Penelitian ini bertujuan untuk menganalisis penggunaan big data bagi praktisi humas di Pertamina regional Sulawesi. Metode yang digunakan adalah metode deskriptif kualitatif. Dalam pengumpulan data menggunakan teknik pengumpulan data wawancara mendalam, observasi, dokumentasi, jurnal, dan media informasi yang ada hubungannya dengan masalah yang diteliti. Analisis data menggunakan teknik analisis menurut Miles dan Huberman yang terdiri dari reduksi data, penyajian, dan penarikan kesimpulan. Validitas data dilakukan dengan teknik triangulasi data. Hasil penelitian menunjukkan bahwa penggunaan big data bagi praktisi humas di Pertamina regional Sulawesi adalah sebagai berikut; Big data digunakan untuk media monitoring, big data menentukan sentimen perusahaan dan mengidentifikasi pesaing perusahaan, dan berita perusahaan yang mampu big data. Penelitian ini didasarkan pada teori strukturasi adaptif, yang mengkaji keberadaan teknologi informasi baru dalam suatu perusahaan atau organisasi berdasarkan struktur perusahaan. Dengan big data ini, praktisi humas di Pertamina regional Sulawesi dapat memanfaatkan teknologi big data untuk pekerjaan yang lebih cepat dan mudah.
This study aims to identify public relations practitioners' adaptation in the big data era in Makassar City. It used the descriptive qualitative method. Data were collected from in-depth interviews, observation, documentation, and relevant journals and media information. Data were analyzed based on the Miles and Huberman covering data reduction, presentation, and concluding. The validity of the data used data triangulation techniques. The results showed that the public relations practitioner's adaptation in the big data era in Makassar City covered the stages of increasing knowledge, following trends, and building creativity in the digital era. This study was based on the Adaptive Structuration Theory which examines the adaptation of new information technology in an organization based on the company structure. Through this adaptation process, public relations practitioners are expected to be able to survive in the big data era.
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