Web-Based Online Queue Design at Puskesmas Siak Hulu I Kabupaten Kampar-Riau

Increasing patient satisfaction in this case, especially Puskesmas as the government agency that provides health services for the community, will certainly have an impact on the quality of service from the Puskesmas Itself. One of them with an efficient queuing system. A good queue will support regularity in an agency. Previously, analysis and calculation of queuing time had been carried out using the Kolgomorov-Smirnov compatibility test at the Puskesmas Siak Hulu I Kabupaten Kampar- Riau, and the results obtained an average of six working hours of patient care. This research is a pilot project that was carried out as a form of increasing effectiveness and efficiency in Puskesmas. The research has been completed and the results are the basis for this research and further research. The purpose of the current research is to make an online queuing system design, where later the results of this design are used to create a web-based online queuing system. The design is adapted to the existing queuing model at the Puskesmas, namely the Sigle Channel-Multi Steps queuing model. System development using System Development Life Cycle (SDLC) consisting of, analysis, design, implementation, and maintenance. The design phase is carried out in three stages, namely conceptual modeling, database design, and interface design. The design starts from making the proposed Rich-Picture, then carries out the predetermined design stages. With this design, it is hoped that in the future it will facilitate the process of developing a web-based online queuing system.

Analysis of the Queuing System for the Indonesian Islamic Bank (BSI) Bengkulu Branch

The purpose of this study is to determine the average level of customer arrivals and the average service time of customers in the queue. The analytical model used in this study is a multi-channel single-phase queuing theory analysis with a mathematical formula. The queuing process is a process related to the arrival of the customer to a queuing system, then waiting in the queue until the waiter selects the customer according to the service discipline, and finally the customer leaves the queuing system after the service is finished. At Bank Syariah Indonesia (BSI) KC Bengkulu S. Parman 1 there are 5 tellers provided to serve customers who will make deposits, withdrawals and cash transfers. Queues that occur at the optimal service level can be obtained by the performance of the queuing system with the calculation results, namely, the average number of customers in the queue (nq) 31.88 customers, customers in the total system 33.08 people, the average time in the queue 0, 000767 and the total system time is 0.034097 or 2 minutes. Thus, customers do not take too long to make transactions. With the number of tellers as many as five people, there is a long waiting time for customers (Wq) in the queue, which is 0.02777 hours or 2 minutes and the average number of customers in the queue (Ls) is 2 people..

ANALISIS METODE BAYESIAN PADA SISTEM ANTREAN RAWAT JALAN DI RSUP Dr. KARIADI DENGAN DISTRIBUSI SAMPEL POISSON DAN GEOMETRIK

Hospital service facilities cannot be separated from queuing events. Queues are an unavoidable part of life, but they can be minimized with a good system. The purpose of this study was to find out how the queuing system at Dr. Kariadi. Bayesian method is used to combine previous research and this research in order to obtain new information. The sample distribution and prior distribution obtained from previous studies are combined with the sample likelihood function to obtain a posterior distribution. After calculating the posterior distribution, it was found that the queuing model in the outpatient installation at Dr. Kariadi Semarang is (G/G/c): (GD/∞/∞) where each polyclinic has met steady state conditions and the level of busyness is greater than the unemployment rate so that the queuing system at Dr. Kariadi is categorized as good, except in internal medicine poly.

Studying the appointment scheduling window considering patient no-show behavior in one public and one private outpatient clinics

Purpose This study is carried out in one public and one private health-care centers based on different probabilities of patient’s no-show rate. The present study aims to determine the optimal queuing system capacity so that the expected total cost is minimized. Design/methodology/approach In this study an M/M/1/K queuing model is used for analytical properties of optimal queuing system capacity and appointment window so that total costs of these cases could be minimized. MATLAB software version R2014a is used to code the model. Findings In this paper, the optimal queuing system capacity is determined based on the changes in effective parameters, followed by a sensitivity analysis. Total cost in public center includes the costs of patient waiting time and rejection. However, the total cost in private center includes costs of physician idle time plus costs of public center. At the end, the results for public and private centers are compared to reach a final assessment. Originality/value Today, determining the optimal queuing system capacity is one of the most central concerns of outpatient clinics. The large capacity of the queuing system leads to an increase in the patient’s waiting-time cost, and on the other hand, a small queuing system will increase the cost of patient’s rejection. The approach suggested in this paper attempts to deal with this mentioned concern.

On the stationary distributions in some queueing systems

В статье рассматриваются стационарные распределения числа требований в системах массового обслуживания $M_{\lambda}|G|n|\infty$ и $GI_{\lambda}^{\nu}|M_{\mu}|1|\infty$, и показывается, что введение в данные системы массового обслуживания вспомогательных распределений с понятным вероятностным смыслом вместе с их производящими функциями позволяет упростить как доказательство так и его восприятие, а также приводит к новой записи полученных результатов. В первой системе рассматривается усечённое распределение искомого стационарного распределения для вложенной цепи Маркова. Данное усечение связано с количеством каналов $n$ и описывает вероятностные веса состояний системы, когда существует хотя бы один незанятый канал. Во второй системе для описания результатов используется распределение, связанное с распределением количества заявок во входящей группе требований: определяются вероятности хвостов описанного распределения, а потом для получения вспомогательного вероятностного распределения берётся их удельный вес между собой. This paper deals with two queuing system: $M_{\lambda}|G|n|\infty$ and $GI_{\lambda}^{\nu}|M_{\mu}|1|\infty$. The purpose is to find the steady-state results in terms of the probability-generating functions.

To analysis of a two-buffer queuing system with cross-type service and additional penalties

The concept of cloud computing was created to better preserve user privacy and data storage security. However, the resources allocated for processing this data must be optimally allocated. The problem of optimal resource management in the loud computing environment is described in many scientific publications. To solve the problems of optimality of the distribution of resources of systems, you can use the construction and analysis of QS. We conduct an analysis of two-buffer queuing system with cross-type service and additional penalties, based on the literature reviewed in the article. This allows us to assess how suitable the model presented in the article is for application to cloud computing. For a given system different options for selecting applications from queues are possible, queue numbers, therefore, the intensities of transitions between the states of the system will change. For this, the system has a choice policy that allows the system to decide how to behave depending on its state. There are four components of such selection management models, which is a stationary policy for selecting a queue number to service a ticket on a vacated virtual machine each time immediately before service ends. A simulation model was built for numerical analysis. The results obtained indicate that requests are practically not delayed in the queue of the presented QS, and therefore the policy for a given model can be considered optimal. Although Poisson flow is the simplest for simulation, it is quite acceptable for performance evaluation. In the future, it is planned to conduct several more experiments for different values of the intensity of requests and various types of incoming flows.

KINERJA LAYANAN DAN KEPUASAN NASABAH MASA PANDEMI COVID-19 PADA BANK BNI CABANG BOGOR

The research is aimed at describing service quality and customer satisfaction with PT Bank BNI services during the COVID-19 pandemic. The study used 60 customers to be selected randomly as samples. The analysis method uses Importance Performance Analysis (IPA) and Customer Satisfaction Index (CSI). The results of the analysis found that the performance of services provided by PT Bank BNI Bogor Branch has been able to meet the interests of customers by 83.07%. Then it is known that several attributes are the main priority because their performance is still below the interests of customers, namely the queuing system during the Covid-19 pandemic, the speed of customer service during the Covid-19 pandemic, bank operational schedules during the Covid-19 pandemic, guarantees of getting quality service. the Covid-19 pandemic, the completeness of the facilities/equipment provided, the alertness to customer complaints during the Covid-19 pandemic, the speed in resolving the Covid-19 pandemic problems, the readiness to overcome queues during the Covid-19 pandemic and the readiness of officers when needed. From the results of the CSI analysis, it is known that the level of customer satisfaction is 77.61% which is included in the satisfied category. Thus the services provided by PT Bank BNI Bogor Branch during the Covid-19 pandemic can be said to be good but they still have to continue to make improvements so that their service performance is getting better.