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All Journal Journal of Information Technology and Computer Science SPEKTA (Jurnal Pengabdian Kepada Masyarakat : Teknologi dan Aplikasi)
Rafif, Sulthan
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Materials Science & Nanotechnology

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Multilabel Classification for Keyword Determination of Scientific Articles Rafif, Sulthan; Setya Perdana, Rizal; Pandu Adikara, Putra
Journal of Information Technology and Computer Science Vol. 8 No. 2: August 2023
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jitecs.202382560

Abstract

In writing scientific articles, there are provisions regarding the structure or parts of writing that must be fulfilled. One part of the scientific article that must be included is keywords. The process of determining keywords manually can cause discrepancies with the specific themes discussed in the article. Thus, causing readers to be unable to reach the scientific article. The process of determining the keywords of scientific articles is determined automatically by the classification method. The classification process is carried out by determining the set of keywords owned by each scientific article data based on the abstract and title. Therefore, the classification process applied is multi-feature and multi-label. Classification is done by applying the Contextualized Word Embedding Method. The implementation of Contextualized Word Embedding Method is done by applying BERT Model. By applying the BERT Model, it is expected to provide good performance in determining the keywords of scientific articles. The evaluation results by applying the BERT Model to the case of multi-label classification on abstract data for keyword determination resulted in a loss value of Training Data is 0.514, loss value of Validation Data is 0.511, and an accuracy value of 0.71, a precision value of 0.71, a recall value of 0.71, an error value of 0.29 and f-1 score of 0.83. Based on the results of the evaluation, it shows that the BERT Classification Model can carry out a classification process to determine a set of keywords from each abstract data in scientific articles.
Developing and Managing MSME Websites to Improve Kampoeng Ilmu's Operational Performance Alifah, Amalia Nur; Rachmaniar, Desita Nur; Mustaqim, Tanzilal; Rafif, Sulthan
SPEKTA (Jurnal Pengabdian Kepada Masyarakat : Teknologi dan Aplikasi) Vol. 6 No. 2 (2025)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/spekta.v6i2.13871

Abstract

Background: MSMEs in Kampoeng Ilmu Surabaya continue to face obstacles in product marketing and digital adoption, which limit their operational growth. This program aims to address these issues by developing an integrated website and improving digital literacy among MSME partners to strengthen their online visibility and business sustainability. Contribution: The program contributes to the community by providing a digital platform (UMKMCerdas website) that enables MSMEs to independently manage product data, storefront profiles, and promotional information. It also enhances partners’ capacity to operate digital tools, supporting long-term empowerment and competitiveness. Method: The implementation consisted of five structured stages: needs analysis through interviews, website design with UI/UX and database planning, website development using PHP (Laravel), MySQL, Tailwind, and Filament, training and mentoring for MSME partners, and evaluation through continuous monitoring. A participatory approach was used to ensure active involvement and skill transfer to 82 MSME actors. Results: The integrated website successfully provides features such as bookstore profiles, product catalogs, Google Maps integration, WhatsApp contacts, and an admin dashboard. Post-training responses showed significant enhancement in partners’ confidence and ability to use digital tools for promoting their businesses and managing information. Conclusion: The program effectively strengthens the digital capabilities of Kampoeng Ilmu MSMEs, enabling them to manage business content independently and expand their market reach.
Co-Authors Alifah, Amalia Nur Desita Nur Rachmaniar Pandu Adikara, Putra Setya Perdana, Rizal Tanzilal Mustaqim