Machine Learning for Handoffs Classification Based on Effective Communication History

Authors

  • Anita Ira Agustina Simbolon AKPER Dharma Husada
  • Maria Pujiastuti STIKes Santa Elisabeth
  • Indra Kelana Jaya Universitas Methodist Indonesia
  • Kerista Tarigan Universitas Sumatera Utara
  • Marzuki Sinambela Department of Physics, FMIPA, Universitas Sumatera Utara

Keywords:

machine learning; handoffs; classification; SVM; effective communication

Abstract

An important step in data effective communication in handoffs process analysis is data exploration and representation. Communication in handoff treatment is crucial to protect the patients and it can lead to patient’s safety, discontinue care of a patient or the cause loss of important information related to the continuum of care. In this case, we use the machine learning technique by using Support Vector Machine for classification the handoffs for twenty weeks to analysis and represented based on the effective communication history. We used handoffs dataset which employed from Arifin Achmad Hospital in Pekanbaru, Indonesia. The result indicated the performance of the designed system was successful and could be used in handoffs analysis based on the effective communication histories in Arifin Achmad Hospital in Pekanbaru, Indonesia.

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How to Cite

Simbolon, A. I. A., Pujiastuti, M., Jaya, I. K., Tarigan, K., & Sinambela, M. (2019). Machine Learning for Handoffs Classification Based on Effective Communication History. Sinkron : Jurnal Dan Penelitian Teknik Informatika, 3(2), 265-267. Retrieved from https://jurnal.polgan.ac.id/index.php/sinkron/article/view/10074