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All Journal English Language and Literature Best Journal (Biology Education, Sains and Technology) Review: Journal of Multidisciplinary in Social Sciences
KHAIRUNNISA, SYAFIRA
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Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Immunology & microbiology Languange, Linguistic, Communication & Media Public Health Social Sciences

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A Multimodal Analysis of Advertisements Broadcasted on YouTube Based on Gender Khairunnisa, Syafira; Rosita, Nur
English Language and Literature Vol 13, No 4 (2024)
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/ell.v13i4.131447

Abstract

This research is concerned with the multimodal analysis of advertisements broadcasted on YouTube based on gender. This study focused on Rexona men and women advertisements in order to analyze gender stereotypes portrayed in verbal and visual elements from the advertisements. A qualitative method was used to analyze the data in the study. Visual data were analyzed by transitivity theory by Halliday (2004), visual data were analyzed by visual grammar representation (Kress and van Leeuwen, 2006) and generic structure potential (Cheong, 2004). Meanwhile, gender stereotypes were analyzed by Branndon (2017) aspect of gender stereotype theory. The result showed that from all six types of processes, material process is the dominant process of the verbal element of Rexona men and women advertisement, whereas in visual grammar analysis dominated by action process. In addition, visual analysis is dominated by visual elements such as lead, display, and emblem. Gender stereotypes could be seen in Rexona Women's advertisement because personality traits dominate it. In contrast, domestic behavior and occupation often appeared in Rexona men's advertisements.
Inovasi EMOKIDS : Alat Pendeteksi Emosi Pada Anak Berbasis Image Processing Dan Extreme Machine Learning Untuk Meningkatkan Mental Siswa Kelas 2 Pada Pendidikan Jasmani Dan Kesehatan Anak Di SD. Harahap, Yusuf; Sari, Mawar; Nurjannah, Vanny; Sari, Nurhana Fatika; Hanum, Latifa; Primadani, Amelia; Amanda, Dyra; Putri, Khairunnisa; Roudhoh, Mustika; Nurafrisa, Luthfia; Resya, Nazwa; Febriola, Sahara; Lestari, Adinda; Khairunnisa, Syafira; Aulia, Cindy
BEST Journal (Biology Education, Sains and Technology) Vol 7, No 2 (2024): September 2024
Publisher : Program Studi Pendidikan Biologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30743/best.v7i2.10471

Abstract

Tujuan utamanya adalah untuk meningkatkan kesehatan mental siswa kelas 2 Sekolah Dasar dalam mata pelajaran pendidikan jasmani dan kesehatan. Di era perkembangan teknologi informasi dan kecerdasan buatan, muncul peluang besar untuk menciptakan sistem yang mampu memantau dan mendeteksi emosi anak secara real-time, sehingga memberikan dukungan emosional yang lebih akurat dan tepat sasaran dalam konteks pendidikan. Pendekatan literature review untuk menganalisis teori-teori terkait deteksi emosi, pengolahan citra wajah, dan penerapan EML dalam dunia pendidikan. Dari hasil kajian pustaka, EMOKIDS diharapkan dapat mengenali emosi dasar siswa, seperti bahagia, marah, takut, dan cemas, yang memiliki pengaruh langsung terhadap keterlibatan mereka dalam aktivitas pendidikan jasmani. Analisis menunjukkan bahwa pemantauan emosi melalui ekspresi wajah dapat menciptakan lingkungan belajar yang lebih inklusif. Hal ini mempermudah guru dalam memberikan intervensi yang sesuai berdasarkan kondisi emosional siswa, terutama pada siswa yang menghadapi tantangan emosional selama proses pembelajaran.Penggunaan teknologi EML dalam pengolahan data menjadi salah satu keunggulan utama alat ini. Dengan mendeteksi emosi anak secara efektif, EMOKIDS diharapkan dapat menjadi alat yang mendukung peningkatan kesehatan mental siswa. Teknologi ini memungkinkan guru untuk memahami lebih baik kebutuhan emosional siswa dan memberikan pendekatan pengajaran yang lebih personal dan sesuai. Alat ini juga berpotensi meningkatkan partisipasi siswa dalam pembelajaran, khususnya pada pendidikan jasmani, di mana tantangan fisik dan sosial dapat memengaruhi motivasi dan kenyamanan siswa
Application of the QCC Method to NG Dent in the Visual Inspection Process at PT Sugiyama Indonesia Khairunnisa, Syafira; Alfariza, Muhammad Rizki; Wibiksana , Fajar; Alamsyah, Mahlufi; Prastyo, Yudi
Review: Journal of Multidisciplinary in Social Sciences Vol. 1 No. 12 (2024): November
Publisher : Lentera Ilmu Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59422/rjmss.v1i12.665

Abstract

The problem that occurs at PT SUGIYAMA Indonesia is that there are many defects in the inner and outer areas. Defects occur during the process stage or cutting, rolling. So that when the material has reached the visual inspection stage, many types of NG (Not Good) occur, including NG (Not Good) which often occurs based on NG (Not Good) recap data in the last three months of 2024 is NG (Not Good) Dent. Based on the data listed, the percentage of NG (Not Good) Dent increases every month, and the highest defect rate is around 33k pcs of the total NG (Not Good) of the overall model. Therefore, a case study study was conducted using the QCC (Quality Control Circle) method to analyze the occurrence of the defect, and aimed to reduce the number of NG (Not Good) Dent and make the production process better. Based on the data from the research results, the researcher succeeded in reducing NG (Not Good) Dent based on data from the last three months, which had reached 100%, after observations and using the QCC method and its auxiliary tools, namely the cause-and-effect diagram (Fishbone) and the pareto diagram, the percentage in the next two months from November to December 2024, only reached 37%.
Co-Authors Alamsyah, Mahlufi Alfariza, Muhammad Rizki Amanda, Dyra Aulia, Cindy Febriola, Sahara Harahap, Yusuf Latifa Hanum Lestari, Adinda mawar sari Nur Rosita Nurafrisa, Luthfia Nurjannah, Vanny Prastyo, Yudi Primadani, Amelia Putri, Khairunnisa Resya, Nazwa Roudhoh, Mustika Sari, Nurhana Fatika Wibiksana , Fajar