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All Journal Jurnal Ilmiah Binary STMIK Bina Nusantara Jaya Journal of Mutidisciplinary Issues
Pangestu Wonohardjo, Eduard
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Agriculture, Biological Sciences & Forestry Computer Science & IT Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Library & Information Science

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Analysis of Search Engine Optimization Application on Markas Gamers' Website Permatasari, Angelina; Pangestu Wonohardjo, Eduard; Hidayat, Desman; Hendrawaty, Manise; Hartato, Hartato
Journal of Multidisciplinary Issues Vol 2 No 1 (2022): Journal of Multidisciplinary Issues
Publisher : APPS Publications

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (835.338 KB) | DOI: 10.53748/jmis.v1i1.32

Abstract

Objective – Along with the rapid development of information technology and the increasing number of websites, search engines like Google will be increasingly strict in sorting out the best websites that have useful information for their users. This causes website owners to increasingly aggressively improve the quality and popularity of their websites in various ways, such as using advertisements, branding on social media, to the use of SEO (Search Engine Optimization) to support the quality of the website so that it can compete in search engine ranking results. Methodology – Method used in this research is by redesigning the user interface and applying SEO methods. Findings – Being able to improve the metrics of the website can be significantly improved both from its UR and DR and increase visitor traffic as a source of profit for a website. Novelty – This research was conducted on a new website that initially had not implemented SEO and had not been maximized in designing its User Interface. Keywords: Google; Markas Gamers; Redesign; SEO; Website Optimization
Model Pembelajaran Mendalam untuk Tugas NLP: Tinjauan Literatur Sistematis Pangestu Wonohardjo, Eduard
Jurnal Ilmiah Binary STMIK Bina Nusantara Jaya Vol 7 No 1 (2025): Jurnal Ilmiah Binary STMIK Bina Nusantara Jaya
Publisher : STMIK Bina Nusantara Jaya Lubuk Linggau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52303/jb.v7i1.157

Abstract

Dengan berkembangnya model pembelajaran mendalam, terjemahan mesin, yang melakukan tugas-tugas penting dalam pemrosesan bahasa alami, juga mengalami kemajuan yang signifikan. Sistem terjemahan mesin saraf yang menggunakan pendekatan jaringan saraf dalam telah melampaui metode statistik tradisional, terutama dengan munculnya arsitektur transformator dan mekanisme perhatian. Tinjauan literatur sistematis ini mengkaji perkembangan terkini dalam terjemahan mesin berbasis pembelajaran mendalam, dengan fokus pada model terlatih multibahasa, model Transformers, BERT, GPT, dan Seq2Seq selama lima tahun terakhir. Berurusan dengan bahasa yang miskin sumber daya, efisiensi pelatihan, dan kualitas terjemahan lintas domain disebut-sebut sebagai masalah utama dalam terjemahan mesin saraf. Dalam artikel ulasan ini, kami membahas kekurangannya. Selain itu, artikel ini juga menyoroti bagaimana model multibahasa dan tanpa pengawasan telah meningkatkan performa terjemahan mesin.
Co-Authors Angelina Permatasari Desman Hidayat, Desman Hartato, Hartato Manise Hendrawaty, Manise