Perancangan Sistem Informasi Analisis Sentimen Engagement Instagram Mitralogistics dengan SVM Berbasis Web: Studi Kasus: PT. Naira Mitralogistik Indonesia - Muhammad Ayub; Surya Hendra Putra; Ramson Rikson Maruwahal Sijabat (Lembaga Pengembangan Kinerja Dosen, 2026)
Naira Mitralogistik Indonesia (Mitralogistics) actively utilizes Instagram as a promotional and digital communication channel, yet its creative team lacks a structured system for recording and monitoring content performance data. Statistical data such as views, likes, comments, and saves are only temporarily observed through Instagram Insights without documentation or data-driven analysis. This study aims to design a web-based information system that integrates content engagement data management with sentiment analysis of user comments using the Support Vector Machine (SVM) method combined with TF-IDF feature extraction. The system was developed using PHP and MySQL with the Waterfall methodology as the development model. The proposed system enables the creative team to input and manage Instagram content statistics, view engagement analysis results, and obtain sentiment classification of comments when available. Compared to the current manual approach, the web-based system offers more structured data management, faster content performance evaluation, and data-driven strategy development. The implementation of this system is expected to improve the effectiveness of digital promotion management and support the development of a more targeted and consistent content strategy at Mitralogistics.