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ANALISIS METODE BAYESIAN PADA KINERJA SISTEM ANTREAN INSTALASI RAWAT JALAN RSUP DR. KARIADI (Studi Kasus: Poliklinik Mata, Poliklinik THT, Laboratorium, dan Pendaftaran)

*Eny Sulistyowati  -  Departemen Statistika, Fakultas Sains dan Matematika, Universitas Diponegoro, Indonesia
Sugito Sugito  -  Departemen Statistika, Fakultas Sains dan Matematika, Universitas Diponegoro, Indonesia
Di Asih I Maruddani  -  Departemen Statistika, Fakultas Sains dan Matematika, Universitas Diponegoro, Indonesia
Open Access Copyright 2021 Jurnal Gaussian under http://creativecommons.org/licenses/by-nc-sa/4.0.

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Abstract

Indonesian people’s awareness of the importance of health has increased significantly so that it has a positive impact on the development of the health sector in Indonesia. The largest service facility in Central Java Province is RSUP Dr. Kariadi. The number of patients who came for an examination at Dr. Kariadi’s arrival rate is unpredictable. This can cause the service system to be busy and result in queues. The purpose of this study was to find out how the service system in Dr. Kariadi especially eye polyclinic, ENT polyclinic, laboratory, and registration. Queue theory has random arrivals and services. Bayesian method is used to analyze the queue system, that has been running for a long time by combining the prior and likelihood distribution of samples. Prior distribution is obtained from previous research, namely the Poisson distribution. Meanwhile, the likelihood of the sample obtained from the current study is the Poisson distribution and the Negative Binomial distribution. The resulting queue models for the eye polyclinic are (GAMM/BETA/4):(GD/∞/∞), ENT polyclinic (GAMM/GAMM/2):(GD/∞/∞), laboratory (GAMM/GAMM/4):(GD/∞/∞), and registration (GAMM/GAMM/3):(GD/∞/∞). Based on the results of the study, it was found that the patient care system at the eye polyclinic, ENT polyclinic, laboratory, and registration met steady state condition, meaning that the service system was running well. The value of the unemployment rate at the eye polyclinic is 96,36%; ENT polyclinic 31,86%; laboratory 34,87% and registration 32.85%. Thus, at the eye polyclinic, the unemployment rate is greater than the busy level. Meanwhile, in ENT polyclinics, laboratories, and registration is the opposite occurs.

 

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Keywords: Bayesian Method; Steady State; Unemployment Rate; Prior Distribution; Posterior Distribution

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