Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal Engineering and Technology International Journal (EATIJ) JADI (Jurnal Teknik Industri)
Ibnu Rosid
Politeknik Negeri Jakarta
Aerospace Engineering Agriculture, Biological Sciences & Forestry Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Mechanical Engineering

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Design, Development, and Performance Evaluation of a Closed-System Batik Fabric Drying Machine for Small-Scale Industry Applications Arifia Ekayuliana; Fathan Dewadi; Nabila Yudisha; Ibnu Rosid; Al Fauzi; Muhamad Purdiatama; Adinda Ludwika; Ahmad Royan; Muhammad Nurcholis
Engineering and Technology International Journal Vol 7 No 03 (2025): Engineering and Technology International Journal (EATIJ)
Publisher : YCMM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55642/eatij.v7i03.1156

Abstract

This study presents the design and performance evaluation of a closed-system batik fabric drying machine for small-scale industries. The system integrates a spinner for initial dewatering and a hot-air blower with thermostatic control at 60 °C. Experimental tests examined drying time, temperature stability, and fabric quality. Results showed that 2 kg of batik fabric dried in 18 minutes—about 70 % faster than traditional sun drying. The closed-loop air circulation improved thermal uniformity (±1.5 °C deviation) and reduced energy use by 25 %. No color fading or fiber damage occurred, and ultraviolet lamps prevented microbial growth. This design demonstrates that combining mechanical efficiency, thermal control, and ergonomics can enhance energy efficiency and production reliability for micro-scale batik industries.
Generative AI and Data-Driven Innovation in Smart Manufacturing: A Systematic Literature Review of Intelligent Industrial Transformation Ibnu Rosid; Fathan Dewadi; Friscilia Simanullang; Mochamad Pangestu
JADI (Jurnal Teknik Industri) Vol. 2 No. 1 (2026): Smart Manufacturing
Publisher : CV. Indie Press Edutaste

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66865/jkyhm884

Abstract

The rapid advancement of Industry 4.0 technologies has accelerated the transformation of manufacturing industries toward intelligent and data-driven systems. Smart manufacturing integrates technologies such as Internet of Things (IoT), Artificial Intelligence (AI), Big Data Analytics, and Digital Twin to improve predictive decision-making and industrial optimization. This study aims to analyze the development of data-driven innovation in smart manufacturing through a systematic literature review approach. Data were collected from Scopus, Web of Science, and Google Scholar databases covering publications from 2015–2026. The review process followed the PRISMA methodology for systematic article selection and analysis. The results indicate that major research themes include predictive analytics, AI-based decision support systems, industrial optimization, digital twin implementation, and smart factory integration. The study also reveals increasing adoption of machine learning and industrial analytics to improve manufacturing efficiency, sustainability, and operational resilience. However, challenges related to cybersecurity, data integration, infrastructure readiness, and implementation costs remain significant barriers. This study concludes that data-driven innovation possesses substantial potential to support intelligent industrial transformation and sustainable manufacturing optimization.
Co-Authors Adinda Ludwika Ahmad Royan Al Fauzi Arifia Ekayuliana Fathan Dewadi Friscilia Simanullang Mochamad Pangestu Muhamad Purdiatama Muhammad Nurcholis Nabila Yudisha