scholarly journals Optimalisasi Prediksi Biaya Komisi Penjualan Mobil Menggunakan Metode Monte Carlo

KOMTEKINFO ◽  
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.

scholarly journals Simulasi Monte Carlo dalam Prediksi Tingkat Penjualan Produk HPAI

2020 ◽  
pp. 86-91
Author(s):  
Rahmatia Wulan Dari ◽  
Sarjon Defit ◽  
Gunadi Widi Nurcahyo
Keyword(s):  
Decision Making ◽  
Monte Carlo ◽  
Monte Carlo Method ◽  
Business Strategy ◽  
Decision Making Process ◽  
Sales Data ◽  
The Monte Carlo Method ◽  
Average Accuracy ◽  
Sales Prediction ◽  
Product Sales

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.

scholarly journals Prediksi Pajak Mineral Non Logam dan Batuan dengan Metode Monte Carlo

2019 ◽  
pp. 32-37
Author(s):  
Julius Santony
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Regional Government ◽  
Test Results ◽  
Accuracy Rate ◽  
Work Plan ◽  
Tax Revenues ◽  
Average Accuracy ◽  
District Government

Regional government in Indonesia annually sets a target for tax revenues of non-metallic minerals and rocks. Setting targets is very important as a guideline in preparing the current year's budget work plan. So far, the target of non-metal mineral and rock tax revenues has been prepared based on a joint agreement between the regional government and the regional legislature. The prediction of non-metal mineral and rock tax revenues using Monte Carlo simulation can be a solution to predict the next few years. This prediction uses data between 2009 - 2018 taken from the tax and retribution management body one of the districts in Indonesia. Testing the results of predictions is done by comparing the results of predictions with data from 2016 - 2018. The test results show that the average accuracy rate reaches 82.05%. So this study greatly helped the district government in setting the target for the acceptance of non-metal minerals and rock taxes.

Organizational Policy Learning and Evaluation Using Monte Carlo Methods

2021 ◽  
pp. 195-208
Author(s):  
Clement Leung ◽  
Nikki Lijing Kuang ◽  
Vienne W. K. Sung
Keyword(s):  
Decision Making ◽  
Monte Carlo ◽  
Reinforcement Learning ◽  
Learning Strategies ◽  
Policy Evaluation ◽  
Stopping Rules ◽  
Policy Learning ◽  
Sequential Trials ◽  
The Cost ◽  
New Strategies

Organizations need to constantly learn, develop, and evaluate new strategies and policies for their effective operation. Unsupervised reinforcement learning is becoming a highly useful tool, since rewards and punishments in different forms are pervasive and present in a wide variety of decision-making scenarios. By observing the outcome of a sufficient number of repeated trials, one would gradually learn the value and usefulness of a particular policy or strategy. However, in a given environment, the outcomes resulting from different trials are subject to external chance influence and variations. In learning about the usefulness of a given policy, significant costs are involved in systematically undertaking the sequential trials; therefore, in most learning episodes, one would wish to keep the cost within bounds by adopting learning efficient stopping rules. In this Chapter, we explain the deployment of different learning strategies in given environments for reinforcement learning policy evaluation and review, and we present suggestions for their practical use and applications.

Sasta Bhojan Sewa: the pricing dilemma

2021 ◽  
Vol 11 (1) ◽  
pp. 1-17
Author(s):  
Harsimar Kaur ◽  
Gopalakrishnan Narayanamurthy
Keyword(s):  
Decision Making ◽  
Social Enterprises ◽  
Poor People ◽  
Selling Price ◽  
Opportunity Identification ◽  
Content Type ◽  
For Profit ◽  
Not For Profit ◽  
Social Venture ◽  
The Cost

Learning outcomes After studying this case, students should be able to: understand the process of opportunity identification for forming social enterprises (knowledge), discuss various concepts related to social entrepreneurship and not-for-profit firms (comprehension), apply tools to differentiate between social and commercial enterprises (application), analyze the role of environmental factors like culture in influencing business (analysis) and develop decision-making skills by critically evaluating the options (evaluation). Case overview/synopsis Sasta Bhojan Sewa (SBS) was one of the key projects of Parupkar Sewa Society. The social venture initiated by Jaswinder Singh, a young resident of Ambala (a small town in Haryana, India), got registered as a not-for-profit society in the year 2018. Mr. Singh initiated various social welfare projects since the year 2006 when he got inspired from the history of Sikh Gurus. As years passed, he was able to employ more and more people. This led to the development of a social venture, which had 33 employees at the end of the year 2019. The society was running seven major projects with the help of dasvandh (donations). Project SBS was about providing home-like hygienic meals to people at merely INR10. There were 11 canteens in Ambala city and cantonment, which were being run under that project. Around 1,500 people were eating daily in those canteens, out of which around 70–80 people were not able to pay even INR10. The project had employed 30 people. The salaries of the staff and other operating expenses like liquid petroleum gas (LPG) expense, transportation cost and electricity were met through dasvandh (donations) from the local households. When the project was initiated, the cost of preparing a meal was INR10, but by the end of 2019, the cost went up to INR12 per meal due to food inflation. The meal was still being sold at INR10 at a loss of INR2 per meal. On December 28, 2019, as founder of the society, Mr. Singh was thinking of raising the selling price to INR12 per meal, which had to be implemented on January 01, 2020 but he was doubtful in doing so. He thought increasing the price might defeat the purpose of starting SBS as he was reflecting on how poor people were and how each rupee mattered to them. He was also considering that it might affect the goodwill of the society that was known for selling food at an extremely low price. By using the example of SBS, we explain various concepts of not-for-profit social enterprises like opportunity identification, key drivers, business model canvas and environmental effects in this teaching note. The teaching note also provides cost–benefit analysis of the available options to facilitate effective decision-making. Complexity academic level Undergraduate and graduate-level business programs. Supplementary materials Teaching notes are available for educators only. Subject code CSS 3: Entrepreneurship.

scholarly journals Prediksi Pajak Mineral Non Logam dan Batuan dengan Metode Monte Carlo

2019 ◽  
pp. 32-37
Author(s):  
Julius Santony
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Regional Government ◽  
Test Results ◽  
Accuracy Rate ◽  
Work Plan ◽  
Tax Revenues ◽  
Average Accuracy ◽  
District Government

Regional government in Indonesia annually sets a target for tax revenues of non-metallic minerals and rocks. Setting targets is very important as a guideline in preparing the current year's budget work plan. So far, the target of non-metal mineral and rock tax revenues has been prepared based on a joint agreement between the regional government and the regional legislature. The prediction of non-metal mineral and rock tax revenues using Monte Carlo simulation can be a solution to predict the next few years. This prediction uses data between 2009 - 2018 taken from the tax and retribution management body one of the districts in Indonesia. Testing the results of predictions is done by comparing the results of predictions with data from 2016 - 2018. The test results show that the average accuracy rate reaches 82.05%. So this study greatly helped the district government in setting the target for the acceptance of non-metal minerals and rock taxes.

Emotional Choices

2018 ◽  
Author(s):  
Robin Markwica
Keyword(s):  
Decision Making ◽  
Choice Behavior ◽  
Choice Theory ◽  
Cuban Missile Crisis ◽  
Coercive Diplomacy ◽  
The Core ◽  
Present Book ◽  
Action Model ◽  
The Cost ◽  
Dynamic Interplay

In coercive diplomacy, states threaten military action to persuade opponents to change their behavior. The goal is to achieve a target’s compliance without incurring the cost in blood and treasure of military intervention. Coercers typically employ this strategy toward weaker actors, but targets often refuse to submit and the parties enter into war. To explain these puzzling failures of coercive diplomacy, existing accounts generally refer to coercers’ perceived lack of resolve or targets’ social norms and identities. What these approaches either neglect or do not examine systematically is the role that emotions play in these encounters. The present book contends that target leaders’ affective experience can shape their decision-making in significant ways. Drawing on research in psychology and sociology, the study introduces an additional, emotion-based action model besides the traditional logics of consequences and appropriateness. This logic of affect, or emotional choice theory, posits that target leaders’ choice behavior is influenced by the dynamic interplay between their norms, identities, and five key emotions, namely fear, anger, hope, pride, and humiliation. The core of the action model consists of a series of propositions that specify the emotional conditions under which target leaders are likely to accept or reject a coercer’s demands. The book applies the logic of affect to Nikita Khrushchev’s decision-making during the Cuban missile crisis in 1962 and Saddam Hussein’s choice behavior in the Gulf conflict in 1990–91, offering a novel explanation for why coercive diplomacy succeeded in one case but not in the other.

scholarly journals Economic Value of Terminal Aerodrome Forecasts at Incheon Airport, South Korea

2021 ◽  
Vol 13 (12) ◽  
pp. 6965
Author(s):  
In-Gyum Kim ◽  
Hye-Min Kim ◽  
Dae-Geun Lee ◽  
Byunghwan Lim ◽  
Hee-Choon Lee
Keyword(s):  
Decision Making ◽  
South Korea ◽  
Co2 Emissions ◽  
Fuel Efficiency ◽  
Economic Value ◽  
Analysis Data ◽  
Annual Average ◽  
Loss Model ◽  
Total Budget ◽  
The Cost

Meteorological information at an arrival airport is one of the primary variables used to determine refueling of discretionary fuel. This study evaluated the economic value of terminal aerodrome forecasts (TAF), which has not been previously quantitatively analyzed in Korea. The analysis data included 374,716 international flights that arrived at Incheon airport during 2017–2019. A cost–loss model was used for the analysis, which is a methodology to evaluate forecast value by considering the cost and loss that users can expect, considering the decision-making result based on forecast utilization. The value was divided in terms of improving fuel efficiency and reducing CO2 emissions. The results of the analysis indicate that the annual average TAF value for Incheon Airport was approximately 2.2 M–20.1 M USD under two hypothetical rules of refueling of discretionary fuel. This value is up to 26.2% higher than the total budget of 16.3 M USD set for the production of aviation meteorological forecasts by the Korea Meteorological Administration (KMA). Further, it is up to 10 times greater than the 2 M USD spent on aviation meteorological information fees collected by the KMA in 2018.

scholarly journals The Analysis of Small Investors’ Demands on a Thermal Insulation System for a Family House: A Case Study

2021 ◽  
Vol 13 (5) ◽  
pp. 2491
Author(s):  
Alena Tažiková ◽  
Zuzana Struková ◽  
Mária Kozlovská
Keyword(s):  
Decision Making ◽  
Thermal Insulation ◽  
Construction Cost ◽  
Environmental Cost ◽  
Multi Criteria Decision Making ◽  
Insulation System ◽  
Insulation Systems ◽  
Small Investors ◽  
The Cost ◽  
Family House

This study deals with small investors’ demands on thermal insulation systems when choosing the most suitable solution for a family house. By 2050, seventy percent of current buildings, including residential buildings, are still expected to be in operation. To reach carbon neutrality, it is necessary to reduce operational energy consumption and thus reduce the related cost of building operations and the cost of the life cycle of buildings. One solution is to adapt envelopes of buildings by proper insulation solutions. To choose an optimal thermal insulation system that will reduce energy consumption of building, it is necessary to consider the environmental cost of insulation materials in addition to the construction cost of the materials. The environmental cost of a material depends on the carbon footprint from the initial origin of the material. This study presents the results of a multi-criteria decision-making analysis, where five different contractors set the evaluation criteria for selection of the optimal thermal insulation system. In their decision-making, they involved the requirements of small investors. The most common requirements were selected: the construction cost, the construction time (represented by the total man-hours), the thermal conductivity coefficient, the diffusion resistance factor, and the reaction to fire. The confidences of the criteria were then determined with the help of the pairwise comparison method. This was followed by multi-criteria decision-making using the method of index coefficients, also known as the method of basic variant. The multi-criteria decision-making included thermal insulation systems based on polystyrene, mineral wool, thermal insulation plaster, and aerogels’ nanotechnology. As a result, it was concluded that, currently, in Slovakia, small investors emphasize the cost of material and the coefficient of thermal conductivity and they do not care as much about the carbon footprint of the material manufacturing, the importance of which is mentioned in this study.

scholarly journals Application of the theory of decision making under risk and uncertainty at modelling of costs

2010 ◽  
Vol 56 (No. 5) ◽  
pp. 201-208 ◽  
Author(s):  
M. Beranová ◽  
D. Martinovičová
Keyword(s):  
Decision Making ◽  
Financial Accounting ◽  
Cost Functions ◽  
Risk And Uncertainty ◽  
Managerial Decision ◽  
Managerial Decision Making ◽  
Bayesian Theorem ◽  
Long Run ◽  
Short Run ◽  
The Cost

The costs functions are mentioned mostly in the relation to the Break-even Analysis where they are presented in the linear form. But there exist several different types and forms of cost functions. Fist of all, it is necessary to distinguish between the short-run and long-run cost function that are both very important tools of the managerial decision making even if each one is used on a different level of management. Also several methods of estimation of the cost function's parameters are elaborated in the literature. But all these methods are based on the past data taken from the financial accounting while the financial accounting is not able to separate the fixed and variable costs and it is also strongly adjusted to taxation in the many companies. As a tool of the managerial decision making support, the cost functions should provide a vision to the future where many factors of risk and uncertainty influence economic results. Consequently, these random factors should be considered in the construction of cost functions, especially in the long-run. In order to quantify the influences of these risks and uncertainties, the authors submit the application of the Bayesian Theorem.

scholarly journals Uncertainty Cost Functions in Climate-Dependent Controllable Loads in Commercial Environments

Energies ◽  
2021 ◽  
Vol 14 (10) ◽  
pp. 2885
Author(s):  
Daniel Losada ◽  
Ameena Al-Sumaiti ◽  
Sergio Rivera
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Simulation Method ◽  
Electricity Sector ◽  
Cost Functions ◽  
Density Estimator ◽  
Monte Carlo Simulation Method ◽  
Commercial Building ◽  
Complementary Method ◽  
The Cost

This article presents the development, simulation and validation of the uncertainty cost functions for a commercial building with climate-dependent controllable loads, located in Florida, USA. For its development, statistical data on the energy consumption of the building in 2016 were used, along with the deployment of kernel density estimator to characterize its probabilistic behavior. For validation of the uncertainty cost functions, the Monte-Carlo simulation method was used to make comparisons between the analytical results and the results obtained by the method. The cost functions found differential errors of less than 1%, compared to the Monte-Carlo simulation method. With this, there is an analytical approach to the uncertainty costs of the building that can be used in the development of optimal energy dispatches, as well as a complementary method for the probabilistic characterization of the stochastic behavior of agents in the electricity sector.

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