Predicting Patient Satisfaction Levels Using Artificial Intelligence Technology for Food Service at ERI Soedewo RSPAD Gatot Soebroto

Suhermi; Rinto; Singgih; Sri Watini; Nova Ramadhona

doi:10.34306/att.v5i2sp.334

Authors

Suhermi MH. Thamrin University
Rinto MH. Thamrin University
Singgih MH. Thamrin University
Sri Watini University of Panca Sakti Bekasi
Nova Ramadhona University of Raharja

DOI:

https://doi.org/10.34306/att.v5i2sp.334

Keywords:

Satisfaction Level, Food Service, Inpatients, Artificial Intelligence

Abstract

Satisfaction is one aspect that assesses the quality of health services, namely in serving food in hospitals. The purpose of this study was to describe the level of patient satisfaction with food at the Eri Soedewo Pavilion, Gatot Soebroto Army Hospital. The results of a study of 47 patients in the Eri Soedewo Pavilion in June 2021 showed that the remaining food of patients who consumed 20%, 35 patients were categorized as good, while 12 patients had the remaining food consumed 20%, which was classified as not good. Therefore, researchers are interested in conducting this research. Methods: The type of research used is observational with a cross-sectional design. Samples were taken using purposive sampling with inclusion criteria: male and female inpatients aged18 years admitted for at least two days, patients who received oral food from the hospital, were not illiterate and could communicate, had signed the PSP form and were willing as research samples. The model in this study was 47 patients taken in June 2021. Results: Based on the sample size calculation, 47 people were determined. The results of the level of patient satisfaction at the Eri Soedewo Pavilion, Gatot Soebroto Army Hospital, found that the performance of food serving has not met the minimum standard set, namely 90%. With a higher percentage of reality, namely with an average of 82.0%, the average expectation percentage is 76.7%. However, suppose the real results are compared with patient expectations. In that case, the result is that the patient is satisfied with the services provided. Artificial intelligence can assess medical data, food preferences, and patient feedback to improve food serving performance.

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