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Fathan Mubina Dewadi
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INDONESIA
JADI (Jurnal Teknik Industri)
Published by CV. Indie Press Edutaste
ISSN : 31247997     EISSN : 31248004     DOI : https://doi.org/10.66865
Core Subject :
JADI (Jurnal Teknik Industri) merupakan jurnal ilmiah yang memfokuskan diri pada pengembangan keilmuan dan praktik dalam bidang teknik industri. Jurnal ini bertujuan untuk menjadi wadah publikasi hasil penelitian, kajian teoritis, maupun studi kasus yang relevan dan berkontribusi terhadap kemajuan dunia industri, teknologi, dan inovasi berbasis data. Cakupan bidang jurnal ini meliputi tiga pilar utama: Industrium. Mewadahi kajian dan penelitian di bidang proses industri yang berfokus pada: Optimasi proses produksi Perencanaan dan pengendalian produksi Manajemen kualitas Rantai pasok (supply chain management) Logistik industri dan distribusi Ergonomi dan rekayasa sistem kerja Sistem pemeliharaan dan keandalan mesin Technoverse Revolusi industri 4.0 dan 5.0 Sistem manufaktur terintegrasi dan otomatisasi Internet of Things (IoT) dalam industry Inovasi berbasis data dan transformasi digital Sistem cerdas dan kecerdasan buatan (AI) dalam industry Teknologi cyber-physical systems dan digital twin Inovetia Inovasi dalam industri transformasi dan sistem kendali Data analytics dan big data untuk pengambilan Keputusan Sistem pendukung keputusan (Decision Support System) Rekayasa sistem industri berbasis inovasi Sustainable manufacturing dan inovasi hijau Jurnal ini terbuka untuk akademisi, peneliti, praktisi industri, dan mahasiswa yang ingin mempublikasikan karyanya secara ilmiah dalam konteks teknik industri dan penerapannya yang strategis serta inovatif di berbagai sektor.
Arjuna Subject : -
Articles 20 Documents
 1   2 
Advancements in Artificial Intelligence for Modern Manufacturing Automation: A Comprehensive Review Adinda Sekar Ludwika; Fathan Mubina Dewadi; Damaiyanti Mahulae; Mutia May Nurrahma; Indra Herlambang
JADI (Jurnal Teknik Industri) Vol. 1 No. 3 (2025): Nopember 2025
Publisher : CV. Indie Press Edutaste

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Abstract

Integrasi Kecerdasan Buatan (AI) telah mengubah manufaktur modern dari otomatisasi kaku menjadi sistem otonom yang mampu mengoptimalkan diri. Penelitian ini mengevaluasi dampak teknis dan efisiensi operasional kerangka kerja berbasis AI dalam Industri 4.0. Menggunakan tinjauan sistematis dan analisis kualitatif pada lingkungan industri berkinerja tinggi, penelitian ini menguji sinergi antara pembelajaran mesin, visi komputer, dan robotika tingkat lanjut. Temuan menunjukkan bahwa implementasi AI meningkatkan Overall Equipment Effectiveness (OEE) sekitar 35% dan mengurangi waktu henti tidak terencana sebesar 80% melalui pemeliharaan prediktif. Selain itu, kontrol kualitas berbasis AI secara konsisten mengungguli inspeksi manusia dalam mendeteksi cacat skala mikro. Meskipun menghadapi tantangan berupa biaya awal yang tinggi dan kompleksitas teknis, transisi menuju manufaktur cerdas sangat penting untuk daya saing global. Artikel ini memberikan peta jalan komprehensif bagi penelitian masa depan mengenai pabrik pintar yang terkoneksi secara hiper dan ekosistem kolaborasi manusia-mesin. Hasil penelitian mengonfirmasi bahwa AI adalah katalisator utama bagi pertumbuhan industri generasi berikutnya, yang menawarkan peningkatan terukur dalam presisi dan manajemen sumber daya
Literature Review: Facility Layout Optimization and Safety Management in Manufacturing Workshops Arifia Ekayuliana; Fathan Mubina Dewadi; Muhammad Nurul Mustofa; Nadia Dwi Yuningsih; Nurul Tri Mulyani
JADI (Jurnal Teknik Industri) Vol. 1 No. 3 (2025): Nopember 2025
Publisher : CV. Indie Press Edutaste

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Abstract

Pengaturan strategis fasilitas produksi dan integrasi protokol keselamatan merupakan faktor penentu kritis bagi efisiensi operasional di bengkel manufaktur, sehingga penelitian ini bertujuan untuk mengevaluasi dan mengoptimalkan tata letak fasilitas yang terdiri dari 57 komponen berbeda, termasuk mesin berat (M1–M7) dan sistem pendukung lainnya. Analisis inventaris situs dan hubungan spasial dilakukan secara sistematis menggunakan kerangka kerja Facility Layout Problem (FLP) dengan membagi bengkel ke dalam klaster fungsional produksi, perakitan, pengawasan, dan logistik guna menilai kedekatan antara meja kerja operator (11–16) dengan unit permesinan inti. Temuan menunjukkan bahwa penempatan terpusat ruang instruktur (R1) dan ruang perencanaan (R3) secara signifikan meningkatkan pengawasan area praktek siswa (D1–Dy), sementara implementasi "Safety Area" yang ditentukan secara efektif memisahkan lalu lintas pejalan kaki dari zona berisiko tinggi seperti mesin press hidrolik (M7) dan stasiun pengelasan (MS). Selain itu, isolasi unit intensif kebisingan seperti ruang kompresor (K1) terbukti menjaga standar ergonomis di zona kontrol (R4) dan administrasi (A). Sebagai simpulan, model tata letak terintegrasi ini menunjukkan sinergi yang berhasil antara kebutuhan produksi skala industri dan kebutuhan pedagogis teknis, memberikan tolok ukur strategis bagi manajemen fasilitas yang berpusat pada keselamatan dan produktivitas.
Strategic Modernization of Vocational Workshop Facilities toward Industry 4.0: A Literature Review Muhamad Emir Purdiatama; Fathan Mubina Dewadi; Muhammad Azmi Raihan; Kharis Fadillah Anwar; Muhamad Siswan Setiadi
JADI (Jurnal Teknik Industri) Vol. 1 No. 3 (2025): Nopember 2025
Publisher : CV. Indie Press Edutaste

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Abstract

Makalah ini mengevaluasi modernisasi bengkel pelatihan vokasi dengan fokus pada transisi dari sistem manual ke sistem digital. Dengan menganalisis data inventaris di lima sektor teknis meliputi Kereta Api, Percetakan, Sepatu, Furnitur, dan Pengelasan, tinjauan ini mengidentifikasi kesenjangan teknologi dan strategi implementasi yang diperlukan untuk menyelaraskan pendidikan dengan lanskap industri 2025. Hasil penelitian mengonfirmasi bahwa konvergensi otomatisasi perangkat keras dan konektivitas berbasis data mendefinisikan pusat keunggulan modern. Investasi strategis pada stasiun robotik dan sistem terintegrasi awan sangat penting untuk memastikan daya saing global lulusan vokasi.
Techno-Economic Analysis of Steel-Based Workshop Workstations: A Literature Review on Cost Efficiency and Structural Integrity Fathan Mubina Dewadi; M Dibyo Setiawan; Cahyo Wibowo; Athifah Azza Harisna; Lionel Marthin Pasaribu
JADI (Jurnal Teknik Industri) Vol. 1 No. 3 (2025): Nopember 2025
Publisher : CV. Indie Press Edutaste

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Abstract

Perancangan dan analisis biaya peralatan bengkel industri sangat penting untuk memastikan efisiensi operasional dan keberlanjutan finansial. Penelitian ini mengevaluasi fabrikasi meja kerja alat berat dengan dimensi 1500 x 700 x 850 mm, menggunakan profil besi hollow 40x40x2 mm dan permukaan plat baja 6 mm. Analisis teknis berfokus pada integritas struktural dan standar ergonomi, sedangkan evaluasi ekonomi menggunakan Bill of Materials (BOM) terstruktur dan penilaian waktu kerja tenaga kerja. Hasil penelitian menunjukkan total biaya produksi sebesar Rp 1.510.000, dengan komponen bahan baku mencakup 65,7% dari total anggaran. Biaya kontinjensi sebesar 10% diintegrasikan untuk memitigasi fluktuasi harga pasar. Studi ini menyimpulkan bahwa desain yang diusulkan menawarkan solusi yang kokoh dan hemat biaya untuk kebutuhan bengkel industri, memberikan daya tahan jangka panjang melalui penyelesaian akhir anti-korosif dua lapis.
Upcycling Used Cans A Practical Transformation through Surface Preparation and Aerosol Coating Ibnu Abdul Rosid; Fathan Mubina Dewadi; Adiesa Nugraha Subekti; Muhammad Riziq Rafsyanjani; Ardifan Rizky Amin
JADI (Jurnal Teknik Industri) Vol. 1 No. 3 (2025): Nopember 2025
Publisher : CV. Indie Press Edutaste

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Abstract

Penelitian ini mengevaluasi proses teknis peningkatan nilai guna wadah logam bekas menjadi barang fungsional bernilai tinggi. Dengan menganalisis tahapan penghilangan karat melalui pengamplasan mekanis dan aplikasi aerosol selanjutnya penelitian ini mengidentifikasi parameter kritis untuk memastikan adhesi permukaan dan ketahanan korosi. Hasil penelitian menunjukkan bahwa persiapan permukaan yang sistematis memperpanjang siklus hidup material dari limbah rumah tangga secara signifikan. Investigasi ini menyimpulkan bahwa transisi dari permukaan teroksidasi menuju ekosistem pelapisan digital terintegrasi sangat penting untuk manufaktur berkelanjutan. Investasi strategis pada peralatan pengamplasan presisi dan protokol pelapisan standar memberikan jalur yang layak bagi ekonomi sirkular.
Digital Twin in Smart Manufacturing: A Systematic Literature Review on Predictive Decision-Making, Industrial Sustainability, and Process Optimization Fathan Dewadi; Ahmad Royan; Muhammad Nurcholis; Muhammad Pratama
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/bdb53m45

Abstract

The rapid advancement of Industry 4.0 has accelerated the adoption of Digital Twin (DT) technology in smart manufacturing systems. DT enables virtual replication of physical assets, supporting real-time monitoring, predictive analytics, simulation, and data-driven decision-making. This systematic literature review investigates the role of Digital Twin technology in predictive decision-making, process optimization, and industrial sustainability within smart manufacturing environments. The review synthesizes recent peer-reviewed studies from Scopus, Web of Science, and IEEE Xplore databases. Findings show that DT enhances operational efficiency through integration with machine learning, cyber-physical systems, and Industrial Internet of Things (IIoT), enabling improved maintenance strategies, energy efficiency, and production optimization. In addition, DT contributes to sustainability by reducing waste generation and supporting circular manufacturing practices. Despite its advantages, implementation challenges remain, including high deployment costs, interoperability issues, cybersecurity risks, and lack of data standardization. Overall, the study concludes that Digital Twin is a key enabling technology for future smart factories, particularly when integrated with artificial intelligence, edge computing, and cloud-based manufacturing systems.
Circular Economy Transformation in Textile and Batik Manufacturing: A Bibliometric and Systematic Review of Sustainable Industrial Practices Fathan Mubina Dewadi; Muhamad Emir Purdiatama; Angga Setiawan; Iwan Ridwan
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/qh4s3561

Abstract

The textile and batik manufacturing industries generate significant environmental impacts due to intensive water consumption, chemical usage, and wastewater discharge during production processes. Circular Economy (CE) has emerged as a sustainable industrial approach emphasizing recycling, reuse, and resource efficiency to support green manufacturing transformation. This study aims to analyze the development of circular economy implementation in textile and batik manufacturing industries using bibliometric analysis and systematic literature review (SLR) approaches. Data were collected from Scopus, Web of Science, and Google Scholar databases covering publications from 2015–2026. Bibliometric analysis was conducted using VOSviewer to identify publication trends, thematic structures, and keyword relationships, while SLR was applied to synthesize findings related to sustainable manufacturing practices. The results indicate significant growth of CE-related publications after 2018, particularly in textile recycling, wastewater treatment, eco-friendly dyeing systems, and industrial sustainability. However, CE implementation in batik manufacturing remains limited due to financial, technological, and policy constraints. This study concludes that circular economy strategies possess strong potential for supporting sustainable industrial transformation and environmental sustainability in textile and batik manufacturing sectors.
Data-Driven Innovation in Smart Manufacturing:A Systematic Review of Predictive Decision-Making and Industrial Optimization Adinda Ludwika; Fathan Dewadi; Fadli Robbi; Abel Sulaiman
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/cz7nsk48

Abstract

Industry 5.0 has accelerated the transformation of manufacturing industries toward autonomous, intelligent, and human-centric production systems. Smart manufacturing technologies increasingly integrate Artificial Intelligence (AI), Internet of Things (IoT), Digital Twin, and Cyber-Physical Systems (CPS) to support predictive decision-making and industrial optimization. This study aims to analyze the development of autonomous smart manufacturing systems through a systematic literature review approach. The review process followed the PRISMA methodology using publications indexed in Scopus, Web of Science, and Google Scholar from 2016–2026. The results indicate that AI-driven manufacturing systems improve predictive maintenance, operational efficiency, production flexibility, and industrial sustainability. However, challenges related to cybersecurity, infrastructure readiness, implementation costs, and ethical AI governance remain significant barriers. This study concludes that autonomous smart manufacturing systems possess strong potential to support intelligent and sustainable industrial transformation in the Industry 5.0 era.
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.
Autonomous Smart Manufacturing Systems in the Era of Industry 5.0: A Systematic Review of AI-Driven Decision Intelligence and Industrial Optimization Ade Suhara; Dibyo Setiawan; Fathan Dewadi; Fisika Putra; Gunawan Musyaffa; Surotun Nabawiyah
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/xv9yr868

Abstract

The emergence of Industry 5.0 has accelerated the transformation of manufacturing industries toward autonomous, intelligent, and human-centric production systems. Smart manufacturing technologies increasingly integrate Artificial Intelligence (AI), Internet of Things (IoT), Digital Twin, and Cyber-Physical Systems (CPS) to support predictive decision-making and industrial optimization. This study aims to analyze the development of autonomous smart manufacturing systems through a systematic literature review approach. The review process followed the PRISMA methodology using publications indexed in Scopus, Web of Science, and Google Scholar from 2016–2026. The results indicate that AI-driven manufacturing systems significantly improve predictive maintenance, operational efficiency, production flexibility, and industrial sustainability. However, challenges related to cybersecurity, infrastructure readiness, implementation costs, and ethical AI governance remain significant barriers. This study concludes that autonomous smart manufacturing systems possess strong potential to support intelligent and sustainable industrial transformation in the Industry 5.0 era.

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