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 1–5 dari 5 artikel
Explainable Artificial Intelligence Framework for Interpretable Fault Diagnosis and Remaining Useful Life Prediction in Smart Industrial Rotating Machinery
Suyahman Suyahman
; Deny Prasetyo
; Ahmad Budi Trisnawan
; Ardy Wicaksono
; Muhamad Furqon
International Journal of Mechanical, Industrial and Control Systems Engineering
Vol 1
, No 1
(2026)
Predictive maintenance (PdM) plays a crucial role in modern industrial systems by minimizing downtime, reducing maintenance costs, and optimizing asset performance. However, many predictive models operate as “black box” systems, limiting transparency and making it difficult for operators to interpret their outputs. This study aims to integrate Explainable Artificial Intelligence (XAI) techniques with Remaining Useful Life (RUL) prediction models to improve both accuracy and interpretability. Var...
Sumber Asli
Google Scholar
DOI
Adaptive Human Robot Collaboration Model Using Computer Vision and Intelligent Control for Flexible Manufacturing Workstations
Deny Prasetyo
; Suyahman Suyahman
; Hadi Jayusman
; Samsinar Samsinar
; Nimas Ratna Sari
; Mursalim Mursalim
International Journal of Mechanical, Industrial and Control Systems Engineering
Vol 2
, No 4
(2025)
The rapid development of modern manufacturing technology has driven the emergence of human-robot collaboration (HRC) as part of the transformation toward a human-centric intelligent production system. In collaborative work environments, robots are not only required to work efficiently but also to interact safely and responsively with operators. However, most conventional industrial robot systems still use rigid motion controls and are unable to dynamically adapt to human activity around them.Thi...
Sumber Asli
Google Scholar
DOI
Experimental Investigation of Green Hydrogen Integration into Industrial Thermal Systems for Sustainable and Low Carbon Manufacturing Applications
Dwi Feriyanto
; Agus Wantoro
; Deny Prasetyo
; Very Dwi Setiawan
; Faizal Riza
International Journal of Industrial Innovation and Mechanical Engineering
Vol 1
, No 2
(2025)
Background: The global energy transition requires low-carbon solutions that can be integrated into existing thermal systems without drastic infrastructure changes. Hydrogen blending in conventional combustion systems has emerged as a promising pathway to reduce carbon emissions while maintaining operational flexibility. Objective: This study aims to experimentally evaluate the effect of hydrogen blending ratios (0–100% by volume) on thermal efficiency, CO₂ emissions, and NOx emissions, and to de...
Sumber Asli
Google Scholar
DOI
Explainable Artificial Intelligence Techniques for Enhancing Interpretability and Trustworthiness in Autonomous Vehicle Decision Making Systems
Ahmad Jurnaidi Wahidin
; Siti Shofiah
; Siska Narulita
; Deny Prasetyo
; Ardy Wicaksono
; Teguh Arifianto
; Muhamad Furqon
International Journal of Computer Technology and Science
Vol 1
, No 2
(2024)
Autonomous vehicles (AVs) are revolutionizing transportation by relying on advanced AI techniques like deep learning and reinforcement learning for decision-making and navigation. However, concerns about the opacity of traditional AI models in safety-critical applications such as autonomous driving raise issues related to safety, accountability, and trust. This study explores the integration of Explainable AI (XAI) techniques in AV systems to enhance transparency and interpretability while maint...
Sumber Asli
Google Scholar
DOI
Edge Computing Enabled Real Time Anomaly Detection Framework for Secure Industrial Cyber Physical Systems Using Lightweight Deep Neural Networks
Mursalim Mursalim
; Deny Prasetyo
; Suyahman Suyahman
; Rosalina Yani Widiastuti
; Mursalim Mursalim
; Antoni Pribadi
International Journal of Mechanical, Industrial and Control Systems Engineering
Vol 1
, No 1
(2024)
Cyber Physical Systems (CPS) are vital for managing and controlling critical infrastructures, such as industrial control systems, power grids, and transportation networks. These systems integrate digital and physical components, offering numerous benefits for industrial automation. However, the increasing interconnectivity of these systems has introduced new security vulnerabilities, particularly in anomaly detection and system reliability. This research aims to address these challenges by propo...
Sumber Asli
Google Scholar
DOI