RADIANT: Journal of Applied, Social, and Education Studies https://radiant.polhas.ac.id/index.php/radiant <p>Jurnal RADIANT menggunakan sistem penerbitan daring berbasis Sistem Jurnal Terbuka (OJS) yang diterbitkan oleh Politeknik Harapan Bangsa Surakarta yang menerbitkan artikel sebanyak 3 (tiga) kali dalam satu tahun yaitu pada bulan April, Agustus dan Desember.</p> <p> </p> <p>RADIANT Journal uses open access journal (OJS) publication system managed by Politeknik Harapan Bangsa Surakarta. The journal publishes 3 times a year in April, August, and December</p> en-US radiant@polhas.ac.id (Vilya Lakstian Catra Mulia, S.Hum. M.Hum) samaratulzanah@gmail.com (Sri Wahyuni S.Z.., M.Hum.) Fri, 23 May 2025 08:39:37 +0000 OJS 3.2.1.1 http://blogs.law.harvard.edu/tech/rss 60 Shareloc: An Analysis of Isekai Elements Across Different Genre and Cinematic Cultures https://radiant.polhas.ac.id/index.php/radiant/article/view/312 <p>The <em>Isekai </em>genre stories where characters are transported from their familiar world to a fantastical or parallel reality has gained significant popularity across various media. However, its presence in films from different cultural contexts has received less scholarly attention. The objective of this research is to explore the <em>Isekai </em>elements found in <em>‘Along with the Gods: The Two Worlds’, ‘Saranjana Kota Ghaib’, ‘Spirited Away’</em>, and <em>‘Jumanji: Welcome to the Jungle’</em>. This study aims to analyze how the movie genres aligned with the <em>Isekai </em>elements through the characters journey. This research employed a descriptive qualitative method to analyze both textual and visual elements derived from narrative components and scenes depicting character teleportation or <em>Isekai </em>transitions. The analysis followed (Spradley, 2016) method, which consists of four phases: domain, taxonomy, componential, and cultural theme. In the domain analysis phase, (Mendlesohn, 2014) theory of <em>Isekai </em>was applied. The analysis reveals that <em>Isekai </em>appears in various genres, including adventure, action, and horror, in the four selected films, featuring elements such as portal-quest, liminal, and intrusion. This research helps readers apply <em>Isekai </em>elements to diverse creative works, such as video games, novels, films, and poetry</p> Ardelia Elvina Cahyaningtyas, Ardita Wahyu Safitri, Andriani Ika Saputri, Siti Komsiyah Yuliana Copyright (c) 2025 RADIANT: Journal of Applied, Social, and Education Studies https://radiant.polhas.ac.id/index.php/radiant/article/view/312 Fri, 23 May 2025 00:00:00 +0000 Comparison of Naive Bayes and Support Vector Machine (SVM) Methods in Female Daily Skincare Sentiment Analysis https://radiant.polhas.ac.id/index.php/radiant/article/view/316 <p>The development of the beauty industry in Indonesia has increased significantly, along with the high participation of consumers in providing online reviews, especially through the Female Daily platform. These reviews contain opinions that can be analyzed to determine consumer sentiment towards a product. This study seeks to perform sentiment analysis on beauty product reviews by applying two text classification techniques: Support Vector Machine (SVM) and Naive Bayes. The research stages include collecting review data from Female Daily, text preprocessing (such as tokenization, stemming, and stopword removal), and sentiment classification into two categories, namely Yes and No. The evaluation results indicate that the SVM method outperforms Naive Bayes, achieving a higher level of accuracy. SVM is able to capture more complex patterns in text data, while Naive Bayes tends to produce lower performance due to the assumption of independence between features. The evaluation results demonstrate that the SVM method performs better than Naive Bayes, achieving higher accuracy scores. SVM excels at recognizing more intricate patterns in textual data, whereas Naive Bayes often shows lower performance due to its assumption of feature independence. Overall, the majority of user reviews are positive, reflecting satisfaction with certain beauty products. This study shows that the SVM method is more recommended for text-based sentiment analysis of reviews in the beauty industry, especially in the context of diverse and unstructured consumer review data. As for the accuracy results of the Naive Bayes method is 80% and the accuracy results of the SVM method is 87%.</p> Rifqi Fauzi Rahmadzani, Riszki Wijayatun Pratiwi, Astrid Noviana Paradita Copyright (c) 2025 RADIANT: Journal of Applied, Social, and Education Studies https://radiant.polhas.ac.id/index.php/radiant/article/view/316 Fri, 23 May 2025 00:00:00 +0000