Multidimensional scalling method (Simple definition)

Multidimensional scaling is a multivariate technique that is part of Interdependence techniques that focus on the object.

Multivariate techniques are classified into:
1. Dependence Techniques
The technique consists of one or more variable bound.

2. Interdependence Techniques
Which is a technique that focuses on the analysis of the variables or objects of research.

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Game Theory Classification

Game Theory Method is divided into various types of games, such as :
 

A. Based on the number of steps and choice, which are classified into two types:

1. Finite game, a game that has a finite number of steps with a finite number of options as well.
2. Infinite game, is a every game except for a finite game.

B. Based on the number of players (people).

C. Based on the number of payments. This type consists of:

1. Zero Sum Game is a game with both sides winning amount is equal to zero. This means the amount of payments received for one of the players who win the same as the amount paid by the losing side.
2. Non Zero Sum Game is a game with a total payment of each player at the end of the game is not equal to zero. This game can be played by 2 or "n" people. It's just that until recently was limited to problems with the number 2 player.

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Flexibility of Supply Chain

Flexibility of Supply Chain on the company established by variables as follows :

1. Delivery System, consisting of the delivery, transportation, time of ordering, delivery and coverage.
2. Production System, consisting of quantity orders, raw materials, manufacture and production capacity required.
3. Product Design, based on the velocity product design and material testing, and quality of material force.
4. Supplier System is a system supplier analysis, consisting of raw materials, spare parts, shipping agreements, and lead time period.

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Perfomance Measurement With Fuzzy Method

In the development of performance measurement is not only focused on the internal condition of a process but also oriented toward the interests of customers. Basically the performance measurement can be performed at three levels, namely the process, the level of output and outcome levels. Establishment of performance attributes obtained from the process of customer needs. 

 

How to application the Fuzzy method in performance measurement ? Fuzzy Method is used to find out establishment of the membership function of respondents, determining the performance of process, determining the weight of a critical success factor (csf), determining the impact of process. All data processing results with "fuzzy method" is used as input in process priority matrix.

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How to make a good questionnaire ?

Talk about market research, comparison fields study, or opinion research, base on my experience as market researcher there are main point that most important to do to make optimal results. What is that ? that is a questionnaire form.  

As we know, the weakness of field research are subjective result, so usually to reduce a subjectivity of result, the researcher determine the significance level, how much error level that we will be used in our research. But all that are useless if our questionnaire not representative with the purpose of research. The point is we must make a good questionnaire. How the way to make a good questionnaire ?

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Least Cost Methode Algorithm

Least Cost method algorithm is as follows:

1. Make initial transportation table format.
2. Capacity and demand must be the same. If it is not the same (maybe capacity> demand or perhaps capacity 3. Having prepared the table, we do start charging empty cells starting from cells that have the least cost / least until satisfied (with respect to capacity and demand). Completion is expected early cell filled eligible m + n -1 because if it does not comply then be called degeneration and this case is its own solution.
3. Calculate the Total Cost of transportation early to know whether the total cost has been minimal or not it should be checking the index improvement empty cells. If all the improvement index ≥ 0 then STOP.
4. If there is still improvement index is negative then do the reallocation started from cells that have the largest negative index improvement and then calculate the total cost of transportation.
5. And so on until the value of all the positive index improvement

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Ishikawa diagram (Fhisbone diagram)

Ishikawa diagram or also known as Fhisbone diagram or fish bone diagram is a diagram showing the relationship between Cause and effect (cause and effect). The beginning is named by Prof. Ishikawa diagram. Kaoru Ishikawa of Tokyo University in 1953, because the shape is like a fishbone diagram is also known as Bone Fish digram.

Function of Ihsikawa diagram is to be used needs - needs as follows:

a. Help identify the root cause of a problem.

b. Help generate ideas - ideas for the solution of a problem.

c. Assisting in the investigation or further fact finding.

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How the easy way to make good design ? the answer is easy :) first, u must have desire and talent of course hehe...then u can learn photoshop program or corel draw, is it hard ? no is not. Everyone can learn that program with easy..we must remember if we can gain our goal in our live with struggle and never give up with ordeal that faced :). so let's do it n hopely succed for u all :).

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Cost ratio plan methode

This method of evaluating the cost of each factor as a percentage of total purchases for the supplier. This method evaluates supplier performance using standard cost. By using this method the buyer must be able to identify additional costs that arise during the cooperation with suppliers. These costs are separate from the elements, namely the quality of supplier performance, service and price. For each of these costs will be converted into a form that describes the ratio of the cost of the incremental cost of purchasing a percentage of the total cost of the supplier. These three cost ratios are summed to obtain the ratio of the overall cost of the supplier and subsequently added to the price of the supplier, and then compared with the ratio of the cost of other suppliers.

This method is very complex in its application that requires a special design, a great company and a computerized accounting system properly to obtain accurate cost data.

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Management Information System (MIS) Methode

The system of management information (MIS) was the application of the information system in the organisation to support information that were needed by all the management stages.

Definition Of MIS

1. The collection from the interaction of information systems;

2. Produced information that was useful for all the management stages.

In the theory, computer must not be used in MIS, but the fact is not possibly MIS that was complex could function without involving the element and the element of the computer of the non-computer. Gordon B. Davis stressed that MIS always was connected with the processing of information that was based to the computer (computer-based information processing). All the information systems that were applied in an organisation were meant to give information to all the management stages, that is the management of the low level (lower the level management), the management of the middle level and the management of the upper level.

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Game Theory (History)

The game was a form of the competition between two sides or two groups that faced each other and used the rule that was known by the two sides that faced each other. A decision must be taken to receive optimum results. A decision was taken to maximise the victory or the minimal profit or minimise the defeat or the loss that the maximum. This decision making was the matter that was most important in the theory of the game that was the quantitative analysis method of the operation research.

Game Theory was the strategy that was introduced for the first time by a mathematician from France that was named Emile Borel during 1921. However just during 1928 succeeded in being proven and analysed by Hon Van Newmann, that now is known as authentication from teorema minimax. Included the principle of the foundation about minimasi from the loss (the defeat) maximum that to teorema the foundation in the theory of the game. Nevertheless just during 1944 the real work of the theory field of this game was put forward in the book was entitled The Theory of Games and Economics Behavior. This book he wrote was with Oscar Morganstern, an economist. In the same year, that is during 1947, when Jon Van Neumann was publishing his work, also was taking place the development and the use of the linear program by Dantzig.

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Krejcie and Morgan (Method for determining sample size of a population)

For any research, the sample size of any study must be determined during the designing stage of the study. However, before determining the size of the sample that needed to be drawn from the population, a few factors must be taken into consideration. According to Salant and Dillman (1994), the size of the sample is determined by four factors: (1) how much sampling error can be tolerated; (2) population size; (3) how varied the population is with respect to the characteristics of interest; and (4) the smallest subgroup within the sample for which estimates are needed.

Using the above methods as a guideline, the following section aims to compare two approaches in determining the sample size of a population of 500 people using (a) Krejcie and Morgan (1970) and (b) Cohen Statistical Power Analysis. In this article i wanna explain about Krejcie and morgan method.

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Definition of Integer Programming

Problems that could be made in the linear program method except for the condition that part or all of his variable must take the form of the integer (integer) was acknowledged as the problem of Integer Linier Programming.

Integer Programming was the problem programming where the optimal solution must produce the integer (integer) so not the fragment. In other words from various integers, must choose and look for the values of the flexible variable and made the Objective function of becoming the maximum. Integer Programming was also said as the program of the count sum, where the program of the sum of the variable count was restricted as the count sum was not negative.

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