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All Journal Brilliance: Research of Artificial Intelligence Informatics and Enginering Dedication
Putra Darmansius, Albertus Dwi Andhika
Unknown Affiliation
Computer Science & IT Decision Sciences, Operations Research & Management Mathematics Other

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Pelatihan Pembuatan Website Portofolio Sederhana Putra Darmansius, Albertus Dwi Andhika; Hartati, Ery; Candra, Candra; Chandra, Kelvin William; nicholas, nicholas; Sasongko, Randie
FORDICATE Vol 3 No 1 (2023): November 2023
Publisher : Universitas Multi Data Palembang, Fakultas Ilmu Komputer dan Rekayasa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/fordicate.v3i1.5069

Abstract

Saat ini rata-rata siswa/i banyak yang hanya dapat menggunakan aplikasi ataupun website saja tanpa mengetahui proses pengerjaannya, maka dari itu penulis mengharapkan agar siswa/i tersebut dapat sedikit memahami tentang proses pembuatan website sehingga dapat menumbuhkan rasa ingin tahu mereka untuk membuat website. Dari hal tersebut, penulis memutuskan untuk mengedukasi para siswa/i dengan memberikan materi berupa HTML dan CSS disekolah. Dari peserta pelatihan, sekitar 80% dapat menjalankan materi dengan baik, sedangkan 20% mengalami kendala dalam mengerjakannya. Pelatihan ini bertujuan untuk mengenalkan HTML dan CSS kepada siswa/siswi agar mereka tertarik dan memiliki keinginan untuk terjun di dunia programmer. Dalam pelatihan ini, penulis memberikan solusi dan bantuan kepada siswa/siswi yang mengalami kesulitan dalam mengerjakan materi.
Implementation Of Word Embedding In Book Recommendations Based On Descriptions Putra Darmansius, Albertus Dwi Andhika; Irsyad, Hafiz
Brilliance: Research of Artificial Intelligence Vol. 5 No. 1 (2025): Brilliance: Research of Artificial Intelligence, Article Research May 2025
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v5i1.6456

Abstract

The rapid development of digital libraries and online bookstores has increased the need for intelligent book recommendation systems that can understand user preferences and provide relevant suggestions. However, many existing systems rely on simple keyword matching or collaborative filtering, which often fail to capture the semantic meaning of complex user descriptions. This study aims to develop and evaluate a content-based book recommendation system that combines Word2Vec word embedding models with Knowledge-Based Filtering to improve the relevance of recommendations based on user-provided descriptions. The proposed system utilizes two Word2Vec architectures, Continuous Bag of Words (CBOW) and Skip-gram, to learn semantic relationships between words in book descriptions and user inputs, while Knowledge-Based Filtering incorporates explicit attributes such as publication year, genre, author, and book length to refine the results. The system was tested using a descriptive query: “a good fiction story telling a boy school at great magic school, published on 1995-1999”. The evaluation, measured by Precision@K and Recall@K at K = 5, 10, and 20, shows that CBOW outperformed Skip-gram, achieving a perfect Precision@5 of 1.00 and balanced precision and recall at higher K values, while Skip-gram exhibited more variability at small K. These results indicate that CBOW is more effective in providing stable and highly relevant recommendations at the top of the list. This research confirms that combining semantic embedding and knowledge-based approaches enhances the accuracy and flexibility of recommendation systems. Further studies can explore diverse datasets and user interfaces to broaden practical applications in digital library and e-commerce platforms.
Co-Authors Candra candra Chandra, Kelvin William Hafiz Irsyad Hartati, Ery Nicholas, Nicholas Sasongko, Randie