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All Journal Jurnal Pengabdian Magister Pendidikan IPA Journal of Classroom Action Research Didaktik : Jurnal Ilmiah PGSD STKIP Subang Jurnal Pendidikan dan Pengabdian Masyarakat
Lalu Ali Wardana
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Journal : Didaktik : Jurnal Ilmiah PGSD STKIP Subang

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ANALYSIS OF CATEGORY SHIFT ON EMMA HEESTERS’S COVER SONG LYRICS ON YOUTUBE Wisnu Sanjaya; Baharuddin; Lalu Jaswadi Putera; Lalu Ali Wardana
Didaktik : Jurnal Ilmiah PGSD STKIP Subang Vol. 10 No. 1 (2024): Volume 10 No. 01 Maret 2024
Publisher : STKIP Subang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36989/didaktik.v10i1.2557

Abstract

This study aims to Analyze and Categorize the types of category shift that occur in the English version of Indonesian Song’s lyrics covered by Emma Heesters. This research was Descriptive Qualitative Research method and catford (1965)translation shift theory was caried in this study . The sample of this research was the lyrics which consist in 7 Song’s of her cover . The data of the research take on Emma Heester Youtube chanel. Based on Catford''s theory as the foundation of this reserach , a total of 189 data were found across 7 songs covered by Emma Heesters. Structure Shift emerged significantly, reaching 20.11%, Intra System Shift, representing 15.87%, . Conversely, Class Shift appeared with the lowest frequency at 5.82%,. Among the identified categories, Unit Shift emerged as the most dominant, constituting 58.20% of the dataset. In summary, the study revealed the dominance of Unit Shift in these translations, highlighting the complexity of adapting song lyrics, including stylistic, rhyme and rhythm consideration and emotional elements, to a different language.
COMPARATIVE STUDY ON CHATGPT VS GOOGLE TRANSLATE IN INDONESIAN-ENGLISH OF BILINGUAL DESCRIPTION OF HISTORICAL HERITAGE AT MUSEUM NEGERI NUSA TENGGARA BARAT Yuni Maulida Afifah SR; Baharuddin; Lalu Jaswadi Putera; Lalu Ali Wardana
Didaktik : Jurnal Ilmiah PGSD STKIP Subang Vol. 10 No. 1 (2024): Volume 10 No. 01 Maret 2024
Publisher : STKIP Subang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36989/didaktik.v10i1.2560

Abstract

Cultural difference pose challenges for machine translation as it’s challenging to find equivalent words to convey cultural concepts. Therefore, this research conducted to find out the accuracy level of two popular machine translation namely Chat-GPT and Google Translate in translating Culture-specific Items from the bilingual description of historical heritage at Museum Negeri Nusa Tenggara Barat. Using HTER by Snover (2006), researcher try to find the level of accuracy of the MT. After long analysis of the accuracy of MT namely Chat-GPT and GT using the HTER theory by Snover, researcher found that between Chat-GPT and GT almost play accurate with the presentation 99.94% and 99.93% while the error rate for Chat-GPT is 0.06% while GT is 0.07%. Furthermore, the quality index (TQI) of the MTs are in the same range, which is EXCELLENT.
Co-Authors Agus saputra Apriani Baharuddin Baharuddin Baiq Mira Aulia Salsabila Boniesta Zulandha Melani Burhanuddin Burhanuddin Dewi Satria Elmiana Dina Sabrina Ida Bagus Yoga Mahendra Johanul Arifin Juni Ningsih Kurniawan Apgrianto M. Ainul Rizki Setiawan M. Sahril Hamdu MARIA BINTANG Maulidatul Hasanah Menariatun Muh. Nazri Nurfitriyanti Handayani Nurhalifah Nur’azizah Putera, Lalu Jaswadi Rani Dwi Hapsari Reksa Rohmadona Renaldi Sutomo Robby Hudiansyah Rosliana Hakim Santi Farmasari Saumi, Fadila Komaris Sri Wahyuni Sribagus Sukardi Sukardi Wahyuni Inggit Pratiwi Wisnu Sanjaya Yuni Maulida Afifah SR