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Rizky Restiana
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IMPLEMENTATION OF MONTE CARLO SIMULATIONS ON THE FINANCIAL RISKS OF CANTEEN AND MUSHOLA CONSTRUCTION PROJECTS Rizky Restiana
Khazanah: Jurnal Mahasiswa Vol. 13 No. 4 (2021): Abstract Proceeding Book: 2st International Conference-Labma Scientific Fair
Publisher : Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/khazanah.vol13.iss4.art24

Abstract

In construction projects definitely require a large cost in the construction process so that the cost estimation stage is needed first. In the cost estimation stage, uncertainty and impending risks are usually not involved. Risk and uncertainty are unavoidable important factors in project financing. To determine the risks and uncertainties required measurements using the Monte Carlo simulation method. Monte Carlo is often used to model and analyze systems to get the best project cost estimates. This research aims to determine the maximum and minimum value of the project based on the unit price of the unit. With the unit price, you can find out the probability of project success in accordance with the cost in the project cost budget, the results of cost estimates, and the percentage of cost comparison that will be experienced by the project with the Monte Carlo simulation method using Microsoft Excel. In this study, an analysis was conducted on the minimum unit price and maximum unit price with each unit price that has been determined in accordance with the project cost budget. The result of conducting a simulation is a probability distribution that is more realistic than the estimated cost value. The results of the study obtained a minimum value of Rp. 357,000,000.00 and a maximum value of Rp. 389,000,000.00 by using Cumulative Distribution Function (CDF) graph, as for determining the percentage probability of using the Probability Density Function (PDF) graph with a success rate of cost conformity in the project cost budget of 100%. The project can achieve a success of 74.31% at a cost of Rp. 377,000,000.00. Keywords: Monte Carlo, Simulation, Financial Risk, Cost Estimation
FLEXSIM MODELING AND SIMULATION TO OPTIMIZE THE OBSTETRICIC POLYCLINIC QUEUE SYSTEM AND OBSTETRIC DISEASES AT DR. SARDJITO HOSPITAL YOGYAKARTA, INDONESIA Rizky Restiana
Khazanah: Jurnal Mahasiswa Vol. 13 No. 4 (2021): Abstract Proceeding Book: 2st International Conference-Labma Scientific Fair
Publisher : Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/khazanah.vol13.iss4.art25

Abstract

There are several factors in assessing the quality of a hospital, namely the level of expertise of doctors owned, quality supporting facilities and infrastructure, and the queuing system implemented by the hospital. If the arrival rate and level of service provided to the patient are not balanced it will cause initiation for the patient and a loss to the hospital because the patient tends to switch to a hospital that has a more optimal level of service. In this study, the method used is a simulation method using flexsim software. The data were obtained using primary data that has been observed directly on the outpatient service queue system of dr. Sardjito Hospital. From the data searched for data distribution using flexsim feature, experfit. During the time the simulation was run found obstacles in the polyclinic queue of obstetrics and obstetric diseases which is in accordance with direct blame. It is known that the average waiting time of the polyclinic queue is for 3.5 hours which is classified as very long and the utilization of doctors works by 44.65%. So there need to be improvements in the form of alternative models in the queue, namely by increasing the number of rooms and doctors who work with as many as 2 and 3 units. From the results of a significant average waiting time from the initial model change with the alternative model, which is as much as 3 units for 2.6 hours with a ratio of 0.9 hours that became the chosen alternative. Based on the research can help the hospital in providing queue services in the queue of obstetric polyclinics and obstetric diseases to patients and the doctor's working time is more optimal and does not exceed the ability of the doctor's work. Keywords: Discrete Event Simulation, Flexsim, Queue
FUEL OPTIMIZATION ON FURNACE DEBUTANIZER REBOILER USING SYSTEM DYNAMICS MODELLING METHOD Rizky Restiana
Khazanah: Jurnal Mahasiswa Vol. 13 No. 4 (2021): Abstract Proceeding Book: 2st International Conference-Labma Scientific Fair
Publisher : Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/khazanah.vol13.iss4.art27

Abstract

The process of processing crude oil requires a furnace that serves as a "cooking" crude oil to a set temperature point which will then be processed further with other devices. The heating process by furnaces needs to be considered four variables, namely temperature, pressure, flow, and fluid level. To support these variables, parameters are needed that support in fulfilling the crude oil heating process. Inefficient operation of furnaces becomes the most important thing in the use of large energy. Increased efficiency is the best option so that energy use can be minimized. This research aims to find out the optimization of furnace debutanizer reboiler by using system dynamics method. The data needed in the study are supporting parameters such as excess water, fuel flow, fuel pressure, fuel temperature, and fuel gas temperature. The data is known to be related to each other and reciprocity by using the help of causal loop diagrams. If the concept has been in accordance with the causal loop diagram that has been created then perform the implementation on the flow diagram. To run simulations with system dynamics methods, equation mathematics is required. The output of the system dynamics simulation is a graph to perform the analysis. The results of this study found that fuel needs increase by 500 kg for one month. The increase was caused by excess water levels reaching 1.5%. While excess water is caused by the loss of oxygen levels in the furnace during the heating process by 0.33%. Therefore, the percentage of furnace optimization does not reach the maximum limit of 87.35%. In order for furnace optimization to be within the optimum limit, there needs to be a hold of oxygen levels in the furnace. By holding oxygen levels, the temperature in the furnace is stable. Keywords: System Dynamics, Simulation, Optimization
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