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All Journal Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi)
Lim Jong Su
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Computer Science & IT

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Implementasi Artificial Intelligence dalam Meningkatkan Cyber Security: Analisis ancaman dan Pencegahan Lim Jong Su; Binastya Anggara Sekti
Prosiding SISFOTEK Vol 8 No 1 (2024): SISFOTEK VIII 2024
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

In today's digital age, cyber threats are becoming more complex and sophisticated.The aim of this study is to analyze the role of artificial intelligence (AI) in improving cybersecurity through threat detection and prevention. By integrating AI techniques such as machine learning and deep learning, cybersecurity systems can detect suspicious behavior patterns and identify threats in real-time.A comprehensive literature review was conducted to explore different AI approaches applied in this field, including anomaly detection analytics, threat intelligence, and automated response. The use of artificial intelligence can significantly improve the accuracy of threat detection and cyber incident response. Moreover, case studies of several organizations that have used AI for cybersecurity have shown increased effectiveness and efficiency in dealing with cyberattacks. However, there are still challenges to overcome, such as: B. Limited training data, interpretability of AI models, and the need for qualified experts. Although AI has great potential to improve cybersecurity, collaboration between technology and human expertise remains crucial to address growing threats.Thus, not only is cybersecurity improving, but there is also an increasing need to develop artificial intelligence (AI) systems that take cybersecurity threats into account in order to attack the security of information systems.
Implementasi Sistem Informasi Manajemen Inventaris Berbasis ERP Odoo 17 pada PT XYZ Lim Jong Su
Prosiding SISFOTEK Vol 9 No 1 (2025): SISFOTEK IX 2025
Publisher : Ikatan Ahli Informatika Indonesia

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PT XYZ is an agribusiness company engaged in the provision of cassava products and fertilizers, with a commitment to supporting sustainable agricultural practices. The main problems faced include stock recording, fertilizer procurement, and coordination of cultivation activities, which are still carried out manually using notebooks and basic spreadsheets. This condition often leads to data duplication, delays in stock updates, and discrepancies between physical stock data and administrative records. This study aims to design and develop an inventory management information system based on ERP Odoo 17 using the Prototyping Model approach. The system is designed to integrate three main modules—Inventory, Purchase, and Agriculture Management—which are interconnected to support centralized, automated, and real-time business processes. The methods used include data collection techniques such as in-depth interviews with the Warehouse Head, Procurement Staff, and Operations Manager, direct observation of stock management processes, and literature review on ERP implementation in the agribusiness sector. The resulting system prototype is capable of recording goods in and out, performing stock adjustments, supporting purchase requests through to goods receipt from vendors, and digitally recording cassava cultivation activities. With inter-module relationships, every data input in one module is automatically updated in the other modules, thereby minimizing the risk of data redundancy.
Co-Authors Benny Muyarman Binastya Anggara Sekti Julius Jery Nolasco Riya Widayanti Setianingsih Syifa Maulida Akmalia