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The Function of Dramatic Persona in the Film “The Menu” (2022) Munawaroh, Silvi; Heriyati, Nungki
Mahadaya: Jurnal Bahasa, Sastra, Dan Budaya Vol 3 No 2 (2023): Oktober 2023
Publisher : Fakultas Ilmu Budaya, Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/mhd.v3i2.11455

Abstract

This study aims to determine the portrayal of characters in the film The Menu 2022. In examining the characters in the film, The Menu, researcher conducted a characterization analysis which was classified into seven functions of dramatic characters through the theoretical framework of Vladimir Propp. This study is used because narratology theory can focus on the actions of a character who is limited in terms of meaning. Through this classification, researchers can find out the depiction of characters and the limits of their actions. The data collection method is carried out by qualitative methods and narrative analysis by collecting research results in the form of descriptions accompanied by screenshots. This study produced findings in the form of depictions of seven-character functions contained in the film "The Menu". The resulting conclusions, based on the data and analysis conducted in this research, reveal a deeper understanding of the narrative structure character’s function using dramatic persona analysis in the film "The Menu" and identify the roles and functions of the characters in the film. The result of this research, researcher found 7 dramatic persona function in the film. Such as, the villain, the donor, the helper, the dispatcher, princess/prize, the hero, and the false hero. Keywords: The Menu Movie, Vladimir Propp, Dramatic Persona, Narratology
Cross-Domain Sentiment Analysis using Transfer Learning: A Literature Review on Natural Language Model Adaptation from Social-Media to Macroeconomic Indicator Prediction Munawaroh, Silvi
International Journal of Research and Applied Technology (INJURATECH) Vol. 5 No. 2 (2025): December 2025
Publisher : Universitas Komputer Indonesia

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Abstract

This study reviews the efficacy of transfer learning in adapting sentiment analysis from social media domains to macroeconomic indicator prediction. The study evaluates existing literature on natural language model architectures, specifically Transformer-based models, performing domain adaptation from informal social media discourse to formal economic contexts. Findings indicate that pre-trained models significantly enhance predictive accuracy for data-scarce economic indicators by capturing real-time public perception. While effective in addressing labeled data sparsity, primary challenges involve linguistic noise and inherent demographic biases within social media datasets. Transfer learning serves as a critical bridge in transforming public sentiment into predictive economic signals. This cross-domain approach provides a dynamic, supplementary instrument for policymakers to monitor macroeconomic fluctuations through digital behavioral patterns.