Simulasi Monte Carlo dalam Prediksi Tingkat Penjualan Produk HPAI

Predicting sales is an important aspect of sales development. Sales prediction simulation is an estimate about calculating the level of product sales in a certain period. The research objective was to predict the level of sales of HPAI products at HNI Halal Mart. The data used is sales data for HPAI products from 2017 to 2019 which are processed using the Monte Carlo method. Based on the results of testing the prediction of the sales level of HPAI products, an average accuracy of 84,5% is obtained, making it easier in the decision making process and helping in choosing a good business strategy.

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Simulasi Monte Carlo dalam Memprediksi Tingkat Pendapatan Advertising

Jurnal Informatika Ekonomi Bisnis ◽

10.37034/infeb.vi0.45 ◽

2020 ◽

pp. 80-85

Author(s):

Beni Mulyana Putra ◽

Sarjon Defit ◽

Gunadi Widi Nurcahyo

Keyword(s):

Monte Carlo ◽

Monte Carlo Method ◽

Business Strategy ◽

Business Owners ◽

Business Strategies ◽

Advertising Revenue ◽

The Monte Carlo Method ◽

Average Accuracy ◽

The Right ◽

High Level

Fulfilling consumer needs is the goal of every business. Owned business capital will affect the readiness to serve consumer demand. The purpose of this study is to predict the level of advertising revenue at Vand Advertising Printing in order to facilitate business owners in preparing business strategies quickly and optimally. This research data is income data from January 2017 to December 2019 which is modeled using the Monte Carlo method. Income level prediction will be carried out annually. Based on the results of the tests that have been done, it is found that the system used to predict the level of advertising revenue with an average accuracy of 90%. The high level of accuracy means that the application of the Monte Carlo method is considered able to predict the level of advertising revenue each year. So that it can make it easier for business owners to choose the right business strategy to increase advertising revenue.

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Prediksi Pendapatan Terbesar pada Penjualan Produk Cat dengan Menggunakan Metode Monte Carlo

Jurnal Informatika Ekonomi Bisnis ◽

10.37034/infeb.v1i4.5 ◽

2019 ◽

Vol 1 (4) ◽

pp. 15-20

Author(s):

Bias Yulisa Geni ◽

Julius Santony ◽

Sumijan

Keyword(s):

Monte Carlo ◽

Monte Carlo Method ◽

Business Strategy ◽

Business Strategies ◽

Sales Revenue ◽

Product Demand ◽

The Monte Carlo Method ◽

Paint Product ◽

The Right ◽

Product Sales

Completing cat products in meeting consumer demand is something that must be addressed. Sales are very important for sales. The amount of demand for goods increases, it will get a large income. The purpose of this study is to predict the sales revenue of paint products at UD. Masdi Related, makes it easy for the leadership of the company to find out the amount of money obtained quickly. This research also makes it easy for companies to take business strategies quickly and optimally. The data used in this research is the data of paint product sales for January 2016 to December 2018 which is processed using the Monte carlo method. Income prediction will be done every year. In addition to predicting revenue, the sales data is also used to predict product demand every year. To predict the sales of paint products using the Monte Carlo method. The results of this study can predict sales revenue of paint products very well. Based on the results of tests conducted on the system used to predict sales revenue of cat products with an average rating of 89%. With a fairly high degree of accuracy, the application of the Monte Carlo method can be estimated to make an estimate of the income and demand for each paint product every year. Necessary, will facilitate the leadership to choose the right business strategy to increase sales of cat product sales.

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Optimalisasi Prediksi Biaya Komisi Penjualan Mobil Menggunakan Metode Monte Carlo

KOMTEKINFO ◽

10.35134/komtekinfo.v7i2.74 ◽

2020 ◽

Vol 7 (2) ◽

pp. 140-151

Author(s):

Zupri Henra Hartomi ◽

Yuhandri ◽

Julius Santony

Keyword(s):

Decision Making ◽

Monte Carlo ◽

Accuracy Rate ◽

Sales Data ◽

For Profit ◽

Marketing Performance ◽

Potential Market ◽

Average Accuracy ◽

Car Sales ◽

The Cost

Sales are the main source of income for every company. Every company in marketing a product, should control the potential market for profit. Predicting the number of sales is important in analyzing sales progress. This study aims to assist companies in predicting car sales and car commission cost budgets based on sales data from the previous year.The data used in the study are car sales data for 2017 and 2018 in the Arengka Automall Pekanbaru Showroom (SAA Pekanbaru).Data processing in research uses the Monte Carlo method.The results of tests that have been carried out state that car sales by Marketing within 1 year resulted in an average accuracy rate of 94% and sales commission fee of Rp 411.000.000.From these results in accordance with calculations performed manually so that with a large accuracy value, the application of the simulation using this Monte Carlo Method feasible to be applied by companies in future decision making to plan the estimated budget for the cost of a car sales commission and as a means to assess Marketing performance at SAA Pekanbaru.

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Akurasi dalam Memprediksi Penetapan Besaran Anggaran Proposal Pendapatan dan Belanja Universitas Menggunakan Metode Monte Carlo

Jurnal Informatika Ekonomi Bisnis ◽

10.37034/infeb.v2i2.42 ◽

2020 ◽

pp. 60-66

Author(s):

Yogo Turnandes ◽

Yuhandri Yunus

Keyword(s):

Higher Education ◽

Monte Carlo ◽

Monte Carlo Method ◽

Community Service ◽

The Monte Carlo Method ◽

Average Accuracy ◽

Service Activities ◽

High Level ◽

The University

The Institute for Research and Community Service at the University of Lancang Kuning has the mandate in research and service activities which are the two dharmas of the Tri Dharma of Higher Education. The purpose of this study is to predict the determination of the budget amount for the University Income and Expenditure Budget (APBU) proposal approved at LPPM Unilak for the following year. Thus, it will make it easier for the LPPM leadership to make decisions on the acceptance of APBU proposals that are approved quickly and optimally. The data used in this research is APBU research and service proposal data approved in 2018 to 2020 which is processed using the monte carlo method. The APBU proposal budget prediction will be carried out every year. Based on the results of tests that have been carried out with the monte carlo method, it is found that the system used to predict the amount of APBU proposal budget approved in 2019 with an average accuracy of 84% and in 2020 with an average accuracy of 73%. Then with a fairly high level of accuracy, the application of the Monte Carlo method is considered to be able to predict the amount of the APBU proposal budget that is approved by each faculty each year.

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Pemodelan dan Simulasi Monte Carlo dalam Meningkatkan Pendapatan Penjualan Peralatan Motor (Studi Kasus : Bengkel AMI Motor)

Jurnal Informatika Ekonomi Bisnis ◽

10.37034/infeb.v2i4.55 ◽

2020 ◽

Author(s):

Wita Siska Moza ◽

Yuhandri Yunus

Keyword(s):

Monte Carlo ◽

Monte Carlo Method ◽

Business Strategies ◽

Web Based ◽

Sales Revenue ◽

Know How ◽

The Monte Carlo Method ◽

Average Accuracy ◽

Almost All ◽

Web Based System

AMI Motor shop is a various shop that is engaged in sales by selling various motorcycle equipment. Sales transactions vary in stores, but almost all products have increased and decreased, so it is necessary to know how the product data is related to consumer demand. Sales simulation is an estimate that can provide benefits in making decisions to increase sales revenue. The purpose of this study is to predict what motorcycle equipment stock should be increased and decreased in sales in the following year. The data used is motor equipment sales data in 2018 and 2019 which are processed using the Monte Carlo method. In speeding up data processing, this system is applied to a web-based system using the PHP (Hypertext Processor) programming language. Based on the results of testing prediction levels of motorcycle equipment sales, average accuracy is 95,92%, making it easier for company leaders to make decisions on developing business strategies to increase sales revenue.

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Simulasi Monte Carlo dalam Prediksi Jumlah Penumpang Angkutan Massal Bus Rapid Transit Kota Padang

Jurnal Informatika Ekonomi Bisnis ◽

10.37034/infeb.v3i2.72 ◽

2020 ◽

Author(s):

Khaliq Alfikrizal ◽

Sarjon Defit ◽

Yuhandri Yunus

Keyword(s):

Monte Carlo ◽

Monte Carlo Method ◽

Real Data ◽

Bus Rapid Transit ◽

Rapid Transit ◽

High Quality ◽

Simulation Data ◽

The Monte Carlo Method ◽

Average Accuracy ◽

High Level

Bus Rapid Transit is a system of bus facilities, services and comfort which is used to increase speed and reliability and is integrated with a strong transit identity through high quality services. Trans Padang is a land transportation based on Bus Rapid Transit in Padang City which is managed by the Transportation Agency which started operating in January 2014 with a total bus fleet of 10 units on the Lubuk Buaya-Pasar Raya Padang route. Currently it has 2 corridors operating out of 6 corridors designed. This study aims to predict the number of Bus Rapid Transit passengers in Padang City and determine the level of accuracy of simulation data with real data using the Monte Carlo method. The data used to predict the number of passengers is data on the number of passengers from January 2017 to December 2019. From the simulations carried out, simulated accuracy is obtained for predicting the number of passengers with an average accuracy of above 80%. Based on a fairly high level of accuracy, the application of the Monte Carlo method to predict the number of Bus Rapid Transit passengers in Padang City is considered to be able to predict the number of passengers in the following year.

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Optimalisasi Prediksi Penjualan Produk Herbal Menggunakan Metode Monte Carlo dalam Meningkatkan Transaksi (Studi Kasus: Toko Herbal An Nabawi)

Jurnal Informatika Ekonomi Bisnis ◽

10.37034/infeb.v2i4.54 ◽

2020 ◽

Author(s):

Nova Hayati ◽

Sarjon Defit ◽

Gunadi Widi Nurcahyo

Keyword(s):

Monte Carlo ◽

Monte Carlo Method ◽

Accuracy Rate ◽

Herbal Products ◽

Web Based ◽

The Public ◽

Product Availability ◽

The Monte Carlo Method ◽

Sales Prediction ◽

Web Based System

Herbs are a product that is in great demand by the public. With so many enthusiasts of herbal products, there is a need for product availability to increase sales transactions for these products. To increase sales transactions for these products, one process that can be done is to predict the sales of herbal products, with data used from January 2018 to December 2019 at the An Nabawi herbal shop. The prediction process is carried out using the Monte Carlo method and to simplify the prediction process a web-based system with the PHP programming language is implemented to make it easier. With the Monte Carlo method used in this study to predict sales of herbal products so that the leadership can use it to make decisions on the availability of herbal products in the shop. The sales prediction results obtained from the Monte Carlo simulation process with an accuracy rate of 87.91%. In this way, the Monte Carlo method can be applied to predict the future sales of herbal products and can be used by store leaders to make decisions regarding the availability of herbal products.

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Economic analysis of replacement regeneration and coppice regeneration in eucalyptus stands under risk conditions

CERNE ◽

10.1590/s0104-77602011000300014 ◽

2011 ◽

Vol 17 (3) ◽

pp. 393-401 ◽

Cited By ~ 5

Author(s):

Isabel Carolina de Lima Guedes ◽

Luiz Moreira Coelho Júnior ◽

Antônio Donizette de Oliveira ◽

José Márcio de Mello ◽

José Luiz Pereira de Rezende ◽

...

Keyword(s):

Decision Making ◽

Monte Carlo ◽

Monte Carlo Method ◽

Economic Analysis ◽

Net Present Value ◽

Economic Feasibility ◽

Technological Advancement ◽

Charcoal Production ◽

The Monte Carlo Method ◽

Return On Capital

Projects are by their very nature subject to conditions of uncertainty that obstruct the decision-making process. Uncertainties involving forestry projects are even greater, as they are combined with time of return on capital invested, being medium to long term. For successful forest planning, it is necessary to quantify uncertainties by converting them into risks. The decision on whether to adopt replacement regeneration or coppice regeneration in a forest stand is influenced by several factors, which include land availability for new forest crops, changes in project end use, oscillations in demand and technological advancement. This study analyzed the economic feasibility of replacement regeneration and coppice regeneration of eucalyptus stands, under deterministic and under risk conditions. Information was gathered about costs and revenues for charcoal production in order to structure the cash flow used in the economic analysis, adopting the Net Present Value method (VPL). Risk assessment was based on simulations running the Monte Carlo method. Results led to the following conclusions: replacement regeneration is economically viable, even if the future stand has the same productivity as the original stand; coppice regeneration is an economically viable option even if productivity is a mere 70% of the original stand (high-tree planted stand), the best risk-return ratio option is restocking the stand (replacement regeneration) by one that is 20% more productive; the probabilistic analysis running the Monte Carlo method revealed that invariably there is economic viability for the various replacement and coppice regeneration options being studied, minimizing uncertainties and consequently increasing confidence in decision-making.

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Prediksi Optimal dalam Produksi Bata Merah Menggunakan Metode Monte Carlo

Jurnal Informatika Ekonomi Bisnis ◽

10.37034/infeb.v2i1.11 ◽

2020 ◽

Vol 2 (1) ◽

pp. 13-20

Author(s):

Hendro Zalmadani ◽

Julius Santony ◽

Yuhandri Yunus

Keyword(s):

Monte Carlo ◽

Monte Carlo Method ◽

Production Process ◽

Production Cost ◽

Business Owners ◽

Production Data ◽

Sales Revenue ◽

The Monte Carlo Method ◽

Average Accuracy ◽

High Degree

The availability of red bricks on the market is a problem that must be addressed. Because the availability of red brick affects sales revenue. The purpose of this research in the Small and Medium Micro Business of the Red Brick City of Pariaman is to predict the production of red bricks to find out income and find out the next production. So this research can make it easier for business owners to find out how much it will cost for the next production cost. The data used in this study are production data from 2017 to 2019 which are processed using the Monte Carlo method. Based on the results of production prediction testing that has been done, it is found that the average accuracy is 90%. With the results of a high degree of accuracy, the application of the monte carlo method is considered to be able to predict production annually. Making it easier for business owners to determine the costs incurred in the next production process.

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