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Menampilkan 91–100 dari 2141 artikel
Systematic Review of Supervised Learning Models for Network Flood Detection (NFD): Trends, Performance Evaluation, and Implementation Insights
Habibi, Roni
; Universitas Logistik dan Bisnis Internasional
; Widana, Naufal Dekha
; Universitas Logistik dan Bisnis Internasional
Telematika
Vol 18
, No 2
(2026)
Due to the growing volume, speed, and sophistication of malicious traffic, Network Flood Detection (NFD), especially in the context of Distributed Denial of Service (DDoS) assaults, continues to be a crucial challenge in contemporary network security. Supervised machine learning has been widely used to enhance the precision, scalability, and real-time detection capabilities of NFD systems. However, current research reveals inconsistent results on the optimal supervised learning algorithm, most...
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Functional Evaluation of the Logia Dashboard Using Boundary Value Testing and Cause-Effect Graph Techniques
Ramadhan, Muhammad Rizky Aulia
; Unversitas Lambung Mangkurat
; Abadi, Friska
; Universitas Lambung Mangkurat
; Nugrahadi, Dodon Turianto
; Universitas Lambung Mangkurat
; Saputro, Setyo Wahyu
; Universitas Lambung Mangkurat
; Herteno, Rudy
; Universitas Lambung Mangkurat
; Friska Abadi, Universitas Lambung Mangkurat
; Dodon Turianto Nugrahadi, , Universitas Lambung Mangkurat
; Setyo Wahyu Saputro, Universitas Lambung Mangkurat
; Rudy Herteno, Universitas Lambung Mangkurat
Telematika
Vol 18
, No 2
(2026)
The Logia Dashboard is a web-based information system used to manage rehabilitation plant data on post-mining land. As an alpha-stage system, Logia requires thorough functional and performance evaluation to ensure that all input validations, logical processes, and system responses operate correctly before wider implementation. This study aims to evaluate the functional reliability and performance of the Logia Dashboard by applying a combined approach of Boundary Value Testing (BVT) and Cause-Eff...
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Pengaruh Harga Terhadap Keputusan Pembelian Sapronak Ayam Pedaging Pada Mitra Peternak PT Sejahtera Abadi Unggas Unit Kediri
Populer: Jurnal Penelitian Mahasiswa
Vol 4
, No 4
(2026)
This study aims to analyze the effect of price on purchasing decisions of broiler chicken production inputs (sapronak) among partner farmers of PT Sejahtera Abadi Unggas, Kediri Unit. A quantitative approach with a causal research design was employed. The research sample consisted of 104 active partner farmers, selected using purposive sampling. Data were collected through structured questionnaires using a five-point Likert scale. The collected data were analyzed using validity and reliability t...
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A Participatory GIS Framework for Multi-Hazard Climate Risk Mapping in Indonesia
Fariz, Trida Ridho
; Budiarti, Ratna
; Listyarini, Jassica
; Puspitasari, Atikah Tri
; Calysta, Nadia
; Naufal, Muhammad Ahganiya
; Heriyanti, Andhina Putri
; Eralita, Norma
Advance Sustainable Science, Engineering and Technology (ASSET)
Vol 8
, No 1
(2026)
Climate change has emerged as a global crisis with severe consequences for tropical and coastal regions. Pekalongan Regency, Indonesia, exemplifies these challenges, facing recurrent floods and landslides that threaten livelihoods and infrastructure. Risk mapping is urgently needed to guide adaptation strategies, yet many regions face constraints due to limited data availability. This study develops a multi-hazard risk mapping approach that integrates Geographic Information System (GIS) technolo...
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Deep Learning-Based Classification of Cognitive Workload Using Functional Connectivity Features
Vineeta Khemchandani
; Alok Singh Chauhan
; Shahnaz Fatima
; Jalauk Singh Maurya
; Abhay Singh Rathaur
; Kumar Sharma, Narendra
; Daya Shankar Srivastava
; Vugar Abdullayev
Advance Sustainable Science, Engineering and Technology (ASSET)
Vol 8
, No 1
(2026)
Cognitive workload plays a vital role in tasks that demand dynamic decision-making, especially under high-risk and time-sensitive conditions. An excessive workload can lead to unexpected and disproportionate risks, whereas insufficient workload may cause disengagement, undermining task performance. This underscores the importance of maintaining an optimal level of mental focus in high-pressure situations to ensure successful task execution. This study leverages deep learning methods alongside fu...
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Pengembangan Aplikasi Analisis Sentimen pada Media Sosial XYZ untuk Pengumuman Acara Semilir Japan Matsuri 3 Menggunakan Metode SVM
Vol 5
, No 1
(2026)
Perkembangan media sosial yang pesat telah menghasilkan volume data teks yang sangat besar dalam bentuk opini dan ulasan pengguna. Analisis manual terhadap data ini untuk memahami sentimen publik tidak lagi efisien. Hal inilah yang mendasari dibuatnya sebuah aplikasi analisis sentimen otomatis menggunakan metode machine learning Support Vector Machine (SVM). Untuk mendukung penelitian yang dilakukan, peneliti menggunakan metode penelitian Research and Development (R&D) serta perancangannya m...
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Pengembangan Aplikasi Analisis Sentimen pada Media Sosial XYZ untuk Pengumuman Acara Semilir Japan Matsuri 3 Menggunakan Metode SVM
Naufaldy, Rheyza Avta
; Migunani
; Dewi, Maya Utami
; Panjaitan, Cherlina Helena Purnamasari
; Naufaldy, Rheyza Avta
; Migunani
; Dewi, Maya Utami
; Panjaitan, Cherlina Helena Purnamasari
JUISI : Jurnal Ilmiah Sistem Informasi
Vol 5
, No 1
(2026)
Perkembangan media sosial yang pesat telah menghasilkan volume data teks yang sangat besar dalam bentuk opini dan ulasan pengguna. Analisis manual terhadap data ini untuk memahami sentimen publik tidak lagi efisien. Hal inilah yang mendasari dibuatnya sebuah aplikasi analisis sentimen otomatis menggunakan metode machine learning Support Vector Machine (SVM). Untuk mendukung penelitian yang dilakukan, peneliti menggunakan metode penelitian Research and Development (R&D) serta perancangannya m...
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A Hybrid Deep-Learning and Evolutionary Feature-Selection Framework for Skin Lesion Classification: Application to Monkeypox Detection
Advance Sustainable Science, Engineering and Technology (ASSET)
Vol 8
, No 1
(2026)
The recent resurgence of Monkeypox has highlighted the urgent need for fast and accurate diagnostic tools. In this paper, we propose a new framework of hybrid deep learning to combine both DenseNet121 and MobileNetV2 to obtain both rich and supplementary attributes of the skin lesion images. By pooling the outputs of these two models in terms of features, we get the lightweight representation of the images as well as rich representations of the images. To improve the feature set, we use Genetic...
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Implementasi Pemasaran Digital dan Online Branding sebagai Strategi Pengembangan UMKM
Wawasan : Jurnal Ilmu Manajemen, Ekonomi dan Kewirausahan
Vol 4
, No 1
(2026)
The development of digital technology has triggered significant changes in marketing and brand management, particularly in the Micro, Small, and Medium Enterprises (MSMEs) sector. This study aims to conduct a comprehensive analysis of the implementation of digital marketing and online branding as strategies for developing MSMEs to increase competitiveness and business sustainability in the digital economy era. This study focuses on the use of social media, marketplaces, and various other digital...
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Klasifikasi Jenis Bunga Menggunakan Algoritma Convolutional Neural Network (CNN)
Ade Irgi Firdaus
; Ade Irgi Firdaus
; Dwi Okta Djoas
; Riefaldi Diofano Saputra
; Indry Anggraeny
; Hilda Apriliya Ningsih
Jurnal Elektronika dan Komputer
Vol 18
, No 2
(2026)
This research aims to develop a multiclass flower image classification system using the Convolutional Neural Network (CNN) algorithm with the EfficientNet architecture. The main problem addressed is the difficulty of manual identification of flower species that share high visual similarity. The research stages include collecting 17,299 flower images across 19 classes, performing data preprocessing such as image resizing, pixel normalization, and augmentation, followed by model training using the...
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