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All Journal West Science Interdisciplinary Studies Prosiding Seminar Nasional Rekayasa dan Teknologi (TAU SNAR- TEK) Journal of Social Entrepreneurship and Creative Technology
Mahmudin Mahmudin
Universitas Islam Syekh-Yusuf
Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Social Sciences

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Deep Learning Untuk Mendeteksi Kelelahan Pekerja Dadang Sujana; Sutresna Juhara; Monita Rahayu; Mahmudin Mahmudin; Maulana Fany Kurnia Pratama
Prosiding TAU SNARS-TEK Seminar Nasional Rekayasa dan Teknologi Vol. 2 No. 1 (2023): Prosiding TAU SNARS-TEK Seminar Nasional Rekayasa dan Teknologi 2023
Publisher : Fakultas Teknik dan Teknologi - TANRI ABENG UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47970/snarstek.v2i1.496

Abstract

Salah satu komponen penyebab kecelakaan kerja adalah human error. Kecelakaan kerja dapat terjadi ketika pekerja mengalami kelelahan baik secara fisik maupun mental. Indikator kelelahan yang digunakan pada penelitian ini adalah rasa kantuk. Mengantuk saat melakukan pekerjaan dapat menyebabkan menurunnya konsentrasi dalam bekerja yang tentunya akan berpengaruh peda produktivitas kerja dan dapat berakibat menimbulkan kecelakaan kerja. Tujuan penelitian ini adalah meminimalisir kecelakan yang terjadi pada lingkungan kerja terutama yang disebabkan oleh rasa kantuk sehingga bisa mencapai zero accident dengan melibatkan perkembangan teknologi. Metode yang digunakan adalah membuat rancangan sistem dengan bahasa phyton, algoritma CNN dan implementasi sistem menggunakan Raspberry Pi yang bisa mendeteksi mata bagi para pekerja atau karyawan untuk mengetahui rasa kantuk yang dapat dilihat dari seberapa sering menutup mata yang terdeteksi oleh kamera kemudian sistem akan bekerja dan mengirimkan sinyal alarm sebagai pengingat bagi pekerja untuk tetap fokus dalam bekerja sehingga tidak menghambat kelancaran produksi. Hasilnya adalah alat pendeteksi kelelahan (kantuk) dengan tahap scan wajah baik secara langsung menggunakan kamera maupun menggunakan foto, shape predictor, eye landmark yang sudah diuji coba menggunakan 15 sampel pekerja dengan tingkat akurasi alat sebesar 93%.
The Effect of Artificial Intelligence Adoption, Demand Prediction, and Production Planning on Operational Efficiency in the Textile Industry in Jakarta Loso Judijanto; Khamaludin Khamaludin; Mahmudin Mahmudin; Devi Susiati; Hanifah Nurul Muthmainah
West Science Interdisciplinary Studies Vol. 2 No. 02 (2024): West Science Interdisciplinary Studies
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/wsis.v2i02.669

Abstract

This research investigates the impact of Artificial Intelligence (AI) adoption, demand prediction, and production planning on operational efficiency within the textile industry in Jakarta. A quantitative approach, employing surveys and statistical analysis, was undertaken with a diverse sample of 150 participants representing various company sizes and industry tenures. The study reveals a moderate level of AI adoption, with machine learning algorithms and predictive analytics being prevalent. While perceived benefits include improved production efficiency and enhanced quality control, challenges such as initial investment costs and the need for skilled personnel underscore the nuanced landscape of AI integration. The effectiveness of demand prediction is moderate, with traditional methods prevailing but advanced analytics demonstrating higher efficacy. Production planning strategies exhibit a positive correlation with Industry 4.0 principles, showcasing their role in enhancing operational efficiency. Participants perceive operational efficiency positively, with significant correlations identified between AI adoption, demand prediction, production planning, and perceived efficiency. Key factors contributing to operational efficiency include streamlined processes, effective resource utilization, and adaptive production planning. The findings provide actionable insights for industry stakeholders, emphasizing the importance of a holistic approach to technology adoption and strategic planning.
SUSTAINABLE BUSINESS MODELS FOR CREATIVE STARTUPS IN THE DIGITAL ERA Loso Judijanto; Khamaludin Khamaludin; Mahmudin Mahmudin; Ma’rifani Fitri Arisa
Journal of Social Entrepreneurship and Creative Technology Vol. 2 No. 1 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jseact.v2i1.2055

Abstract

The rise of the digital era has transformed the way businesses operate, especially for startups in the creative industries. As digital technologies reshape market dynamics, the need for sustainable business models that can adapt to rapid changes and ensure long-term success has become crucial. Creative startups, often operating in a highly competitive and fast-evolving environment, face unique challenges in maintaining financial stability while staying innovative. This research aims to explore sustainable business models for creative startups in the digital era, identifying strategies that can drive growth, profitability, and resilience. The study uses a mixed-methods approach, combining qualitative case studies of successful creative startups with quantitative surveys to assess common practices and challenges. Findings reveal that startups employing flexible, customer-centric business models, leveraging digital tools for global reach, and emphasizing continuous innovation are more likely to achieve sustainability. Moreover, the integration of sustainable practices, such as environmentally conscious production and ethical business strategies, has shown to contribute to long-term success. The study concludes that creative startups in the digital era must adopt adaptable, tech-driven business models that prioritize customer engagement and sustainability. By embracing digital transformation, startups can not only survive but thrive in a rapidly changing business landscape.
Co-Authors Dadang Sujana Devi Susiati Hanifah Nurul Muthmainah Khamaludin Khamaludin Loso Judijanto Ma'rifani Fitri Arisa Maulana Fany Kurnia Pratama Rahayu, Monita Sutresna Juhara