PI B.INGGRIS

PREDICTION MOTORCYCLE SALES BEAT CW PGM IN. PACIFIC MOTOR IV CIKARANG

SCIENTIFIC WRITING SEMINAR

Asked To Completing Terms To Achieve
Equivalent Bachelor Degree Programs Study Management Strata One
Faculty of Economics, University Gunadarma

Name: Andry Sugianto
NPM: 10212854
Management major
Supervisor: Irfan Ardiansyah, SE, MM

FACULTY OF ECONOMICS

UNIVERSITY GUNADARMA

JAKARTA

2015

TABLE OF CONTENTS
TITLE PAGE i
SHEET STATEMENT OF ORIGINALITY ii
ENDORSEMENT SHEET iii
ABSTRACT iv
INTRODUCTION v
Vi TABLE OF CONTENTS
LIST OF TABLES ix
LIST OF FIGURES x
CHAPTER I INTRODUCTION
1.1 Background 1
1.2 Formulation Problems and Limitations 2
1.2.1 Formulation malasah 2
1.2.2 Limitations 2
1.3 Objective 2
1.4 Benefits of Research 2
1.4.1 Academic Benefits 2
1.4.2 Practical Benefits 2
1.5 Research Methods 3
1.5.1 Research Object 3
1.5.2 Data / Variable 3
1.5.3 Data Collection Methods 3
1.5.4 Analysis tool used 3
CHAPTER II LITERATURE
2.1 Framework Theory 5
Definition 2.1.1 Forecasting 5
2.1.2 Forecasting Objectives 6
Sales Forecasting 2.1.3 Uses 7
Method 2.1.4 - Forecasting methods 7
2.1.5 Type - the type of Forecasting 7
2.1.6 Forecasting Process 9
2.1.7 Stage - step Forecasting 10
2.1.8 Characteristics of a Good Forecasting 12
2.1.9 Techniques To Make Sales Forecast 13
2.1.10 Forecasting Techniques 13
2.2 Assessment Research Similar 15
2.3 Analysis Tool 17
2.3.1 Method MA (Moving Average) 17
2.3.2 Weight Moving Average (An average moving
weighted) 18
2.3.3 Exponential Smoothing (ES) 19
2.3.4 Mean Absolute Devisiasion (MAD) 19
CHAPTER III RESEARCH METHODS
3.1 Research Object 21
3.1.1 A Brief History of the Company 21
3.1.2 Company Organizational Structure and Function 22
3.2 Data / Variables Used 24
3.3 Data Collection Methods 24
3.4 Hypotheses 24
3.5 Analysis Tools Used 24
3.5.1 Method MA (Moving Average) 24
3.5.2 Weight Moving Average (An average moving
weighted) 25
3.5.3 Exponential Smoothing (ES) 26
3.5.4 Mean Absolute Devisiasion (MAD) 26
CHAPTER IV DISCUSSION
4.1 Results and Discussion Analysis 27
4.1.1 Sales Forecasting Method Using
Moving Average Period By Wearing 5 27
Sales Forecasting 4.1.2 by using Method
Weight Moving Average Period 3, where W1 = 0.2,
W2 and W3 = 0.3 = 0.5 30
4.1.3 Sales forecasting by using Method
Exponential Smoothing (ES) = 0.5 32
4.2 Summary of Results 35
CHAPTER V CONCLUSIONS AND SUGGESTIONS
5.1 Conclusion 37
5.2 Suggestions 38
REFERENCES 39
ATTACHMENT

BIBLIOGRAPHY


ABSTRACTION


Andry Sugianto, 10212854
PREDICTION MOTORCYCLE SALES BEAT CW PGM IN. PACIFIC MOTOR IV CIKARANG
PI. Department of Management, Faculty of Economics, University Gunadarma, 2015
Keywords: Forecasting Sales

(X + 39 + Appendix)

In this paper the authors used three methods of sales forecasting, namely moving average (MA) 5 period, Weight Moving Average (WMA) 3 periods and Exponential Smoothing (ES) to determine the PGM Beat motorcycle sales in March 2015 and April 2015. Of the three count the method is known that most good sales forecasts for the months of March 2015 and April 2015 with a method which menghasilakn Weight Moving average forecasting sales in March 2015 as many as 221.4 units Motor Beat, with an error rate of the average - average (MAD) of 25.41 units Motor Beat, so PT.Pacific Motor IV Cikarang predicts sales in March 2015 as much as 195.99 up to 246.81 units Motor Beat. Then in April 2015 amounted to 237.48 units generate penjuaan Motor Beat, with an error rate of the average - average (MAD) of 22.24 units. so PT.Pacific Motor IV Cikarang predicts sales in April 2015 as much as 215.24 up to 259.72 units Motor Beat. So Weight Moving Average method is better than the method used Moving Average (MA) and ExponentialSmoothing (ES)







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