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All Journal IT-Explore: Jurnal Penerapan Teknologi Informasi dan Komunikasi
William, Thomas
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Computer Science & IT Control & Systems Engineering

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Pengembangan sistem pendukung keputusan berbasis AI untuk evaluasi ide konten digital pra-produksi Honggowidagdo, Hermawan; William, Thomas; Henkie Ongowarsito
IT Explore: Jurnal Penerapan Teknologi Informasi dan Komunikasi Vol 5 No 1 (2026): IT-Explore Februari 2026
Publisher : Fakultas Teknologi Informasi, Universitas Kristen Satya Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24246/itexplore.v5i1.2026.pp109-118

Abstract

The rapid growth of short-form social media platforms has increased the complexity of decision-making during the digital content planning stage. Content creators are required to evaluate the feasibility of content ideas and determine platform suitability prior to production, while most existing tools primarily focus on post-publication analytics. This study aims to design an Artificial Intelligence (AI)-enabled Decision Support System (DSS) to evaluate digital content ideas in the pre-production stage. Adopting a Design Science Research approach, the study develops a conceptual design artifact that integrates intrinsic content idea characteristics with cognitive and affective response modeling grounded in the Stimulus–Organism–Response (S-O-R) framework, alongside platform affordance mapping. The proposed artifact operationalizes a reflective evaluation mechanism that generates platform recommendation scores and idea enhancement suggestions without claiming deterministic or predictive performance modeling. Evaluation was conducted qualitatively through practitioner assessment to examine perceived usefulness, clarity of recommendations, and decision support contribution. The findings indicate that the developed artifact provides a structured reflective framework for early-stage content evaluation. Theoretically, this study extends the application of the S-O-R framework by operationalizing it as a design logic for a pre-production DSS artifact. Practically, the proposed system has the potential to support more systematic decision-making prior to content production.
Co-Authors Henkie Ongowarsito Honggowidagdo, Hermawan