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All Journal Journal of Educational, Health and Community Psychology Tibuana : Journal of Applied Industrial Engineering Jurnal Abadimas Adi Buana Majalah Ekonomi Jurnal Penamas Adi Buana Wahana : Tridarma Perguruan Tinggi WAKTU: Jurnal Teknik UNIPA Jurnal Teknik Elektro dan Komputer TRIAC Aptisi Transactions on Technopreneurship (ATT) Humaniora bit-Tech Jurnal Ilmiah Manajemen Kesatuan Jurnal Scientia Etos : Jurnal Pengabdian Masyarakat IJORER : International Journal of Recent Educational Research Seminar Nasional Hasil Riset dan Pengabdian (SNHRP) Jurnal Pengabdian Inovasi dan Teknologi Kepada Masyarakat Jurnal Sains dan Aplikasi Keilmuan Teknik Industri Jurnal Ilmiah Multidisiplin Indonesia Jurnal Pengabdian Masyarakat dan aplikasi Teknologi Kanigara Journal of Economic Development and Village Building Advance Sustainable Science, Engineering and Technology (ASSET)
Yunia Dwie Nurchayanie
Universitas PGRI Adi Buana Surabaya
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Journal : bit-Tech

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Fashion Cerdas: AI dan Masa Depan Industri Mode Yunia Dwie Nurcahyanie; Adi Winarno; Agus Ridwan Misbahuddin
bit-Tech Vol. 7 No. 3 (2025): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v7i3.2242

Abstract

Industri fashion mengalami transformasi fundamental dengan integrasi kecerdasan buatan (AI) dalam berbagai aspek, mulai dari desain, produksi, hingga pemasaran. AI telah merevolusi cara industri ini beroperasi dengan memungkinkan personalisasi tren, prediksi permintaan pasar, serta optimalisasi rantai pasok secara lebih efisien dan akurat. Teknologi berbasis machine learning, computer vision, dan natural language processing berperan dalam menganalisis data konsumen, mengembangkan desain otomatis, serta meningkatkan pengalaman pelanggan melalui sistem rekomendasi berbasis AI. Selain itu, AI berkontribusi dalam pengurangan limbah produksi melalui optimalisasi penggunaan bahan baku dan prediksi tren mode yang lebih presisi, sehingga meningkatkan aspek keberlanjutan industri fashion. Penelitian ini meninjau penerapan AI dalam industri fashion dengan fokus pada berbagai teknologi inovatif yang digunakan dalam pengembangan desain fashion, e-commerce, serta manajemen rantai pasok. Studi ini juga mengidentifikasi tantangan utama dalam implementasi AI, termasuk biaya investasi tinggi, ketergantungan pada data berkualitas, serta isu etika terkait bias algoritma dan dampak terhadap tenaga kerja manusia. Meskipun menghadapi tantangan tersebut, penerapan AI menawarkan peluang besar untuk meningkatkan efisiensi operasional, mempercepat inovasi desain, dan memperkuat daya saing industri fashion di tingkat global. Dengan berkembangnya teknologi AI, industri fashion diharapkan dapat lebih adaptif, inovatif, dan berkelanjutan dalam menghadapi dinamika pasar global. Hasil penelitian ini dapat memberikan wawasan bagi akademisi dan praktisi industri fashion dalam memahami potensi serta implikasi jangka panjang dari adopsi AI, sekaligus mendorong penelitian lebih lanjut mengenai integrasi teknologi ini dalam berbagai aspek industri fashion.
Text-Based Sentiment Analysis of Online Reviews: Evidence from Indonesia’s Muslim Women’s Fashion Sector Nurcahyanie, Yunia Dwie; Saraswati, Sabrina Nur
bit-Tech Vol. 8 No. 3 (2026): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Indonesia’s Muslim women’s fashion market has expanded rapidly alongside e-commerce growth, generating massive volumes of online product reviews (OPRs) that remain underutilized for systematic product development. This study addresses a gap in the literature: while sentiment analysis can classify review polarity, term-level classification alone cannot translate consumer feedback into actionable design attributes for fashion products, a domain where tacit knowledge, material properties, and aesthetic judgment are central. A two-layer hybrid approach is proposed that combines computational sentiment extraction with expert semantic translation. In the first layer, 2,050 OPRs from three Indonesian Muslim fashion brands on Shopee were preprocessed and classified using a maximum entropy (MaxEnt) model, achieving 84.11% accuracy, 90.09% precision, and an F1 score of 89.95% on test data. In the second layer, ten experienced designers interpreted the MaxEnt output through structured interviews, translating raw sentiment features into design-relevant categories. Positive sentiment features clustered around product quality, material comfort, and design authenticity, while negative features concentrated on product-image discrepancies, poor fabric quality, sizing mismatches, and color inaccuracy. Designer interpretation uncovered semantic dimensions invisible to the classifier, yielding eight major product performance categories. This study contributes methodologically by demonstrating the necessity of a human-in-the-loop expert validation layer for sentiment-based consumer insight extraction in design-intensive domains, and practically by providing a framework for converting OPR data into product development inputs.
Co-Authors A.A. Ketut Agung Cahyawan W Abdul Hafidz Achmad Afandy Adi Winarno Afrista, Sitta Mega Agus Ridwan Misbahuddin Alarsy, Alarsy Anggalih , Nanda Nini Antonius Cahyono Antonius Cahyono Arieviana Ayu Laksmi Asidigisianti Surya Patria Azzahra, Adelia Baihaqi Baihaqi Binantoro, Patria Winahyu Carreca, Irhamna Nirbhaya David Nugroho Deril Adi Setya Dewi Sukmawati Dinar Ester Marturia Oktaviana Simanjuntak Dinda Cahya Novianti Djoko Adi Walujo Djoko Adi Walujo Djoko Adi Walujo Dwi Arman Prasetya Eva Rosita Gilang Surya Hanny Hafiar Istikhoroh, Siti Jariyah Jati Abdhi Wasesa, Andarmadi Jelita Citrawati Jihan Jumali, Muhamad Abdul Khalid Walidi Kiky Bagus Setiyo Pratama Koesdijati, Titik Laksmi, Arieviana Ayu M. Hanif Zufikri M. Nushron Ali Mukhtar Maemonah, Maemonah Martadi, Martadi Meita Santi Budiani Meita Santi Budiani, Meita Santi Mochammad Abdul Machfud Muhammad Dwi Hendra Yudha Muhammad Risfan Ramadhani Muhammad Setyo Ferdhiansyah Mulyana, Phonny Aditiawan nanda, famela berry Ni Wayan Sukmawati Puspitadewi Noerchoidah NOVA KRISTIANA Olievia Prabandini Mulyana Olievia Prabandini Mulyana, Olievia Prabandini Panjaitan, Nismah Patria Winahyu Binantoro Prasetiyo, Bagus Prihono Prihono Prihono Prihono Prihono Prihono Prihono, Prihono Rohmadiani, Linda Dwi Rosariawari, Firra Rosita, Eva Rudiyantoro Rudiyantoro Rudiyantoro, Rudiyantoro Rusdiyantoro Rusdiyantoro Rusdiyantoro Rusdiyantoro Rusdiyantoro Rusdiyantoro, Rusdiyantoro Sabrina Nur Saraswati Sagita Rochman Saraswati , Sabrina Nur Saraswati, Sabrina Nur Siti Nuurlaily Rukmana, Siti Nuurlaily Sitta Mega Afrista Suharyanto Suharyanto Suparman Suparman Titik Koesdijati Titik Koesdijati Titik Koesdijati Tjahjani, Ida Kusnawati Umi Anugerah Izzati Umi Anugerah Izzati, Umi Anugerah usuf Agung Zakaria Walidi, Khalid Wildan Surya Wijaya Yitno Utomo Yulianto , Muhammad Teguh Zakaria, Muhammad Zulvan