Improvement of knowledge in NLP based on AI for students and teachers in the fashion department

Authors

  • Dwi Intan Af'idah Informatics Engineering, Politeknik Harapan Bersama, Indonesia
  • Sharfina Febbi Handayani Informatics Engineering, Politeknik Harapan Bersama, Indonesia
  • Muhammad Fikri Hidayattullah Informatics Engineering, Politeknik Harapan Bersama, Indonesia
  • Putri Ajeng Imamah Informatics Engineering, Politeknik Harapan Bersama, Indonesia

DOI:

https://doi.org/10.22219/jcse.v5i3.32351

Keywords:

Artificial intelligence, Fashion industry, Natural language processing

Abstract

The fashion department at SMK Negeri 1 Warureja faces significant challenges in understanding and applying Artificial Intelligence (AI)-based Natural Language Processing (NLP) among its students and teachers. Despite the potential benefits of NLP technology for the fashion industry, the limited knowledge and skills concerning NLP tools at SMK Negeri 1 Warureja impede effective utilization. This Community Service Program (CSP) is strategically designed to address these gaps by providing targeted training on NLP tools such as ChatGPT, Chatbot, and Brand24.com within the fashion context. This CSP activity applies the technique of training an initial evaluation through a pre-test assessed participants' baseline understanding prior to the training. During the practical tutorial phase, participants received hands-on training with NLP tools, including practical guidance to ensure real-world application of these concepts. Evaluation results indicated a significant improvement in participants' understanding and skills. The post-test average of 80.47 points showed a significant improvement of 32.19 points over the pre-test average of 48.28 points.

Downloads

Download data is not yet available.

References

Af’idah, D. I., Kusumaningrum, R., & Surarso, B. (2020). Long short term memory convolutional neural network for Indonesian sentiment analysis towards touristic destination reviews. Proceedings - 2020 International Seminar on Application for Technology of Information and Communication: IT Challenges for Sustainability, Scalability, and Security in the Age of Digital Disruption, ISemantic 2020, 630–637. https://doi.org/10.1109/iSemantic50169.2020.9234210

Afidah, D. I., Handayani, S. F., Pratiwi, R. W., & Sari, S. N. (2022). Sentiment of Balis touristic destination reviews using bidirectional long short term memory. Jurnal Manajemen, Teknik Informatika, Dan Rekayasa Komputer, 21(3), 607–618. https://doi.org/10.30812/matrik.v21i3.1402

Agarwal, R., & Wadhwa, M. (2020). Review of state of the art design techniques for chatbots. SN Computer Science, 1–12. https://doi.org/10.1007/s42979-020-00255-3

Alyasiri, O. M., Selvaraj, K., Younis, H. A., Sahib, T. M., Almasoodi, M. F., & Hayder, I. M. (2024). A survey on the potential of artificial intelligence tools in tourism information services keywords artificial intelligence ChatGPT hospitality and tourism industry tourism education and research tourism and management. Babylonian Journal of Artificial Intelligence, 2024, 1–8. https://doi.org/10.58496/BJAI/2024/001

Ardiansyah, A. (2023). Pendampingan perancangan chatbot sebagai media interaktif dalam menghadapi tantangan era digitalisasi. Lamahu: Jurnal Pengabdian Masyarakat Terintegrasi, 2(1), 44–55. https://doi.org/10.34312/ljpmt.v2i1.18078

Aslam, U. (2023). Understanding the usability of retail fashion brand chatbots: Evidence from customer expectations and experiences. Journal of Retailing and Consumer Services, 74, 103377. https://doi.org/10.1016/j.jretconser.2023.103377

Baha, T. A., Hajji, M. El, Es-Saady, Y., & Fadili, H. (2024). The impact of educational chatbot on student learning experience. Education and Information Technologies, 29(8), 10153–10176. https://doi.org/10.1007/s10639-023-12166-w

Bini, S. A. (2018). Artificial intelligence, machine learning, deep learning, and cognitive computing: What do these terms mean and how will they impact health care? The Journal of Arthroplasty, 33(8), 2358–2361. https://doi.org/10.1016/j.arth.2018.02.067

Chadha, J., Gubba, S., & Agrawal, A. (2023). Using NLP to ascertain changes in the fast-fashion industry based on UN sustainable development goals. Journal of Emerging Investigators, 3, 1–6. https://doi.org/10.59720/22-214

Chung, M., Ko, E., Joung, H., & Kim, S. J. (2020). Chatbot e-service and customer satisfaction regarding luxury brands. Journal of Business Research, 117, 587–595. https://doi.org/10.1016/j.jbusres.2018.10.004

Ekawati, D., & Khodra, M. L. (2017). Aspect-based sentiment analysis for Indonesian restaurant reviews. 2017 International Conference on Advanced Informatics, Concepts, Theory, and Applications (ICAICTA), 1–6. https://doi.org/10.1109/ICAICTA.2017.8090963

Ferine, K. F., Nadriati, S., Arif, M., & Muharmi, Y. (2024). Socialization of the use of Chat GPT in increasing village community resources. Journal Of Human And …, 4(3), 271–277. https://jahe.or.id/index.php/jahe/article/view/939

Gruetzemacher, R., & Whittlestone, J. (2022). The transformative potential of artificial intelligence. Futures, 135(November 2021), 102884. https://doi.org/10.1016/j.futures.2021.102884

Ibrohim, M. O., & Budi, I. (2023). Hate speech and abusive language detection in Indonesian social media : Progress and challenges. Heliyon, 9(8), 6. https://doi.org/10.1016/j.heliyon.2023.e18647

Iqbal, T., & Qureshi, S. (2020). The survey: Text generation models in deep learning. Journal of King Saud University - Computer and Information Sciences, xxxx, 1–14. https://doi.org/10.1016/j.jksuci.2020.04.001

Khurana, D., Koli, A., Khatter, K., & Singh, S. (2023). Natural language processing: State of the art, current trends and challenges. Multimedia Tools and Applications, 82(3), 3713–3744. https://doi.org/10.1007/s11042-022-13428-4

Li, W., & Xu, B. (2020). Aspect-based fashion recommendation with attention mechanism. IEEE Access, 8, 1–10. https://doi.org/10.1109/ACCESS.2020.3013639

Lin, X. (2020). Sentiment analysis of e-commerce customer reviews based on natural language processing. Proceedings of the 2020 2nd International Conference on Big Data and Artificial Intelligence, 32–36. https://doi.org/10.1145/3436286.3436293

Liu, L., Subbareddy, R., & Raghavendra, C. G. (2022). AI Intelligence chatbot to improve students learning in the higher education platform. Journal of Interconnection Networks, 22(Supp02). https://doi.org/10.1142/S0219265921430325

Mahmud, M., Ahmed, R. M., & Anas, M. (2023). Sentiment analysis of women’s clothing reviews on e-commerce platforms: A machine learning approach. https://www.researchgate.net/publication/371608341_Sentiment_Analysis_of_Women’s_Clothing_Reviews_on_E-commerce_Platforms_A_Machine_Learning_Approach

Mohamed, K., & Bayraktar, Ü. A. (2022). Analyzing the role of sentiment analysis in public relations: Brand monitoring and crisis management. International Journal of Humanities and Social Science, 9(3), 116–126. https://doi.org/10.14445/23942703/ijhss-v9i3p116

Mohammadi, S. O., & Kalhor, A. (2021). Smart fashion: A review of AI applications in the fashion & apparel industry. In arXiv. https://doi.org/10.48550/arXiv.2111.00905

Niham, D. (2023). Unleashing uncharted horizons: The parallel evolution of AI and historic technological shifts. International Transactions on Education Technology (ITEE), 2(1), 59–64. https://doi.org/10.33050/itee.v2i1.415

Perez-Soler, S., Juarez-Puerta, S., Guerra, E., & De Lara, J. (2021). Choosing a chatbot development tool. IEEE Software, 38(4), 94–103. https://doi.org/10.1109/MS.2020.3030198

Rumaisa, F., Puspitarani, Y., Rosita, A., Zakiah, A., & Violina, S. (2021). Penerapan Natural Language Processing (NLP) di bidang pendidikan. Jurnal Inovasi Masyarakat, 1(3), 232–235. https://doi.org/10.33197/jim.vol1.iss3.2021.799

Shi, M., Chussid, C., Yang, P., Jia, M., Lewis, V. D., & Cao, W. (2021). The exploration of artificial intelligence application in fashion trend forecasting. Textile Research Journal, 1–30. https://doi.org/10.1177/00405175211006212

Sleiman, R., Tran, K.-P., & Thomassey, S. (2022). Natural language processing for fashion trends detection. 2022 International Conference on Electrical, Computer and Energy Technologies (ICECET), 1–6. https://doi.org/10.1109/ICECET55527.2022.9872832

Suraperwata, R. H., & Suyanto, S. (2020). Language modeling for journalistic robot based on generative pretrained transformer 2. 2020 8th International Conference on Information and Communication Technology, ICoICT 2020. https://doi.org/10.1109/ICoICT49345.2020.9166359

Yuniarti, A. R., Munawir, M., Suteddy, W., Muhammad, R., & Ardimansyah, M. I. (2022). Pelatihan pembuatan media pembelajaran online interaktif berbasis chatbot untuk guru SMA/SMK di Kota Bandung. Jurnal Pengamas, 5(December), 1–14. https://doi.org/10.33387/.v5i2.4411

Zhang, L., Wang, S., & Liu, B. (2018). Deep learning for sentiment analysis: A survey. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 8(4). https://doi.org/10.1002/widm.1253

Downloads

Published

2024-12-27

How to Cite

Af'idah, D. I., Handayani, S. F., Hidayattullah, M. F., & Imamah, P. A. (2024). Improvement of knowledge in NLP based on AI for students and teachers in the fashion department. Journal of Community Service and Empowerment, 5(3), 631–638. https://doi.org/10.22219/jcse.v5i3.32351

Issue

Vol. 5 No. 3 (2024): December

Section

Articles

License

Copyright (c) 2024 Dwi Intan Af'idah, Sharfina Febbi Handayani, Muhammad Fikri Hidayattullah, Putri Ajeng Imamah

Creative Commons License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.