Winnie’s personality in Natalie Babbit’s tuck everlasting a scientific publication

Authors

  • Aulia Rizkhan Universitas Ahmad Dahlan

DOI:

https://doi.org/10.12928/commicast.v1i2.2729

Abstract

This research is entitled†Winnie’s Personality In Natalie Babbit’s Tuck Everlasting.†The object of this study is to see the personalities of the character in the novel. This research is based on the awareness psychological approach to the type study and laws of psychology are applied to literary works. In this research, the researcher applied psychological approach and Individual psychological theory. Through the objective approach the researcher see the personalities of the character in the novel. The method of the research is descriptive qualitative method. The main data are taken from words, phrases, and sentences of the novel. The supporting data are taken from some books, articles, and internet. The results of this study are clearly explained as follows. The researcher found six personalities in the novel: fictional finalism, social interest, inferiority feeling, striving superiority, style of life, and creative power. From the six analysis of Adler’s individual psychological is connected to each other and builds a unity from the main character’s personality.

References

Adler, A. (2013). The Practice And Theory Of Individual Psychology. In The Practice And Theory Of Individual Psychology. https://doi.org/10.4324/9781315010120
Babbit, S. E., & Roemer, M. (1997). Telling Stories: Postmodernism and the Invalidation of Traditional Narrative. The Journal of Aesthetics and Art Criticism. https://doi.org/10.2307/431809
Feist, G. J. (2006). The psychology of science and the origins of the scientific mind. In The Psychology of Science and the Origins of the Scientific Mind. https://doi.org/10.5860/choice.44-0270
Jandevi, U. (2019). Communication strategy to improve women’s political participation in Indonesia. International Journal of Communication and Society, 1(2), 68–81. https://doi.org/10.31763/ijcs.v1i2.46
Klarer, M. (2013). An introduction to literary studies. In An Introduction to Literary Studies. https://doi.org/10.4324/9780203068915
Lachney, M., Babbit, W., & Eglash, R. (2016). Software Design in the “ Construction Genre ” of Learning Technology : Content Aware versus Content. Computational Culture.
Rijali, A. (2019). ANALISIS DATA KUALITATIF. Alhadharah: Jurnal Ilmu Dakwah. https://doi.org/10.18592/alhadharah.v17i33.2374
Sindelar, J. J., & Milkowski, A. L. (2012). Human safety controversies surrounding nitrate and nitrite in the diet. Nitric Oxide - Biology and Chemistry. https://doi.org/10.1016/j.niox.2012.03.011
Ulfah, M., & Barry, A. (2019). Indonesia Leader Forum, post-truth and political interests in social media and television. International Journal of Communication and Society, 1(1), 17–25. https://doi.org/10.31763/ijcs.v1i1.18

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Published

2020-11-02

Issue

Vol. 1 No. 2 (2020): September

Section

Articles

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