scholarly journals ANALISIS SISTEM PELAYANAN KERETA API DI STASIUN SEMARANG TAWANG MENGGUNAKAN PROSES BAYESIAN

2020 ◽  
Vol 9 (4) ◽  
pp. 495-504
Author(s):  
Lifana Nugraeni ◽  
Sugito Sugito ◽  
Dwi Ispriyanti
Keyword(s):  
Poisson Distribution ◽  
Posterior Distribution ◽  
Public Transportation ◽  
Bayesian Method ◽  
Service System ◽  
Likelihood Function ◽  
Performance Standard ◽  
Sample Distribution ◽  
Service Patterns ◽  
Transportation Facilities

Along with the times, transportation has progressed. Regarding the means of transportation, one of the phenomenon that is easily encountered in everyday life is the queue at public transportation facilities. One of the queues that occurred at public transportation facilities is  the train queue at Semarang Tawang Station. The number of trains that passes the station can cause the train service at the station busy. This study aims to see whether the train service system of Semarang Tawang Station is good or not. This can be consider by the queues method, determining the distribution of arrival patterns and service patterns to obtain a queues system model and a system performance standard. In this study, the distribution of arrival patterns and service patterns are determined by calculating the posterior distribution using the Bayesian method. The bayesian method was chosen because it is able to combine the sample distribution in the current study with the previous information for the same cases. The prior distribution and the likelihood function are the elements needed to obtain the posterior distribution. The distribution of arrival patterns and service patterns obtained from previous information follows the Poisson distribution. Based on the calculation of the posterior distribution, the result shows that the distribution of the arrival pattern is a discrete uniform distribution and the distribution of the service pattern is a Poisson distribution. The result shows that the train service system at Semarang Tawang Station has a model (Uniform Discrete / Gamma / 7: GD / ~ / ~) and has good service based on the performance values obtained.

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

2021 ◽  
Vol 10 (3) ◽  
pp. 413-422
Author(s):  
Nur Azizah ◽  
Sugito Sugito ◽  
Hasbi Yasin
Keyword(s):  
Internal Medicine ◽  
Posterior Distribution ◽  
Prior Distribution ◽  
Bayesian Method ◽  
Likelihood Function ◽  
Queuing System ◽  
Hospital Service ◽  
Queuing Model ◽  
Sample Distribution ◽  
New Information

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. 

scholarly journals PEMODELAN SISTEM ANTREAN PELAYANAN BUS JALUR BARAT TERMINAL TIRTONADI KOTA SURAKARTA DENGAN METODE BAYESIAN

2021 ◽  
Vol 10 (3) ◽  
pp. 466-475
Author(s):  
Nurul Khasanah ◽  
Sugito Sugito ◽  
Yuciana Wilandari
Keyword(s):  
System Performance ◽  
Prior Information ◽  
Bayesian Method ◽  
Service System ◽  
Performance Measure ◽  
The West ◽  
Queue System ◽  
Service Patterns ◽  
Bus Service ◽  
System Performance Measure

Tirtonadi is the largest bus station in Surakarta City. The departure line is devided into two lines, namely west line and east line. The west line serves buses to the west of Surakarta City. The number of buses that enter and leave the station every day causes bus queues. Modeling the queue system and analyzing the system performance measure aims to determine wether the bus service system is good or not. The queue system model is obtained by finding the distribution of arrival patterns and service patterns using the Bayesian method. This method is used because it combines the information from the current research and the prior information from the previous research. The queueing condition of the five lanes in the west line meets steady state conditions because the utility value is less than 1. The queue displant is First Come First Service (FCFS) with unlimited customers and unlimited calling sources. Based on the posterior distribution, the queue system of service bus is (GAMM/IG/1):(GD/∞/∞) for Solo-Jakarta-Bandung lane and Pedesaan lane, while for Solo-Purwokerto-Cilacap, Solo-Yogyakarta, and Solo-Semarang has the queue system (GAMM/GAMM/1):(GD/∞/∞). The queue system of service bus for each lane has good services based on the value of system performance measure. 

scholarly journals ANALISIS METODE BAYESIAN MENGGUNAKAN NON-INFORMATIF PRIOR UNIFORM DISKRIT PADA SISTEM ANTREAN PELAYANAN GERBANG TOL MUKTIHARJO

2021 ◽  
Vol 10 (3) ◽  
pp. 337-345
Author(s):  
Dini Febriani ◽  
Sugito Sugito ◽  
Alan Prahutama
Keyword(s):  
System Performance ◽  
Prior Distribution ◽  
Bayesian Method ◽  
Negative Binomial ◽  
Service System ◽  
Likelihood Function ◽  
System Model ◽  
Large Cities ◽  
The Road ◽  
On The Road

The growth rate of the traffic that is high resulting in congestion on the road network system. One of the government's efforts in addressing the issue with the build highways to reduce congestion, especially in large cities. One of the queuing phenomena that often occurs in the city of Semarang is the queue at the Toll Gate Muktiharjo, that the queue of vehicles coming to make toll payment. This study aims to determine how the service system at the Toll Gate Muktiharjo. This can be known by getting a queue system model and a measure of system performance from the distribution of arrival and service. The distribution of arrival and service are determined by finding the posterior distribution using the Bayesian method. The bayesian method combine the likelihood function of the sample and the prior distribution. The likelihood function is a negative binomial. The prior distribution used a uniform discrete. Based on the calculations and analysis, it can be concluded that the queueing system model at the Toll Gate Muktiharjo is a (Beta/Beta/5):(GD/∞/∞). The queue simulation obtained that the service system Toll Gate Muktiharjo is optimal based on the size of the system performance because busy probability is higher than jobless probability.  

Penataan Terminal Tipe B Kabupaten Sukabumi

2020 ◽  
Vol 4 (1) ◽  
pp. 27-42
Author(s):  
Wiyoga Triharto ◽  
Bambang Perkasa Alam
Keyword(s):  
Public Transportation ◽  
Design Concept ◽  
Tourist Attraction ◽  
Regional Government ◽  
Type B ◽  
Field Surveys ◽  
Future Needs ◽  
Terminal Design ◽  
Transportation Facilities ◽  
Descriptive Qualitative

Ratu harbor beach is one of the mainstay tourist sites for the Regional Government of Sukabumi Regency in bringing PAD, besides public transportation facilities and terminals have a major role in supporting the queen port as a tourist attraction so that tourists are comfortable and facilitated in accessing through public transportation. The condition of the Pelabuhan Ratu Terminal, Sukabumi Regency is currently very poor, poorly maintained, and many supporting facilities are damaged and inadequate. This study aims to identify problems and formulate the type B terminal arrangement in Sukabumi Regency. The method used is descriptive qualitative in order to get a picture of the problems of the situation and conditions currently taking place or occurring in the present and the study of policies. Collecting data by field surveys, literature studies and interviews. The results in this study get a terminal B type terminal design concept Sukabumi Regency according to current and future needs.

scholarly journals On Bayesian procedure for maximum earthquake magnitude estimation

2012 ◽  
Vol 2 (1) ◽  
pp. 7 ◽  
Author(s):  
Andrzej Kijko
Keyword(s):  
Maximum Likelihood ◽  
Posterior Distribution ◽  
Ad Hoc ◽  
Likelihood Function ◽  
Fundamental Problem ◽  
Likelihood Estimation ◽  
Earthquake Magnitude ◽  
Bayesian Estimator ◽  
Bayesian Procedure ◽  
Posterior Estimate

This work is focused on the Bayesian procedure for the estimation of the regional maximum possible earthquake magnitude <em>m</em><sub>max</sub>. The paper briefly discusses the currently used Bayesian procedure for m<sub>max</sub>, as developed by Cornell, and a statistically justifiable alternative approach is suggested. The fundamental problem in the application of the current Bayesian formalism for <em>m</em><sub>max</sub> estimation is that one of the components of the posterior distribution is the sample likelihood function, for which the range of observations (earthquake magnitudes) depends on the unknown parameter <em>m</em><sub>max</sub>. This dependence violates the property of regularity of the maximum likelihood function. The resulting likelihood function, therefore, reaches its maximum at the maximum observed earthquake magnitude <em>m</em><sup>obs</sup><sub>max</sub> and not at the required maximum <em>possible</em> magnitude <em>m</em><sub>max</sub>. Since the sample likelihood function is a key component of the posterior distribution, the posterior estimate of <em>m^</em><sub>max</sub> is biased. The degree of the bias and its sign depend on the applied Bayesian estimator, the quantity of information provided by the prior distribution, and the sample likelihood function. It has been shown that if the maximum posterior estimate is used, the bias is negative and the resulting underestimation of <em>m</em><sub>max</sub> can be as big as 0.5 units of magnitude. This study explores only the maximum posterior estimate of <em>m</em><sub>max</sub>, which is conceptionally close to the classic maximum likelihood estimation. However, conclusions regarding the shortfall of the current Bayesian procedure are applicable to all Bayesian estimators, <em>e.g.</em> posterior mean and posterior median. A simple, <em>ad hoc</em> solution of this non-regular maximum likelihood problem is also presented.

scholarly journals RESOURCE SUPPLY AN ACCESSIBILITY OF PUBLIC TRANSPORTATION FACILITIES

YMER Digital ◽  
2021 ◽  
Vol 20 (12) ◽  
pp. 446-455
Author(s):  
Eshetu Mathewos Juta ◽  
Keyword(s):  
Public Transportation ◽  
Lessons Learned ◽  
Assessment System ◽  
Behavioral Changes ◽  
Public And Private ◽  
The Public ◽  
Urban Mass Transit ◽  
Transportation Accessibility ◽  
Private Actors ◽  
Transportation Facilities

The term “urban mass transit” generally refers to scheduled intra-city service on a fixed route in shared vehicles. Public transportation is an important contributing factor to urban sustainability. Effective transportation networks that incorporate public transit livable by easing commute and transportation needs and increasing accessibility. To assess public transportation accessibility in metropolitan networks, two indices are used: the supply level of urban public transportation facilities resource and the public transportation-private automobile traveling time ratio. As the research in the Wolaita sodo town region and the assessment system, an evaluation technique for urban public transportation facility resource supply is developed based on accessibility. Accessibility is a representative indicator for evaluating the supply of bus system. Traditional studies have evaluated the accessibility from different aspects. Considering the interaction among land use, bus timetable arrangement and individual factors, a more holistic accessibility measurement is proposed to combine static and dynamic characteristics from multisource traffic data. The objective is to highlight the main lessons learned and identify knowledge gaps to guide the design and evaluation of future transport investments. Moreover, studies looking at ways to improve the operational efficiency of systems and those seeking to promote behavioral changes in transport users offer great potential to generate learning that is useful for the public and private actors involved.

scholarly journals ANALISIS BIAYA OPERASIONAL KENDARAAN (BOK) DAN WTP (WILLINGNESS TO PAY) PADA BUS AKAP JURUSAN BANJARMASIN - SAMARINDA

2018 ◽  
Vol 1 (2) ◽  
pp. 115
Author(s):  
Bagus Nugroho Putra ◽  
Utami Sylvia Lestari
Keyword(s):  
Willingness To Pay ◽  
Public Transportation ◽  
Operating Costs ◽  
Bus Drivers ◽  
The Public ◽  
Passenger Transportation ◽  
The Pacific ◽  
Wide Range ◽  
Transportation Facilities

Kota Banjarmasin adalah ibu kota provinsi dari Kalimantan Selatan dengan berbagai macam aktivitas. Salah satu angkutan umum Kota Banjarmasin adalah bus AKAP (Antar Kota Antar Provinsi) PO. Pulau Indah Jaya yang melayani transportasi penumpang dengan tujuan kota dan provinsi. Sarana transportasi memiliki tarif biaya yang ditentukan berdasarkan Biaya Operasional Kendaraan (BOK). Tujuan penelitian ini untuk mengetahui besar BOK bus AKAP dengan metode Pacific Consultant International (PCI) dan untuk mengetahui besar tarif yang diinginkan penumpang beserta tanggapan terhadap tarif yang berlaku saat ini Willingness To Pay (WTP).Penelitian ini dilakukan melalui survei wawancara untuk BOK kepada pihak PO. dan sopir bus dengan jumlah data 25 unit bus dan untuk WTP survei wawancara dengan sampel 200 penumpang bus di terminal KM 6 tempat pembelian tiket bus.Besar BOK yang dikeluarkan oleh PO. Pulau Indah Jaya Rp Rp 8.137.912.279 /tahun (bus Non AC) dengan tarif Rp 168.194 /penumpang dan Rp 8.712.239.580 /tahun (bus AC+Toilet) dengan tarif Rp 229.173 /penumpang. Besar nilai WTP bus Non AC Rp 185.000 /penumpang dan AC+Toilet Rp 245.000 /penumpang. Tanggapan terhadap tarif bus AKAP Non AC Rp 175.000 /penumpang dan AC+Toilet Rp 235.000 /penumpang adalah harga tarif bus  sesuai dengan kemampuan penumpang membayar dan mau membayar lebih dengan syarat adanya penambahan pelayanan dan fasilitas.Kata Kunci: Bus AKAP, Biaya Operasional Kendaraan (BOK), Willingness To Pay (WTP)banjarmasin city is the capital of the province of South Borneo with a wide range of activities. One of the public transportation of Banjarmasin city is the bus AKAP (Inter-City Inter Province) PO. Pulau Indah Jaya which serves passenger transportation with a city and provincial destinations. Transportation facilities have a fee that is determined based on Vehicle Operating Costs (VOC). The purpose of this study is to find out the size of the bus AKAP VOC with the Pacific Consultant International (PCI) method and to find out the number of tariffs desired by passengers along with responses to the current rates of Willingness To Pay (WTP).This research was conducted through interview surveys for VOC to PO. parties and bus drivers with data on 25 bus units and for WTP interview surveys with a sample of 200 bus passengers at the terminal KM 6 places to buy bus tickets.VOC amount issued by PO. Pulau Indah Jaya Rp. 8.137.912.279 /year (Non AC buses) with a tariff of Rp 168.194 /passenger and Rp. 8.712.239.580 /year (AC + Toilet bus) at a rate of Rp. 229.173 /passenger. The value of the Non AC WTP bus is Rp. 185.000 /passenger and the AC + Toilet Rp. 245.000 /passenger. The response to the AKAP Non AC bus fare of Rp. 175.000 /passenger and AC + Toilet Rp. 235.000 /passenger is the price of the bus fare according to the ability of the passengers to pay and pay more on the condition of additional services and facilities.Keywords: Bus AKAP, Vehicle Operating Costs (VOC), willingness to pay (WTP) 

Metropolis-Hastings Algorithms for DSGE Models

2015 ◽  
Author(s):  
Edward P. Herbst ◽  
Frank Schorfheide
Keyword(s):  
Random Walk ◽  
Posterior Distribution ◽  
Prior Distribution ◽  
Large Scale ◽  
Likelihood Function ◽  
Dsge Models ◽  
Posterior Distributions ◽  
Dsge Model ◽  
Alternative Proposal ◽  
Posterior Moments

This chapter talks about the most widely used method to generate draws from posterior distributions of a DSGE model: the random walk MH (RWMH) algorithm. The DSGE model likelihood function in combination with the prior distribution leads to a posterior distribution that has a fairly regular elliptical shape. In turn, the draws from a simple RWMH algorithm can be used to obtain an accurate numerical approximation of posterior moments. However, in many other applications, particularly those involving medium- and large-scale DSGE models, the posterior distributions could be very non-elliptical. Irregularly shaped posterior distributions are often caused by identification problems or misspecification. In lieu of the difficulties caused by irregularly shaped posterior surfaces, the chapter reviews various alternative MH samplers, which use alternative proposal distributions.

scholarly journals The Bühlmann–Straub Estimation of Claim Means in Random B-F Reserve Model

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Zhang Yi ◽  
Wen Limin ◽  
Li Zhilong
Keyword(s):  
Prior Distribution ◽  
Personal Experience ◽  
Bayesian Method ◽  
Historical Data ◽  
Credibility Theory ◽  
Empirical Bayesian ◽  
Sample Distribution ◽  
Empirical Bayesian Method ◽  
Chain Ladder ◽  
Bayesian Estimators

In the B-F reserve model, it is a very critical step to estimate the claim means of the accident year. However, the traditional method uses the prior estimators of the claim means based on the personal experience of actuaries or historical data. This method inevitably carries the subjectivity of the actuary himself. In this paper, a stochastic B-F model is established, and a prior distribution is constructed for the claim means in the accident year. The idea of the credibility theory is used to derive the linear Bayesian estimators of claim means. Finally, the empirical Bayesian method is used to estimate the first two moments of the prior distribution, and the empirical Bayesian estimators of the claim means and the corresponding reserves are derived. The estimators obtained in this paper do not depend on the specific forms of the sample distribution and the prior distribution and can be used directly in practice. In the numerical simulation, our estimates are compared with the traditional B-F estimates and the chain ladder estimates. It is verified that the estimates given in this paper have small mean square error.

Systems Planning for Capital Asset Management: Case Study of New Jersey Public Transportation Facilities and Equipment Management System

1997 ◽  
Vol 1604 (1) ◽  
pp. 109-117
Author(s):  
Ann Ludwig
Keyword(s):  
New Jersey ◽  
Asset Management ◽  
Public Transportation ◽  
Management System ◽  
Lessons Learned ◽  
Fiscal Year ◽  
Problem Analysis ◽  
Team Approach ◽  
Equipment Management ◽  
Transportation Facilities

The Public Transportation Facilities and Equipment Management System (PTMS) is a capital programming tool developed for NJ TRANSIT. It was one of six management systems formerly mandated by the Intermodal Surface Transportation Efficiency Act of 1991 (ISTEA) to manage transportation infrastructure. PTMS organizes pertinent information of physical assets (condition, performance, financial, functional, and descriptive) to assist decision makers; select cost-effective programs and projects; improve efficiency, serviceability, and safety of the infrastructure of NJ TRANSIT; and protect prior federal investments. Implementation of PTMS is now a voluntary program under the ISTEA. However, NJ TRANSIT remains committed to completion of the New Jersey PTMS. A team approach was used (design working group) to identify the specifications for the PTMS. The team participated in all phases of project development and implementation. The system is being tested with the introduction of the fiscal year 1998 capital program cycle. A problem analysis relating to the design and development of the New Jersey PTMS is presented. It is designed to show key issues, accomplishments compared with original objectives, output from the system, and lessons learned.

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