Klaim Artikel Anda
Verifikasi kepemilikan artikel akademik
Apakah artikel-artikel ini milik Anda?
Daftarkan diri Anda sebagai author untuk mengklaim artikel dan dapatkan profil akademik terverifikasi dengan fitur lengkap.
Badge Verifikasi
Profil terverifikasi resmi
Statistik Lengkap
H-index, sitasi, dan metrik
Visibilitas Tinggi
Tampil di direktori author
Kelola Publikasi
Dashboard artikel terpadu
Langkah-langkah Klaim Artikel:
- 1. Daftar akun author dengan email akademik Anda
- 2. Verifikasi email dan lengkapi profil
- 3. Login dan buka menu "Klaim Artikel"
- 4. Cari dan klaim artikel Anda
- 5. Tunggu verifikasi dari admin (1-3 hari kerja)
Menampilkan 181–190 dari 5979 artikel
A Lightweight Maize Leaf Disease Recognition Using PCA-Compressed MobileNetV2 Features and RBF-SVM
Journal of Computing Theories and Applications
Vol 3
, No 3
(2026)
The integration of Artificial Intelligence (AI) into precision agriculture has significantly improved plant disease recognition; however, many existing deep learning models remain computationally expensive and feature-redundant, limiting their deployment on low-power and edge devices. To address these limitations, this study proposes a lightweight framework for maize leaf disease recognition based on serial deep feature extraction, dimensionality reduction, and machine-learning–based classificat...
Sumber Asli
Google Scholar
DOI
Microstructural and Carbon Phase Analysis of Water Hyacinth Derived Biochar under Particle Size Variation
Lontar Physics Today
Vol 5
, No 1
(2026)
Water hyacinth is an abundant lignocellulosic biomass with strong potential as a sustainable carbon source. This study aims to investigate the effect of particle size variation on the carbon phase and microstructural development of biomass-derived carbon from water hyacinth. The leaves of water hyacinth were used as a raw material, thoroughly washed, cut into small pieces, and sun-dried for 11 days until completely dry. The dried leaves were then ground into powder and sieved into three particle...
Sumber Asli
Google Scholar
DOI
Pengaruh Tingkat Pendidikan Terhadap Kualitas Laporan Keuangan Berbasis SAK EMKM Dengan Sistem Informasi Akuntansi Sebagai Variabel Moderasi : Studi Kasus Pada Coffee Shop Kota Kediri
Jurnal Ekonomi, Bisnis dan Manajemen (EBISMEN)
Vol 5
, No 1
(2026)
This study aims to analyze the effect of education level on the quality of financial statements based on SAK EMKM, with accounting information systems as a moderating variable, focusing on coffee shop micro, small, and medium enterprises (MSMEs) in Kediri City, Indonesia. A quantitative approach was employed using primary data collected through structured questionnaires distributed to 32 business owners or financial managers selected by purposive sampling. Data were analyzed using descriptive st...
Sumber Asli
Google Scholar
DOI
Pengaruh DER, ROE, dan EPS Terhadap Harga Saham Pada Perusahaan Sub Sektor Pulp dan Kertas Yang Terdaftar di BEI Periode 2018 – 2023
Wawasan : Jurnal Ilmu Manajemen, Ekonomi dan Kewirausahan
Vol 4
, No 1
(2026)
This study aims to analyze the effect of Debt to Equity Ratio (DER), Return on Equity (ROE), and Earning Per Share (EPS) on stock prices of pulp and paper sub-sector companies listed on the Indonesia Stock Exchange (IDX) during the 2018–2023 period. This research employs a quantitative associative approach using secondary data obtained from annual financial statements and stock closing prices. The population consists of all pulp and paper sub-sector companies listed on the IDX, with six companie...
Sumber Asli
Google Scholar
DOI
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...
Sumber Asli
Google Scholar
DOI
Addressing Algorithmic Bias and Data Privacy in Human Resource Management
Herdiana, Hendi
; Universitas Pendidikan Indonesia
Universitas Indonesia
Universitas Diponegoro
; Munir, Munir
; Department Management, Faculty of Economics and Business Education, Universitas Pendidikan Indonesia, Bandung, Indonesia
; Hurriyati, Ratih
; Department Management, Faculty of Economics and Business Education, Universitas Pendidikan Indonesia, Bandung, Indonesia
; Sultan, Mokh. Adib
; Department Management, Faculty of Economics and Business Education, Universitas Pendidikan Indonesia, Bandung, Indonesia
; Tua, Frans David
; Department of Electrical Engineering, Faculty of Engineering, Universitas Indonesia, Depok, Indonesia
; Ergashevna, Buriyeva Kibrio
; Faculty of pedagogical, Chirchik State Pedagogical University, Chirchik, Uzbekistan
Telematika
Vol 18
, No 2
(2026)
Artificial intelligence (AI) has transformed Human Resource Management (HRM) by automating recruitment, enhancing performance evaluation, and enabling data-driven workforce planning. However, its adoption raises critical concerns related to algorithmic bias, data privacy, and employee trust, creating a significant gap in understanding how these technical and ethical dimensions interact. This study aims to synthesize current evidence on the impact of AI on HRM functions, the challenges associated...
Sumber Asli
Google Scholar
DOI
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...
Google Scholar
DOI
Development and Evaluation of an IndoBERT-Based NLP Model for Automated Clickbait Detection
Advance Sustainable Science, Engineering and Technology (ASSET)
Vol 8
, No 1
(2026)
The rapid growth of digital news platforms necessitates reliable and automated systems for maintaining content quality at scale. This study presents the engineering and evaluation of an IndoBERT-based Natural Language Processing (NLP) framework for automated clickbait detection in Indonesian news headlines. The proposed framework is designed as an end-to-end text classification pipeline, incorporating data preprocessing, tokenization, fine-tuning of a pretrained IndoBERT model, and systematic pe...
Google Scholar
DOI
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...
Google Scholar
DOI
Implementation of KAMI Index for IT Risk Management at PT. X
Nur Amalina Sabrina
; Keisha Jovie Dermawan
; Annisa Wulandari
; Muhammad Hafidz Fadlillah
; Vicho Yunanda Hidayat
; Afifah Trista Ayunda
JUISI : Jurnal Ilmiah Sistem Informasi
Vol 5
, No 1
(2026)
Keamanan informasi menjadi aspek yang sangat penting bagi perusahaan yang bergantung pada teknologi informasi dalam operasional bisnisnya. PT. X sebagai pengelola pusat perbelanjaan modern memiliki tingkat ketergantungan tinggi terhadap sistem elektronik seperti membership, pembayaran, CCTV, dan perparkiran, sehingga membutuhkan pengelolaan keamanan informasi yang terstruktur. Penelitian ini bertujuan mengevaluasi tingkat kematangan keamanan informasi PT. X menggunakan Indeks Keamanan Informasi...
Sumber Asli
Google Scholar
DOI