Landasan Teoretis Penelitian AI dan Jurnalisme: Sebuah Tinjauan Literatur Sistematis

Abstract

The rapid integration of artificial intelligence (AI) into journalism has generated a substantial body of academic research, yet this growing field remains characterized by significant theoretical fragmentation. This article presents a systematic literature review (SLR) aimed at identifying and analyzing the theoretical frameworks employed in studies on AI and journalism, as well as examining how these frameworks are applied in research. A comprehensive literature search was conducted across Scopus and Web of Science databases for the period Januari 2019– June 2026. The findings reveal that research in this field utilizes diverse theoretical frameworks, with three dominant theories emerging: (1) the Socio-Technical Systems approach, which emphasizes the interplay between AI technology and human elements within the journalistic ecosystem; (2) Gatekeeping Theory, employed to analyze how AI transforms news selection and distribution processes; and (3) Human-Machine Communication (HMC), which focuses on the communication dynamics between AI as a communicative agent and audiences. However, the analysis also uncovers significant theoretical fragmentation and persistent gaps.