Modeling simulation application Monte Carlo method for LPG distribution

The purpose of writing this journal is to create a model and simulation of the distribution of LPG (Liquefied Petroleum Gas) Gas Stock Availability that can meet the needs of Pertamina, agents and bases and existing community elements. The design of this application uses the PHP programming language (Personal Home Page) with a database using My SQL [1]. The method used in the design is Monte Carlo [2], and the test method used is the Black box and Questionnaire methods. Monitoring System for Gas Stock Availability Distribution This Liquefied Petroleum Gas (LPG) tube in Makassar presented report printing criteria. In the form of distribution monitoring report, in the form of proof of purchase transactions of LPG (Liquefied Petroleum Gas) Gas to Pertamina agents and bases in real-time per day, month and year Monitoring System Availability Stock Distribution This LPG (Liquefied Petroleum Gas) Gas Tube in Makassar will also be able to control the LPG (Liquefied Petroleum Gas) stock in each existing agent and base in the form of several a stroke on the monitoring map [3].


Introduction
The increasing need for LPG (Liquefied Petroleum Gas) and evenly distributed throughout the region in Indonesia is very influential given the possibility of a surge in the need for LPG (Liquefied Petroleum Gas). The number of requests for LPG (Liquefied Petroleum Gas) in each agent until the assessment is also considered being increasing, to determine the amount of incoming and outgoing LPG (Liquefied Petroleum Gas) stock data information that can be taken as a reference.
Based on the data got through the survey method in the form of interviews with questionnaires and secondary data collection from relevant agencies [2]. The researchers concluded that the need to provide a simulation model that can determine the amount of demand for LPG (Liquefied Petroleum Gas) that occurs every day Pertamina, agents, bases by the community.
This design uses the PHP programming language (Personal Home Page) with a database using My SQL. The aim of research and design is to provide information on the demand for LPG (Liquefied Petroleum Gas) stocks needed every day/week, and month

Data source
The data used in this study are LPG (Liquefied Petroleum Gas) documents got from PT. PERTAMINA PERSERO Makassar and the results of interviews in the field with the handling of LPG (Liquefied Petroleum Gas) from Pertamina and parties from several LPG (Liquefied Petroleum Gas) agents in Makassar. Secondary data is in the form of searching as much literature as possible, both from books, the internet and journal references or related research reports and other sources considered supporting research. Use of the Monte Carlo method

Design research
Research this is a research experimental Where room scope problem could do with method studies library (library research), method field data collection (field research) and design system. In the research, design carried out the researcher used Application Monte Carlo method in modeling simulations carried out guna get results calculations later made into information.

Monte carlo simulation
Research this is a research experimental Where room scope problem could do with method studies library (library research), method field data collection (field research) and design system. In the research, design carried out the researcher used Application Monte Carlo method in modeling simulations carried out guna get results calculations later made into information.

Simulation demand annual
There are 2 stages in request data simulation. First do is simulation magnitude request (order received = volume per each order). Next, it is done simulation date the arrival request. For simulation, the mount request, done with Monte Carlo simulation. For the simulation date, the arrival request, done with formula distribution exponential.

Volume simulation of each order
Monte Carlo simulation techniques are applied for do estimation (forecasting) of order orders received. Results from request data analysis for one year ( 2018 ) shows that pattern demands not erratic. it showed by the results testing (goodness-of-fittest) using SPSS which concludes not there is distribution theoretical that is right to describe pattern request. because of its compiled distribution empirical demand shows a pattern, as in Table 2.
Hackl hose class that is then compiled a Monte Carlo simulation model with pattern distribution empirical, like shown in Table 2. The simulation process was carried out with Microsoft Excel Software because of its ease of aspect in programming mathematical models. In addition, Excel MIS also has a function to generate random numbers to facilitate the simulation process. To obtain results that converge to a stable parameter value, the simulation is carried out several times run (run). One of the simulation outputs, as shown in Table 3. Rata-rata 40.5 The Monte Carlo simulation technique as described previously can be produced an estimate of the volume of each order and the time interval between (arrival) orders. Further analysis, can be made an estimate of the volume of product demand for one year.

Conclusion
From the results research this could conclude, among other conditions probabilistic management te distribution retama determined by the order, the size of the order, time Wait order is of a natureun controllable; For resolving a The use of technique simulation for describing situation probabilistic in a period long proven enough effective.