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Blok E No 16 Bagu, Kecamatan Pringgarata, Kabupaten Lombok Tengah, Nusa Tenggara Barat Kodepos: 83562
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Breakthroughs in Informatics, Networking, Algorithms, Research, and Yield (BINARY)
Published by Pengelola Jurnal Lombok Scholar
ISSN : -     EISSN : 31095003     DOI : -
Core Subject :
Breakthroughs in Informatics, Networking, Algorithms, Research, and Yield (BINARY) is a peer-reviewed academic journal committed to the dissemination of high-quality original research articles and comprehensive review papers in the domains of computer science and informatics. The journal serves as a prominent platform for the publication of pioneering breakthroughs in informatics, network technologies, algorithmic design, and applied research that collectively contribute to advancing both theoretical foundations and practical applications in the field of computer science. By fostering scholarly exchange and interdisciplinary collaboration, BINARY aims to shape the future of computing through rigorous research and innovation. Focus and Scope Breakthroughs in Informatics, Networking, Algorithms, Research, and Yield (BINARY) BINARY aims to foster interdisciplinary collaboration by welcoming contributions that bridge theoretical foundations and practical applications. It covers a broad spectrum of topics including, but not limited to: Computer Networks and Communication Systems Algorithms and Data Structures Artificial Intelligence and Machine Learning Cybersecurity and Information Assurance Distributed and Cloud Computing Software Engineering and Development Data Mining and Big Data Analytics Human-Computer Interaction Internet of Things (IoT) Computational Theory and Formal Methods Bioinformatics and Computational Biology Embedded Systems and Real-Time Computing
Arjuna Subject : -
Articles 5 Documents
 1 
Search results for , issue "vol. 2 no. 2 (2026): intelligent computing, computer vision, and secure digital transformation" : 5 Documents clear
Best Cafe Assessment Information System Using the ARAS (Additive Ratio Assessment) Method in Soppeng Regency Andi Muhamad Sabri; Sri Wulandari; Hendrawansyah; Amriadi
Breakthroughs In Informatics, Networking, Algorithms, Research, And Yield (BINARY) Vol. 2 No. 2 (2026): Intelligent Computing, Computer Vision, and Secure Digital Transformation
Publisher : Breakthroughs In Informatics, Networking, Algorithms, Research, And Yield (BINARY)

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Abstract

The development of cafe businesses in Soppeng Regency has increased rapidly, but it has not been supported by an objective evaluation system in determining the best quality cafe. So far, cafe assessments are still subjective and unstructured, oftencausing dissatisfaction from consumers. This study aims to build the best cafe assessment information system using the ARAS (Additive Ratio Assessment) method that can assess cafe quality objectively and measurably based on the criteria of taste, price, comfort, and service. The ARAS method is used because it is able to manage various types of criteria both benefit and cost, and produce a final ranking of each alternative based on its contribution to the ideal solution. The system was developed using the Waterfall model and tested using the Blackbox method. Data collection techniques included observation, interviews, and literature studies. The results show that the system successfully displays the complete assessment process, from value input, normalization, contribution calculation, to ranking results and printed reports. The best cafe assessment information system built us-ing the ARAS method has proven effective in supporting a more accurate and transparent decision-making process.
EVALUASI KEPUASAN PENGGUNA E-LEARNING TOFAS MENGGUNAKAN METODE EUCS PADA SISWA KELAS IX SMP NEGERI 5 BATUKLIANG M. ALFIAN RAMADHANI; Danang Tejo Kumoro; Nuraqilla Waidha Bintang Grendis
Breakthroughs In Informatics, Networking, Algorithms, Research, And Yield (BINARY) Vol. 2 No. 2 (2026): Intelligent Computing, Computer Vision, and Secure Digital Transformation
Publisher : Breakthroughs In Informatics, Networking, Algorithms, Research, And Yield (BINARY)

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Abstract

Perkembangan teknologi informasi telah mendorong transformasi metode pembelajaran dari tatap muka menjadi berbasis digital, salah satunya melalui platform e-learning. SMP Negeri 5 Batukliang mengimplementasikan platform e-learning TOFAS (Technology of Online Fast Application System) sebagai media pembelajaran daring. Penelitian ini bertujuan untuk mengevaluasi tingkat kepuasan siswa kelas IX terhadap penggunaan TOFAS menggunakan metode End-User Computing Satisfaction (EUCS). Metode EUCS mengukur lima dimensi utama, yaitu konten (content), akurasi (accuracy), tampilan (format), kemudahan penggunaan (ease of use), dan ketepatan waktu (timeliness). Penelitian ini menggunakan pendekatan kuantitatif deskriptif dengan metode survei terhadap 57 siswa sebagai sampel yang diambil dari total populasi 66 siswa. Data diperoleh melalui kuesioner dan dianalisis menggunakan Microsoft Excel dan IBM SPSS, dengan uji validitas dan reliabilitas sebagai instrumen pengujian. Hasil penelitian menunjukkan bahwa secara umum siswa merasa puas terhadap platform TOFAS pada semua dimensi EUCS, dengan nilai rata-rata kepuasan berada pada kategori “puas” hingga “sangat puas”. Temuan ini diharapkan dapat menjadi masukan bagi pihak sekolah dan pengembang TOFAS untuk meningkatkan kualitas sistem pembelajaran daring yang lebih efektif dan sesuai kebutuhan pengguna.
Classification of Tilapia Freshness Based on Visual Eye Images Using a Convolutional Neural Network Method Sulistiani; Fahmi Syuhada; Syahrani Lonang
Breakthroughs In Informatics, Networking, Algorithms, Research, And Yield (BINARY) Vol. 2 No. 2 (2026): Intelligent Computing, Computer Vision, and Secure Digital Transformation
Publisher : Breakthroughs In Informatics, Networking, Algorithms, Research, And Yield (BINARY)

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Abstract

This study aims to classify the freshness levels of tilapia based on visual images using a Convolutional Neural Network (CNN) with a VGG16 architecture. Manual assessment of fish freshness tends to be subjective and inefficient, necessitating a more accurate and faster automated system. The research methods used include data collection, data preprocessing (resizing, augmentation), model design, training, and model evaluation. This study compares two models: a conventional CNN and a transfer learning-based CNN using the VGG16 architecture. The results show that the conventional CNN achieved an accuracy of 99.62% with a loss value of 0.0107, while the CNN with the VGG16 architecture achieved 100% accuracy with a loss value of 0.0002. Based on these results, it can be concluded that the use of the VGG16 architecture is capable of improving the model’s performance in classifying the freshness of tilapia more accurately compared to a CNN without the architecture. The developed system can serve as a solution to assist in the rapid and objective identification of fish freshness.
Prototype Model For Plastic Bottle Waste Detection Using Yolov8s lalu sahrul ismail lalu
Breakthroughs In Informatics, Networking, Algorithms, Research, And Yield (BINARY) Vol. 2 No. 2 (2026): Intelligent Computing, Computer Vision, and Secure Digital Transformation
Publisher : Breakthroughs In Informatics, Networking, Algorithms, Research, And Yield (BINARY)

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Abstract

Plastic bottle waste is one of the most common types of inorganic waste found in the environment and has become a serious environmental problem. Along with the rapid development of artificial intelligence technology, object detection methods based on deep learning can be utilised to automatically detect plastic bottle waste in digital images. This study aims to develop a prototype model for plastic bottle waste detection using the YOLOv8s algorithm. The research method used is descriptive quantitative with several stages including dataset collection, preprocessing, model training, testing, and evaluation. The dataset used consisted of 1001 images of plastic bottle waste obtained independently using a smartphone camera and additional datasets from Kaggle. The dataset was labelled and processed using Roboflow with image resizing to 512×512 pixels and divided into training, validation, and testing datasets. Model training was carried out using the Ultralytics library on Google Colab with parameters of 5 epochs, image size 512×512, and batch size 8. The results showed that the YOLOv8s model was able to detect plastic bottle objects properly in various environmental conditions, backgrounds, and lighting variations. Evaluation results indicated that the model achieved good performance based on precision, recall, mAP50, and mAP50-95 values. Therefore, YOLOv8s can be effectively implemented as a lightweight and real-time object detection model for plastic bottle waste detection.
The Website Design and Construction as a Publication Media for MSMEs in the Tembolak Area Using the Laravel Framework Rubiatun Isnaini; Yuan Sa'adati
Breakthroughs In Informatics, Networking, Algorithms, Research, And Yield (BINARY) Vol. 2 No. 2 (2026): Intelligent Computing, Computer Vision, and Secure Digital Transformation
Publisher : Breakthroughs In Informatics, Networking, Algorithms, Research, And Yield (BINARY)

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Abstract

The development of information technology provides opportunities for Micro, Small, and Medium Enterprises (MSMEs) to expand their business promotions through digital media. However, MSMEs in the Tembolak area, Jempong Village, Mataram City, do not yet have a centralized information media that can be used to present business information to the public effectively. This condition causes MSME information to remain scattered and difficult to access by potential customers and tourists. This study aims to design and build a website as a publication medium for MSMEs in the Tembolak area using the Laravel framework. The system development method used is the Waterfall method which includes the stages of needs analysis, system design, implementation, and testing. The system design was carried out using UML and ERD, while the system testing used the Black Box Testing method to ensure all functions run according to requirements.

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