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p-Index From 2021 - 2026
0.444
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This Author published in this journals
All Journal Metathesis: Journal of English Language, Literature, and Teaching Asian Journal of Management, Entrepreneurship and Social Science
Kanafi
STMIK Bina Patria
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Social Sciences

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Practices Strategies To Increase Student Acceptance During The Covid-19 Pandemic Through Network Marketing ( Case Study) Tri Yusnanto; Kanafi; Khoirul Mustofa
Asian Journal of Management, Entrepreneurship and Social Science Vol. 1 No. 1 (2021): November, Asian Journal of Management, Entrepreneurship and Social Science
Publisher : Cita Konsultindo Research Center

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Abstract

Using network marketing, a public relations technique was used to improve university marketing during the COVID-19 epidemic. This article was written using a qualitative approach and literature study data collection techniques, such as analyzing several books containing national and international articles to obtain data in the form of text studies, which were then analyzed and concluded to obtain research results that are relevant to the research topic. The results of publishing scientific papers in the form of creating a marketing mix during the COVID-19 epidemic can be done by optimizing collage social media such as Facebook and Twitter. for example, collage websites and YouTube accounts. 2) In the context of education, marketing requires a marketing network in order for marketing to be effective and for institutions to readily obtain clients (students). 3) Public relations can study the target environment, develop marketing programs to be carried out, organize the marketing team, implement marketing programs, and track the results of marketing activities that have been carried out while deciding the marketing strategy. This is done so that higher education marketing results in customer satisfaction, allowing the target of students in higher education to be met.
Developing A Collaborative Learning-Based English for Artificial Intelligence Textbook for ESP Instruction Sri Waluyo; Fatimah Nur Arifah; Kanafi
Metathesis: Journal of English Language, Literature, and Teaching Vol. 9 No. 1 (2025): Metathesis: Journal of English Language, Literature, and Teaching
Publisher : Universitas Tidar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31002/metathesis.v9i1.2681

Abstract

Non-native English speakers often face challenges in navigating the complex and specialized language used in AI literature. This study reports on the development of a textbook titled English for Artificial Intelligence, designed to address these challenges through a collaborative learning approach. This book is designed to bridge the gap by providing targeted language instruction tailored to the needs of AI professionals. Employing a Research and Development (R&D) methodology, the study followed the ADDIE model. Data were collected through simple random sampling involving 76 Informatics students, 2 ESP lecturers, a content and a layout expert during the needs analysis phase. The textbook primarily focuses on reading comprehension with supplementary activities in writing and speaking on the exercises. The validation stage, involving 20 students, ESP lectures, and subject matter experts, evaluated the textbook. Results showed that this textbook is Very Feasible to use for ESP teaching and learning. The feasibility aspects can also be seen from the scores given by students and experts, with 4.69 and 4.68 on average, respectively. The feasibility aspects cover content feasibility, presentation feasibility, language use, and graphic feasibility. The acceptance level for this book is 88% and 84% by the experts and students, respectively. These findings confirm that the textbook is both pedagogically sound and contextually appropriate, offering a practical solution for improving English proficiency among AI learners and contributing to more inclusive participation in the global AI discourse.
Co-Authors Fatimah Nur Arifah Khoirul Mustofa Sri Waluyo Tri Yusnanto