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Karona Cahya Susena
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INDONESIA
Jurnal Komputer Indonesia
Published by Universitas Dehasen Bengkulu
ISSN : -     EISSN : 29623626     DOI : -
Core Subject : Science,
Computer Science & IT
Jurnal Komputer Indonesia (JKI) diterbitkan oleh Universitas dehasen Bengkulu. JKI memuat naskah hasil-hasil penelitian di bidang Ilmu Komputer. JKI berkomitmen untuk memuat artikel berbahasa Indonesia yang berkualitas dan dapat menjadi rujukan utama para peneliti dalam bidang Ilmu Komputer. Ruang lingkup JKI adalah sebagai berikut: Domain Specific Frameworks and Applications IT Management dan IT Governance e-Government e-Healthcare, e-Learning, e-Manufacturing, e-Commerce ERP dan Supply Chain Management Business Process Management Smart Systems Smart City Smart Cloud Technology Smart Appliances & Wearable Computing Devices Robotic Systems Smart Sensor Networks Information Infrastructure for Smart Living Spaces Intelligent Transportation Systems Models, Methods and Techniques Conceptual Modeling, Languages and design Software Engineering Information-centric Networking Human Computer Interaction Media, Game and Mobile Technologies Data Mining Information Retrievel Information Security Image Processing and Pattern Recognition Remote Sensing Natural Language Processing
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 7 Documents
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Search results for , issue "Vol. 2 No. 1 (2023): Juni" : 7 Documents clear
Design And Implementation Of Adversarial Neural Network For Voice Data Processing Tarigan, Heskyel Pranata
Jurnal Komputer Indonesia Vol. 2 No. 1 (2023): Juni
Publisher : LPPJPHKI Universitas Dehasen Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jki.v2i1.562

Abstract

In today's digital age, voice data processing has become an important area in information and communication technology. Adversarial Neural Networks (GANs) are one of the recent methods that show great potential in improving the quality and efficiency of voice data processing. This article discusses the design and implementation of GANs for speech data processing, focusing on model architecture, optimization techniques, and performance evaluation. The results show that GANs can produce better speech representations and improve processing quality compared to traditional methods. It also explores the challenges faced in the implementation of GANs and provides recommendations for future development.
Security Analysis Of AI-Based Mobile Application For Fraud Valentino, Muhammad Ryan
Jurnal Komputer Indonesia Vol. 2 No. 1 (2023): Juni
Publisher : LPPJPHKI Universitas Dehasen Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jki.v2i1.563

Abstract

Fraud in digital transactions is increasing along with the development of technology. To address this issue, artificial intelligence (AI)-based mobile applications have been used in detecting and preventing fraudulent acts. This research aims to analyze the security of AI-based mobile applications in the context of fraud detection, as well as identify the weaknesses and challenges faced. The results of the analysis show that while AI-based applications have great potential in detecting fraud, there are several security risks that must be addressed, including data privacy issues and attacks on AI models. This study also provides recommendations to improve the security and effectiveness of applications in detecting fraud.
Search Algorithm Optimization In E-Commerce Applications For Better User Experience Simeramisna, Brenda Sita
Jurnal Komputer Indonesia Vol. 2 No. 1 (2023): Juni
Publisher : LPPJPHKI Universitas Dehasen Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jki.v2i1.564

Abstract

In the competitive world of e-commerce, user experience is a key factor in attracting and retaining customers. One of the important elements in user experience is the efficiency and accuracy of the search feature. This article discusses the optimization of search algorithms in e-commerce applications to improve user experience. This research explores various optimization techniques, such as search personalization, the use of machine learning algorithms, and user behavior analysis. Through experiments and data analysis, it is found that optimized search algorithms can significantly improve user satisfaction, speed up the search process, and ultimately, increase sales conversion. The results of this study show that integrating advanced technologies in search algorithms is an effective strategy in developing competitive e-commerce applications.
Implementation Of Biometric-Based Security System On Mobile Banking Application Saputri, Vettyca Diana
Jurnal Komputer Indonesia Vol. 2 No. 1 (2023): Juni
Publisher : LPPJPHKI Universitas Dehasen Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jki.v2i1.565

Abstract

Security is a crucial aspect in mobile banking applications, given the increasing cyber threats that can harm both users and financial institutions. The implementation of biometric-based security systems, such as fingerprint scanning and facial recognition, offers a more secure solution than traditional authentication methods. This article discusses the implementation of biometric security systems in mobile banking applications, evaluating its effectiveness and challenges in its integration. Using literature review and system prototyping methods, this research shows that biometrics can increase the level of security and convenience for users, but requires attention to privacy issues and technology compatibility.
Neural Network Optimization Optimization For Medical Image Processing Fatimah, Siti
Jurnal Komputer Indonesia Vol. 2 No. 1 (2023): Juni
Publisher : LPPJPHKI Universitas Dehasen Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jki.v2i1.566

Abstract

Medical image processing is a crucial field in healthcare, especially in supporting diagnosis and clinical decision-making. Artificial Neural Networks (ANNs) have become an effective tool in medical image processing, but challenges in ANN optimization still need to be addressed to achieve higher accuracy and better efficiency. This article examines JST optimization methods applied to medical image processing. Various techniques such as network architecture adjustment, regulation, and the use of advanced optimization algorithms are explored in this study. The results show that JST optimization can significantly improve the performance in pattern recognition and classification of medical images.
Utilization Of Artificial Intelligence In Image-Based Medical Diagnosis Febriani, Rizki Annisa
Jurnal Komputer Indonesia Vol. 2 No. 1 (2023): Juni
Publisher : LPPJPHKI Universitas Dehasen Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jki.v2i1.567

Abstract

Artificial Intelligence (AI) has become one of the most revolutionary technologies in the medical field, especially in image-based diagnostics. This research aims to explore the utilization of AI, particularly through deep learning and Convolutional Neural Networks (CNN), in improving the accuracy and efficiency of medical diagnosis systems. This research uses a literature study approach and prototype implementation to analyze how AI can support doctors in making faster and more informed clinical decisions. The results show that AI is able to improve the accuracy of diagnoses as well as reduce human errors in medical image analysis.
Cyber Security In 2023: The Latest Challenges And Solutions Wiratama, Ahmad Doni
Jurnal Komputer Indonesia Vol. 2 No. 1 (2023): Juni
Publisher : LPPJPHKI Universitas Dehasen Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jki.v2i1.569

Abstract

Cybersecurity has become a crucial issue in the digital age, especially in 2023 where technology continues to evolve rapidly. This article discusses the challenges faced in maintaining cybersecurity, such as the rise of increasingly sophisticated cyberattacks, and the latest solutions offered to deal with them. The research was conducted through literature analysis as well as relevant case studies. The results show that new approaches such as Zero Trust, artificial intelligence in threat detection, and collaboration between entities are key to strengthening cybersecurity in 2023.

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