Apriori algorithm will be used to identify products that are often purchased simultaneously by customers. By understanding these purchasing patterns, companies can design more effective marketing strategies, such as strategic product placement, bundling package offers, and special promotions. This research involves several stages, starting from collecting sales transaction data, data preprocessing, applying the Apriori algorithm, to interpreting the results. The transaction data used is taken from the sales database of a retail store during a certain period. After the data is processed, the Apriori algorithm is applied to identify frequent itemsets and form association rules. The results of this research show that there are several significant purchasing patterns, such as a combination of product A and product B which are often purchased together. By applying data mining using the a priori algorithm method, you can find out which products sell the most. From the results of manual calculations it was found that consumers who bought RB 1060 would buy RB 1099 with 81% confidence, whereas using WEKA it was found that consumers who bought RB 1060 would buy RB 1099 with a confidence value of 82%.
Website Development as a Media for Disseminating Information in RT. 39 Jelutung Village, Jambi City Ikhsan, Muhammad; Darmuji, Darmuji; Adhiatma, Novri; Helmina, Helmina
Brilliance: Research of Artificial Intelligence Vol. 4 No. 1 (2024): Brilliance: Research of Artificial Intelligence, Article Research May 2024
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v4i1.4198

Abstract

RT 39 Jelutung Village, Jambi City is currently facing challenges in terms of disseminating information to its citizens. Conventional methods that have been used, such as announcements on information boards, regular meetings, and distributing leaflets, are often ineffective in reaching all residents. This research seeks to create a website for sharing information for disseminating information in RT. 39, Jelutung Village, Jambi City, using the Waterfall method and UML modeling to describe the system flow. This website is designed to facilitate effective communication between RT administrators and residents and provide fast and accurate access to information regarding activities, announcements and public services. The Waterfall methodology includes the phases of needs analysis, design, implementation, testing and maintenance. UML modeling is used to visually describe the structure and flow of a system, including use case diagrams, activity diagrams, and class diagrams. The finding is a website with main features such as Information Portal, Website Dashboard, Manage Mail. Evaluation was carried out through a survey of RT residents. 39 to assess the effectiveness and satisfaction with the use of this website. The evaluation results show that this website has succeeded in increasing information accessibility and citizen participation in RT activities. 39. Thus, it is hoped that the development of this website can become a model that can be applied in other RTs To enhance the caliber of communication and informational offerings.
Implementation And Simulation Of Dynamic Arp Inspection In Cisco Packet Tracer For Network Security Putra, Fauzan Prasetyo Eka; Ubaidi, Ubaidi; Tamam, Alief Badrit; Efendi, Reynal Widya
Brilliance: Research of Artificial Intelligence Vol. 4 No. 1 (2024): Brilliance: Research of Artificial Intelligence, Article Research May 2024
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v4i1.4199

Abstract

Dynamic ARP Inspection (DAI) is a security feature that helps prevent Address Resolution Protocol (ARP) spoofing attacks, which can compromise the integrity and confidentiality of data in a network. This paper presents the implementation and simulation of DAI using Cisco Packet Tracer, a network simulation tool. The goal is to show how DAI can be configured and used to improve network security by verifying ARP packets in a switched network. The implementation involved setting up a network topology with switches and end devices, configuring DHCP snooping, and enabling DAI on the switches. Simulations tested various scenarios, including normal operation, ARP spoofing attacks, and the network response to these attacks with DAI enabled. The results show that DAI effectively mitigates ARP spoofing attacks, ensuring only legitimate ARP packets are forwarded, thus protecting the network from potential security breaches. The study concludes that implementing DAI is an important step in securing networks, especially in environments with sensitive data and high security needs. This paper serves as a practical guide for network administrators looking to improve their network security posture using Cisco Packet Tracer.
Systematic Literature Review: Security Gap Detection On Websites Using Owasp Zap Putra, Fauzan Prasetyo Eka; Ubaidi, Ubaidi; Hamzah, Amir; Pramadi, Walid Agel; Nuraini, Alief
Brilliance: Research of Artificial Intelligence Vol. 4 No. 1 (2024): Brilliance: Research of Artificial Intelligence, Article Research May 2024
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v4i1.4227

Abstract

This research highlights the detection of security vulnerabilities on websites using OWASP ZAP, a highly regarded open-source web security testing tool. Through a comprehensive literature review approach and systematic research methodology, this research emphasizes the urgency of addressing the ever-evolving security threats in web systems. Web security is a crucial aspect of information technology as more and more sensitive data is transmitted through web applications. OWASP ZAP, recognized for its reliability in identifying various security holes, was used to evaluate its effectiveness and efficiency in detecting vulnerabilities in web applications. This tool assists developers and security researchers in finding and fixing weaknesses that could be exploited by attackers. The results of the study show that OWASP ZAP is not only effective in identifying vulnerabilities such as SQL Injection, XSS (Cross-Site Scripting), and misconfiguration but also provides practical solutions to strengthen overall web security. Additionally, this research identifies several challenges faced when using OWASP ZAP and offers recommendations to address these issues. This study makes a significant contribution towards a better understanding of web security and offers recommendations for the implementation of better security testing tools in web development environments. Consequently, this research encourages the adoption of more proactive and systematic security practices in web application development.
Application of Internet of Things Technology in Monitoring Water Quality in Fishponds Putra , Fauzan Prasetyo Eka; Ubaidi, Ubaidi; Saputra, Rama Nurja; Haris, Farras Maulana; Barokah, Selviana Nur Rizqi
Brilliance: Research of Artificial Intelligence Vol. 4 No. 1 (2024): Brilliance: Research of Artificial Intelligence, Article Research May 2024
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v4i1.4231

Abstract

Monitoring water quality in fish ponds is essential to maintain fish health and productivity. In recent years, Internet of Things (IoT) technology has emerged as an effective solution to efficiently monitor and manage water quality. This article describes the application of IoT technology in monitoring the water quality of aquaculture ponds with the aim of improving fish productivity and welfare. Data on water quality parameters such as temperature, dissolved oxygen, pH, ammonia levels, and turbidity can be monitored in real time through a network of connected sensors. The main advantage of using IoT for fish pond water quality monitoring is that it can provide accurate and fast information on water conditions. This allows fish farmers to proactively take appropriate actions to maintain an optimal water environment for fish growth. In addition, integration with data management and remote monitoring systems allows fish pond owners to continuously monitor water conditions, even in remote locations. This helps reduce the risk of environmental damage and fish loss due to inappropriate water quality conditions. Therefore, the use of IoT technology for water quality monitoring in fish ponds not only increases productivity but also ensures the well-being of fish and reduces negative impacts on the environment.
The Sentiment Analysis of Bekasi Floods Using SVM and Naive Bayes with Advanced Feature Selection Amali, Amali; Maulana, Donny; Widodo, Edy; Firmansyah, Andri; Danny, Muhtajuddin
Brilliance: Research of Artificial Intelligence Vol. 4 No. 1 (2024): Brilliance: Research of Artificial Intelligence, Article Research May 2024
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v4i1.4268

Abstract

Flood management in Bekasi City poses significant challenges, necessitating strategies grounded in an understanding of community sentiment. This study aims to develop and optimize sentiment analysis of social media data related to flooding using Support Vector Machine (SVM) and advanced feature selection techniques. The primary goal is to enhance the accuracy of classifying public sentiment toward flood management efforts in Bekasi City. Data is collected from various social media platforms, preprocessed, and analyzed using SVM with feature selection techniques like Information Gain and Analysis of Variance (ANOVA). (Thoriq et al., 2023) Our findings indicate that using SVM with advanced feature selection significantly improves sentiment classification accuracy compared to standard methods. These results offer insights into public perceptions, helping policymakers improve management strategies and communication for flood events. This method assists in understanding community responses and pinpointing critical areas needing attention. Moreover, this study contributes to disaster management in urban flood-prone areas by presenting a methodological approach applicable to other disaster contexts. Integrating social media sentiment analysis with advanced machine learning techniques offers a robust framework for real-time public sentiment assessment, enhancing disaster response strategies. Furthermore, these techniques help create a more resilient urban environment by improving the efficiency and effectiveness of flood management practices. This comprehensive tool is essential for better preparedness, response, and recovery from flood events, ultimately enhancing community resilience and safety in Bekasi City. This research is part of machine learning in disaster management and a valuable asset for city planners and disaster professionals around the world.
Service Quality Analysis of RFID-Based Smart Door Lock in Front One Azana Style Hotel Area Putra, Fauzan Prasetyo Eka; Ramadhani, Nilam; Fauzan, Fauzan; Mursidi, Moh.
Brilliance: Research of Artificial Intelligence Vol. 4 No. 1 (2024): Brilliance: Research of Artificial Intelligence, Article Research May 2024
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v4i1.4292

Abstract

This research evaluates the service quality of an RFID-based smart door lock system in the Front One area of Azana Style Hotel Pamekasan. Employing qualitative analysis techniques, the study assesses the system's reliability, security, convenience, and responsiveness based on user experience and behavioral data. The primary goal is to understand how effectively the smart lock system enhances hotel services and operational efficiency. The findings aim to offer valuable insights to hotel management and the broader hospitality industry regarding the impact of smart technology on guest experience and hotel operations, thus fostering innovation and promoting environmental sustainability. By integrating RFID-based smart door locks with the Internet of Things (IoT), the system enables real-time access control, manages meeting room schedules, facilitates remote security monitoring, and oversees employee access management. This integration not only boosts service quality and operational efficiency but also creates a more connected and intelligent hotel environment. Consequently, the study highlights the potential of smart technology to transform hotel operations, improve guest satisfaction, and contribute to a sustainable future for the hospitality industry. Additionally, the research underscores the importance of continuous technological advancements in maintaining competitive advantage in the rapidly evolving hospitality sector, ensuring that hotels can meet the ever-changing needs and expectations of their guests.
Case Study of Computer Network Development for the Internet Of Things (IoT) Industry in an Urban Environment Rachman, Anang Fakchtur; Putra, Fauzan Prasetyo Eka; Syirofi, Syirofi; Wahid, Durrahman
Brilliance: Research of Artificial Intelligence Vol. 4 No. 1 (2024): Brilliance: Research of Artificial Intelligence, Article Research May 2024
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v4i1.4302

Abstract

This research presents a case study of computer network development to support the Internet of Things (IoT) industry in an urban environment. The rapid growth of the IoT industry has created the need for a network infrastructure that can support the connectivity of various smart devices widely and reliably. This research focuses on urban environments that have unique complexities such as high population density, intensive movement, and diverse infrastructure needs. The research methodology involves a detailed analysis of the implementation of computer networks in the context of the IoT industry in urban environments. Data was collected through field observations, interviews with experts, and analysis of relevant project documents. The analysis results show that the development of computer networks in urban environments to support industrial IoT requires scalable network design, efficient bandwidth management, tight security, and adaptation to existing infrastructure. This case study describes various strategies and technologies used in the development of computer networks, including the implementation of 5G-based wireless networks and the monitoring of urban environments using smart sensors. These results highlight the importance of a holistic and sustainable approach when developing computer networks for the IoT industry in urban environments. Ensuring your infrastructure can meet future needs requires collaboration between stakeholders, investment in the right technology, and careful planning. This study makes an important contribution to the optimisation of computer networks that support the growth of the IoT ecosystem in urban environments.
Improving Network Service Quality in parts of Sampang City: QoS Evaluation and User Perception of QoE Putra, Fauzan Prasetyo Eka; Ubaidi, Ubaidi; Aziz, Mohammad; Irfan, Moh.; Alim, Royfal
Brilliance: Research of Artificial Intelligence Vol. 4 No. 1 (2024): Brilliance: Research of Artificial Intelligence, Article Research May 2024
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v4i1.4311

Abstract

In an era of rapid urbanization, the quality of network services in urban environments is becoming increasingly important. This article explores efforts to improve network service quality in several sampang cities through an evaluation of Quality of Service (QoS) and user perceptions of Quality of Experience (QoE). The research is based on a survey conducted at various locations in sampang city to collect data on the reliability, speed, and availability of network services. The survey involved a diverse sample of users, covering a wide range of ages, professions, and levels of technology usage. In addition, we also analyzed users' perceptions of service quality based on their experiences of using the network in an urban environment. The results highlighted several key challenges in improving QoS, such as user density, signal interference, and network infrastructure limitations. However, we also found that strategies such as the use of advanced network technologies, such as 5G and beamforming, as well as traffic prioritization based on application type, can help to significantly improve QoS. In addition, we found a strong positive correlation between improved QoS and improved QoE, suggesting that improved quality of service has a direct impact on improving user experience. These findings provide valuable insights for network operators and policy makers in their efforts to improve network services in dense urban environments. The research also recommends further investment in network technologies and the development of policies that support more effective management of network traffic to ensure optimal quality of service.

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