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Journal : Jurnal Ilmiah Profesi Pendidikan

Students’ Ability in Reading Narrative Text at The Eleventh Grade of SMAN 1 Masbagik in Academic Year 2023/2024 Ilahi, M. Rifky Surya; Thohir, Lalu; Wardana, Lalu Ali; Elmiana, Dewi Satria
Jurnal Ilmiah Profesi Pendidikan Vol. 9 No. 4 (2024): November
Publisher : Fakultas Keguruan dan Ilmu Pendidikan, Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jipp.v9i4.2715

Abstract

This study aim to analyze the ability of grade XI students at SMAN 1 Masbagik in reading narrative text. It is descriptive qualitative design. The participants in this study were 19 students from class XI-F7. The data were collected using a reading test and a questionnaire. The data obtained from the reading test were analyzed and calculated to determine the final score and identify the most difficult aspects of reading. Meanwhile, the data from the questionnaire were analyzed by reducing the data, displaying, and drawing conclusions. The results of this study indicate that out of 19 students, only three students scored in the very high category, six students scored high, three students scored medium, four students scored low, and three students scored very low. In addition, making inferences emerged as the most challenging reading aspect. Through an analysis of questionnaire responses, two prominent obstacles were identified: limited vocabulary knowledge and cognitive load. Many students faced difficulties in deciphering individual word meanings, thereby impeding their overall comprehension of texts. This study highlights the imperative for targeted strategies aimed at addressing these challenges to improve reading proficiency and academic achievement among students.
Exploring Translation Strategies of Thesis Abstract Written by Non-English Department Students in The University of Mataram Zahara, Intan Hardiani; Baharuddin, Baharuddin; Wardana, Lalu Ali; Putera, Lalu Jaswadi
Jurnal Ilmiah Profesi Pendidikan Vol. 9 No. 4 (2024): November
Publisher : Fakultas Keguruan dan Ilmu Pendidikan, Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jipp.v9i4.2822

Abstract

This study investigates the translation problems, strategies, and the most frequently used strategy in translating Indonesian thesis abstracts into English. The subjects of this research comprised eight thesis abstracts written by non-English department students at the University of Mataram during the 2023 academic year. Utilizing Baker’s theory on translation problems and strategies, which encompasses eleven aspects, this study employed a mixed-methods approach, combining quantitative and qualitative analyses. The findings reveal a total of 78 translation problems across the eight Indonesian thesis abstracts. Among Baker's identified problems, only eight were observed, including: culture-specific concepts (31 instances), source language concepts not lexicalized in the target language (4 instances), semantically complex source language words (14 instances), a lack of specific terms in the target language (1 instance), differences in expressive meaning (8 instances), differences in form (2 instances), differences in frequency and purpose of specific forms (6 instances), and the use of loan words in the source text (12 instances). To address these challenges, seven out of eight translation strategies from Baker’s theory were employed in the English thesis abstracts. The most utilized strategy was translation using loan words (35 instances, 45%), followed by translation using a more general word (12 instances, 16%), translation using a neutral word (10 instances, 13%), translation by omission (10 instances, 13%), translation by paraphrase using a related word (4 instances, 5%), and the least employed strategies were translation using cultural substitution (3 instances, 4%) and paraphrase using unrelated words (3 instances, 4%). Of the 78 translation problems identified, 77 were resolved using the seven strategies, while one problem remained unsolved due to an unacceptable translation. This thesis aims to serve as a valuable reference for translators, English department students, and researchers in the field of translation. The findings indicate a significant need for enhanced support and resources in the translation process for non-English department students at the University of Mataram.
The Translation of Multilingual Signboards in Mataram City Using Google NMT Fithri, Nurshahifah; Baharuddin, Baharuddin; Wardana, Lalu Ali
Jurnal Ilmiah Profesi Pendidikan Vol. 10 No. 4 (2025): November
Publisher : Fakultas Keguruan dan Ilmu Pendidikan, Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jipp.v10i4.4100

Abstract

This research investigates the use of Google Neural Machine Translation (GNMT) in translating multilingual signboards across Mataram City. It focuses on examining the accuracy and readability of GNMT translations to assess their effectiveness in representing real-world public communication. Based on the formulated research questions, this study aims to analyze the accuracy and readability of Google Neural Machine Translation (GNMT) in translating multilingual signboards in Mataram City and to assess the translation quality of Google NMT in comparison to human translation on public multilingual signboards. The research was conducted from June 9 to July 4, 2025, along Jl. Majapahit, Mataram City, West Nusa Tenggara. The population of this study encompasses all multilingual signboards found in public spaces across Mataram City, while the sample was drawn specifically from multilingual signboards located along Jl. Majapahit, Mataram. A total of 209 signboards, including both monolingual and multilingual types, were purposively selected based on readability, completeness, and accessibility for analysis. The study found that GNMT achieved an average accuracy and readability score of 4.37 compared to the human score of 5.0, performing well on clear and structured texts but showing limitations in translating cultural and idiomatic expressions, which require human refinement for contextual accuracy. In conclusion, GNMT effectively translates multilingual signboards with 100% OCR success, performing well on clear texts but struggling with idiomatic and culturally nuanced expressions, thus highlighting the need for human involvement to ensure contextual and cultural accuracy.