Performance of Chatbot Assistant for Stroke Patients Through Quality of Service Metrics

Azwar Rangga Arasaf; Erika Loniza; Meilia Safitri

doi:10.21831/jee.v8i2.72009

Performance of Chatbot Assistant for Stroke Patients Through Quality of Service Metrics

Azwar Rangga Arasaf, Department of Medical Electronics Technology, Universitas Muhammadiyah Yogyakarta, Indonesia
Erika Loniza, Department of Medical Electronics Technology, Universitas Muhammadiyah Yogyakarta, Indonesia
Meilia Safitri, Department of Medical Electronics Technology, Universitas Muhammadiyah Yogyakarta, Indonesia

10.21831/jee.v8i2.72009

Abstract

Strokes can impede functioning by disrupting blood circulation, leading to functional deficits that may make communication difficult for stroke survivors. Communication issues can significantly lower the quality of life for stroke patients, who often depend on family and caregivers, who may struggle to understand their needs. A stroke patient communication tool using a chatbot assistant system is needed. This system enables patients and caregivers to communicate remotely without disrupting the caregiver's work. This study aims to assess the effectiveness of communication aid devices for stroke patients when integrated with a chatbot assistant system. It also aims to evaluate network performance through Quality-of-Service testing to ensure optimal connectivity for caregivers. The Quality of Service approach assesses the internet network's quality with the support of the Wireshark application. The average outcome for the delay parameter is 163.243 ms, with a 0% result for the packet loss parameter and a throughput value of 16.236 Kbps. Based on these findings, it achieves a score of 3 in one category and excels in delay and throughput. Concerning packet loss, it scores a four and is considered excellent in this area. Based on the findings related to delay, packet loss, and throughput, an average index of 3.33 has been calculated, indicating a positive outcome for Quality of Service evaluation.

Keywords

stroke, chatbot assistant, quality of service

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DOI: https://doi.org/10.21831/jee.v8i2.72009