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Journal : PERSPEKTIF

Fenomena Keterbukaan Diri Selebgram Perempuan di Kota Medan Sebagai Cermin Budaya Populer di Media Sosial Instagram Yolanda Harahap; Rahmanita Ginting; Leylia Khairani
PERSPEKTIF Vol 10, No 2 (2021): PERSPEKTIF - July
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/perspektif.v10i2.5117

Abstract

This research aims to analyse the phenomenon of self-disclosure and determine the type of self-disclosure of female Instagram celebrities in Medan as popular culture on Instagram social media. This research uses Self Disclosure Theory and New Media Theory. This research method with qualitative approach. This research uses in-depth interview and observation data collection techniques. Informants in this study were five female Instagram celebrities in Medan, who were selected according to the criteria of the research informant until the information was at its saturation point. The results obtained from this study are female Instagram celebrities in Medan discovering a new perspective on themselves by opening themselves up through the Insta Story feature on Instagram social media, self-disclosure is a job desk for Instagram female Instagram celebrities in Medan, they have pioneered in the trend of opening themselves through the Instagram insta story feature, they are making the pioneers as an example and reference for acting on Instagram social media. The female Instagram celebrities in Medan more often share daily moments than their opinions on updating issues. The moment is about their work or college, a moment of social activity, a moment of hangout, and a vacation moment.
Enhancing Disaster Resilience: Evaluating the Implementation of an Early Warning System through Table Top Exercises Intan Permata Sari; Leylia Khairani; Rahmanita Ginting
PERSPEKTIF Vol. 12 No. 4 (2023): PERSPEKTIF, October
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/perspektif.v12i4.10341

Abstract

This research investigates the periodic implementation of an Early Warning System (EWS) using the Table Top Exercise (TTX) method to assess its effectiveness in enhancing community preparedness for disasters. Specifically, it analyzes the utilization of the Early Warning System as a disaster communication medium through the Table Top Exercise method and identifies challenges faced within the Disaster Risk Reduction Forum in Gung Pinto Village, Kec. Namanteran District, Karo. The study focuses on the People-Centered Early Warning System and the incorporation of Local Wisdom in the Early Warning System. The research employs the Knowledge Construction Theory as its theoretical framework. Data is gathered through interviews, observations, and document analysis, with qualitative analysis methods applied. The study concludes that the implementation of an Early Warning System (EWS) can significantly mitigate risks and safeguard communities against disaster impacts. Additionally, it highlights challenges such as limited information accessibility, resource constraints, and time limitations in the process.
Sentiment Analysis of Comments on Instagram Account @Kalis Mardiasih Regarding Advocacy for the Nia Kurnia Sari Case: A Critical Feminist Approach Khairani, Leylia
PERSPEKTIF Vol. 14 No. 1 (2025): PERSPEKTIF January
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/perspektif.v14i1.13215

Abstract

This study explores public sentiment on Instagram regarding advocacy around the tragic case of Nia Kurnia Sari, a young street vendor brutally murdered in an act of gender-based violence. The case underscores urgent issues of gender inequality and societal responses to violence against women, providing a significant context for this research. Using a critical feminist lens, the study analyzes 251 comments from the Instagram account @KalisMardiasih, employing a mixed-methods approach that integrates quantitative sentiment analysis and qualitative thematic coding. Sentiment analysis, conducted through Python notebooks to automate data processing, reveals that 45% of comments express empathy and solidarity with the victim, while 35% exhibit victim-blaming and skepticism toward feminist advocacy. The remaining 20% are categorized as neutral, including ambivalent statements, requests for more information, or non-committal responses. This neutral category offers essential insights into audience engagement dynamics. Thematic analysis identifies key themes such as solidarity, demands for systemic reform, and resistance rooted in patriarchal norms. Instagram emerges as an empowering platform for feminist advocacy and a contested space where progressive and conservative ideologies collide. These findings emphasize the importance of sustained advocacy and education to combat gender-based violence and advance gender equality.