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Journal of Security, Computer, Information, Embedded, Network and Intelligence System
Published by PT. Lontara Digitech Indonesia
ISSN : 30248701     EISSN : 30248329     DOI : https://doi.org/10.61220/scientist
Core Subject : Science, Engineering,
Computer Science & IT Engineering
Articles submitted in SCIENTIST Scientific Journal will be examined by the editorial board. If the article matches the scope and style of writing an SCIENTIST Scientific Journal, the editorial board will assign the article to the reviewer. Reviewers name cannot be seen by the author. The author only sees the review results from the reviewer, so the author must revise the reviewer request. Each article will be reviewed by two reviewers. If one of the reviewers refuses, the decision will be submitted to the editor. If all reviewers receive the article will be published. Articles that do not make revisions will not be published in the SCIENTIST Scientific Journal. These fields include: Intelligence System Artificial Intelligence Machine Learning Data Science Computer Vision Information System Decision Support System Expert System Automation System Data Mining Embedded Sytem Internet of Things Robotic Wearable Technology Wireless Sensor Networks Network and Security Network Security Cryptography Cloud Computing Virtualization
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 5 Documents
 1 
Search results for , issue "Vol. 3, No. 1 (June 2025)" : 5 Documents clear
A Computational Enhancement Of Base64 Algorithm Using Residue Number System Algorithms Logunleko, Kolawole Bariu; Logunleko, Abolore Muhamin; Wuraola, Asaju-Gbolagade Ayisat; Babatunde, Akinbowale Nathaniel; Gbolagade, Kazeem Alagbe
Journal of Security, Computer, Information, Embedded, Network, and Intelligence System Vol. 3, No. 1 (June 2025)
Publisher : PT. Lontara Digitech Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61220/scientist.v3i1.20251

Abstract

A significant part of information security has been played by cryptography techniques. Today's daily existence depends heavily on the advancement of data, information, and communication technologies. Consequently, there is a huge increase in the need for data and information. In communicating data over a public network, data security is a necessity that must be carefully taken into consideration. Thus, Base64 algorithm has been used in numerous security applications for ensuring data confidentiality, integrity and authentication. However, research shows that there is security vulnerabilities in most widely used Base64 algorithm due to the absence of key mechanism. To address this concern, this research employs residue number system algorithms for the enhancement of base64 algorithm because of its cryptographic features whereby strengthen the transformation of the existing base64 algorithm to produce a novel symmetric-based cryptographic algorithm. The developed algorithm generates a symmetric key by shuffling the original key with the textual data, making the transformation of each character of the data better each time it is shuffled. Therefore, the research bridges the security gap in Base64 cryptographic algorithm by factoring key mechanism of RNS based algorithm into the newly developed algorithm. In addition, the developed symmetric-based cryptographic algorithm is more robust than the existing Base64 cryptographic algorithm because of the planned pattern and confusion produced during the methodology procedure thereby safeguards the data more effectively as shown in the cipher text generated.
Larimele Burger: Aplikasi Mobile Pemesanan Makanan Cepat Saji Berbasis Android untuk Meningkatkan Efisiensi Pelayanan Restoran Nugraha, Windu Yoga; Pratama, Muhammad Rifky Anugrah; Aprian, Wandy; Payangan, Juniati Tiku
Journal of Security, Computer, Information, Embedded, Network, and Intelligence System Vol. 3, No. 1 (June 2025)
Publisher : PT. Lontara Digitech Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61220/scientist.v3i1.20255

Abstract

The evolution of modern lifestyles demands a fast, reliable, and seamless fast-food ordering process. Larimele Burger is an Android application we developed to facilitate efficient fast-food ordering. Its key features include instant registration and login, a persistent shopping cart, and product recommendations by the admin (administrator rating). Evaluation was conducted through a Black-Box Testing, confirming that all functions operate according to specifications. The application offers a practical solution for ordering burgers at the restaurant.
Moodiary: Aplikasi Pencatat Suasana Hati Ananta, Anggi Diva; Nur, Muhammad Faturrahman; Saputra S., Syawal
Journal of Security, Computer, Information, Embedded, Network, and Intelligence System Vol. 3, No. 1 (June 2025)
Publisher : PT. Lontara Digitech Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61220/scientist.v3i1.20254

Abstract

Moodiary is an Android application developed to help users track their moods and daily activities, aiming to enhance self-awareness and emotional reflection. The app integrates Firebase Authentication for secure login and Firebase Realtime Database for real-time data storage. Featuring a minimalist and user-friendly interface, users can log their daily moods, write short personal narratives, and monitor emotional trends through data visualizations. Moodiary was developed using the Agile methodology, enabling iterative development based on user needs. Key features include icon-based mood tracking, mood history charts, daily reminders, and profile customization. Functional and non-functional testing results show excellent performance in terms of availability, reliability, security, and user experience. Thus, Moodiary serves as an effective digital solution to support mental well-being and self-reflection, particularly for mobile users seeking fast, secure, and personalized emotional tracking tools.
Pengembangan Fitur Absensi Pengenalan Wajah Menggunakan Model Facenet pada Aplikasi Buku Tamu Desa Ilham, Muhammad; Mappeasse, Muhammad Yusuf; Patta, Abd Rahman
Journal of Security, Computer, Information, Embedded, Network, and Intelligence System Vol. 3, No. 1 (June 2025)
Publisher : PT. Lontara Digitech Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61220/scientist.v3i1.20252

Abstract

The FaceNet model is one of the deep learning-based face recognition methods capable of transforming facial images into feature vectors (embedding) that represent the unique identity of each individual. In previous studies, this model is often combined with classification methods such as Support Vector Machine (SVM) or K-Nearest Neighbor (K-NN). Although accurate, these approaches require high computation and complex inference processes, making them less suitable for applications that require fast response and efficiency, such as real-time attendance systems. This research proposes an alternative approach using cosine similarity to compare similarity between face vectors. Cosine similarity measures the similarity of two vectors based on the angle between them, with values ranging from 0 (not similar) to 1 (identical). The system was developed by combining FaceNet and cosine similarity models, without any additional classification. Test results showed that faces registered in the system produced cosine similarity values between 0.83 and 0.96 (closer to 1 indicates a high match), with an average of 0.90, while unregistered faces had values between 0.42 and 0.67, with an average of 0.53. By setting the threshold at 0.7, the system successfully differentiated between recognized and unrecognized faces with 100% accuracy on 30 respondents. This approach significantly reduces the computational burden, enables implementation on devices with limited specifications, and provides a practical and accurate solution for face recognition-based digital attendance systems.
Digital Transformation of Refillable Water Services Using the Easy Galon Android-Based System Rahmah, Ummiati; Mustapa, Mahmud; Budiarti, Nur Azizah Eka
Journal of Security, Computer, Information, Embedded, Network, and Intelligence System Vol. 3, No. 1 (June 2025)
Publisher : PT. Lontara Digitech Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61220/scientist.v3i1.20253

Abstract

The advancement of technology in this period has been exceedingly swift.  The plethora of emerging innovations compels individuals to remain current.  The selling of gallons constitutes a significant and prevalent industry, prompting numerous gallon enterprises to transition to an online sales model via mobile applications.  Consequently, the researchers choose to develop an innovative and user-centric Gallon Refill Water Sales Application.  This article elucidates how the Gallon Refill Water Sales Application has enhanced efficiency and ease in the purchasing process.  This program enables consumers to swiftly and effortlessly order gallons via their mobile devices.  Users can see the inventory of available products, preferred brands, and execute payments using the COD (Cash On Delivery) method

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