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Menampilkan 1–6 dari 6 artikel
Hubungan Keterlibatan Orang Tua dengan Prestasi Belajar Matematika Siswa Kelas IV SD Inpres 18 Kabupaten Sorong
Glory Gracia Christadella
; Mursalim Mursalim
; Dwi Pamungkas
Algoritma : Jurnal Matematika, Ilmu pengetahuan Alam, Kebumian dan Angkasa
Vol 4
, No 3
(2026)
This study aimed to determine the relationship between parental involvement and mathematics learning achievement of fourth-grade students at SD Inpres 18 Sorong Regency. The research employed a quantitative approach with a correlational design. The research subjects consisted of all fourth-grade students from classes IV A and IV B, totaling 66 students. Data on parental involvement were collected using a questionnaire, while students’ mathematics achievement data were obtained from documentation...
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Multi Objective Evolutionary Optimization of Additive Manufacturing Process Parameters for Enhanced Mechanical Performance and Surface Integrity
Yulaikha Maratullatifah
; Dwi Utari Iswavigra
; Very Dwi Setiawan
; Mursalim Mursalim
; Budi Wibowo
International Journal of Mechanical, Industrial and Control Systems Engineering
Vol 1
, No 1
(2026)
Introduction: Additive Manufacturing (AM) has revolutionized the production of complex geometries, offering flexibility, customization, and precision across various industries. However, optimizing multiple process parameters simultaneously to enhance AM performance remains a significant challenge. This study focuses on improving both mechanical properties and surface quality by utilizing multi-objective optimization techniques. Literature Review: The research reviews existing approaches in AM op...
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Energy Aware Reinforcement Learning Approach for Dynamic Production Scheduling Optimization in Sustainable Smart Manufacturing Environments
Yogiek Indra Kurniawan
; Krisna Widi Nugraha
; Rosyid Ridlo Al-Hakim
; Erick Fernando
; Rian Ardianto
; Genrawan Hoendarto
; Mursalim Mursalim
International Journal of Mechanical, Industrial and Control Systems Engineering
Vol 2
, No 4
(2025)
Background: The development of modern manufacturing systems requires production scheduling strategies that not only improve productivity but also optimize energy utilization. Multi-machine production systems with job-shop configurations exhibit high complexity due to dynamic interactions between machines, job queues, and varying processing times, making conventional scheduling methods less effective in handling changing operational conditions. Objective: This study aims to develop and evaluate a...
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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...
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Integrated Digital Twin and Physics Informed Machine Learning Model for Real Time Performance Prediction of Industrial Mechanical Systems
Irlon Irlon
; Siti Shofiah
; Helmi Wibowo
; Erick Fernando
; Genrawan Hoendarto
; Mursalim Mursalim
International Journal of Mechanical, Industrial and Control Systems Engineering
Vol 2
, No 2
(2025)
Background: The rapid advancement of digital technologies in the Industry 4.0 era has transformed industrial mechanical systems into highly interconnected and data driven environments through the integration of sensors, the Internet of Things (IoT), data analytics, and cyber physical systems. This increasing complexity requires more adaptive and accurate monitoring and prediction methods than conventional simulation approaches, which often face limitations in capturing real time dynamic system b...
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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...
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