EVALUASI ELABORATION LIKELIHOOD MODEL DALAM PEMROSESAN INFORMASI KONTEN INSTAGRAM @JALAHOAKS TERHADAP INTENSI KETERLIBATAN AUDIENS MELALUI SIKAP AUDIENS

Sapta Hari Subangkit, . (2026) EVALUASI ELABORATION LIKELIHOOD MODEL DALAM PEMROSESAN INFORMASI KONTEN INSTAGRAM @JALAHOAKS TERHADAP INTENSI KETERLIBATAN AUDIENS MELALUI SIKAP AUDIENS. Tesis thesis, Universitas Pembangunan Nasional Veteran Jakarta.

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Abstract

The dissemination of misinformation and disinformation through social media requires government public communication that is not only informative but also capable of shaping attitudes and encouraging audience engagement. This study evaluates the explanatory capacity of the Elaboration Likelihood Model (ELM) by examining the effects of argument quality as substantive information associated with central-route processing and source credibility, source attractiveness, and visual presentation as peripheral cues on audience engagement intention toward content published by @jalahoaks, with audience attitude as a mediator. An explanatory quantitative survey was administered online to 391 followers of @jalahoaks. The data were analyzed using covariance-based Structural Equation Modeling with IBM SPSS AMOS 31, including Confirmatory Factor Analysis, structural-model assessment, direct-effect testing, and indirect-effect testing using a 95% bias-corrected bootstrap procedure with 5,000 resamples. Argument quality had a positive direct effect on engagement intention (β = 0.499; p < 0.001) and an indirect effect through attitude (β = 0.126; 95% BC CI [0.008, 0.347]). Attitude positively affected engagement intention (β = 0.434; p = 0.003), whereas source credibility, source attractiveness, and visual presentation had no significant direct or indirect effects on engagement intention. The findings indicate that substantive information is the most consistent driver in the model. Accordingly, misinformation-correction content should prioritize evidentiary strength, relevance, contextual clarity, and verifiability, while source-related and visual elements should support message processing.

Item Type: Thesis (Tesis)
Additional Information: [No.Panggil: 2410421001] [Pembimbing 1: Drina Intyaswati] [Pembimbing 2: Kusumajanti] [Penguji 1: Rini Riyantini] [Penguji 2: Machyudin Agung Harahap]
Uncontrolled Keywords: Elaboration Likelihood Model; argument quality; audience attitude; audience engagement intention; digital public communication.
Subjects: H Social Sciences > H Social Sciences (General)
Divisions: Fakultas Ilmu Sosial dan Ilmu Politik > Program Studi Ilmu Komunikasi (S2)
Depositing User: SAPTA HARI SUBANGKIT
Date Deposited: 28 Aug 2026 02:17
Last Modified: 28 Aug 2026 02:17
URI: http://repository.upnvj.ac.id/id/eprint/52832

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