The Snow Storm Lawsuit Research Paper Example | Topics and Well Written Essays - 1000 words

The Snow Storm Lawsuit - Research Paper Example In the given case study, because of heavy snow storm, many hospital staffs who were working for a no-profit community hospital providing patient care called out from work on the 3-11 and 11-7 shifts which resulted in damages including loss of life to patients due to lack of nursing staff available during that period. The families of these patients sued the hospital on behalf of their deceased relatives. This paper briefly analyses legal, ethical, professional and business considerations involved in this case. The first legal consideration involved in this case is that the hospital management failed to provide necessary protection to the patients admitted in the hospital. It is the duty of the hospital management to ensure adequate medical care to all the patients admitted in the hospital at any cost. By calling out the nursing staff, the management sacrificed the interests of the patients. The hospital should have taken adequate precautionary measures to counter the problems associated with snow storm as snow storm was not a new thing to them. The patients who were not able to move out of hospital left unnoticed in the hospital till the snow storm ends which is definitely illegal. The hospital management played with the lives of patients and definitely they were guilty of neglecting the interests of the patients. The second legal consideration in this case is that whether the hospital staff could be forced to work in such drastic conditions. Life is precious to all whether it belongs to the patients or to the hospital staffs. Under such circumstances, can the hospital authorities pressurise the hospital staff to work? The third legal consideration in this case is that one patient lost his life because of incorrect medication. Only one nurse was agreed to work during this disaster period and she should have heavy workload during this period because of lack of other medical staffs available at that time in that hospital. It is quiet possible that she might have

Business-Level and Corporate-Level Strategies Essay - 13

Business-Level and Corporate-Level Strategies - Essay Example The operations carried out at America, China, and United Kingdom was very successful. It provides online shopping opportunity to its customers. Its main objective is to provide better life to its customers with the help of the donations in kind. Wal-Mart is managed by Walton family as it is a family owned business. It has around 2.2 million employees across the world. Corporate level mainly deals with framing the mission and vision of the organization and planning accordingly to reach the desired goal. It formulates different strategies which are required for attainment of objectives of the company. The Functional level objectives are derived from that of the corporate level. This level develops coordination between the corporate and business unit level. In this complex environment of the business, the strategies are required to be formulated. This strategy is very well defined as in this level the marketing strategy will be further divided between the sales. The strategy in this level helps in the attainment of functional objectives of the organization (Hoskisson, Hitt and Ireland, 2012). Strategic management is required for the growth of the organization. It helps in the formulation of effective business environment. Business strategy is compared and formulated with the five forces that build competition. The strategic position of the company can be determined by the business level strategy. Wal-Mart adopts competitive advantage by delivering unique product to its customers by providing a standardized product at a lowest competitive price. The company can select any one from the given strategies to gain competitive advantage by delivering uniqueness in the product and lowering down the cost. The retail industry focuses on the cost leadership strategy to sustain in the market and narrowing the competitive scope. When the company provides unique product the customers will be willing to pay a premium for the product. Corporate level refers to the strategy

Stock photography Essay Example | Topics and Well Written Essays - 500 words

Stock photography - Essay Example Stock photography in this case becomes highly cost effective and of great use at the right time. Moreover, hiring and explaining while training the photographer as to what the company actually needs out of his work takes a lot of time and still cannot assure the desired results. Therefore in order to minimize the risk of getting the wrong outcomes, most of the companies go for stock photography (Highton, 244). The use of stock photography is most commonly found in the advertising, design or such related agencies which have more of a creative and artistic work to do. Although this type of photography seems easy but it has some serious criterion related to it. Such photographers always have to keep on following certain criteria so that their images can match up to the standards which most of the reputed and well established companies desire (Gross, 185). This type of photography is best utilized by those companies which are purely involved in their core business and can hardly manage these advertising and promotional aspects on their own.Stock photography is of great value both to the photographer as well as the employer as it mutually benefits both parties not only in financial terms but also in terms of saving valuable time of both parties. The success of stock photography entirely depends upon the effectiveness and efficiency of the photographer. If the portfolio of his or her pictures is diverse and caters almost everything that can match the needs of his target clients, then it would definitely get him a huge business. Similarly, he would not be in need of updating the portfolio of new pictures every now and then. The trend of the stock photography started a long time back, nearly in the nineteen twenties. But now the things have changed drastically. It has not just been limited to photography but a number of agencies have been established

International Maritime Organization Assignment Example | Topics and Well Written Essays - 750 words

International Maritime Organization - Assignment Example It includes number of safety measures like that of improving the electrical installation and machinery installation, life saving equipments, fire protection, navigation safety, carriage of hazardous goods, radiotelegraphy and radiotelephony, nuclear merchant ships, and the overall safety of the shipping. The primary function of IMO is to form legislation and establish global treaties relating marine pollution prevention and safety of shipping. The organisation keeps the legislation always up to date so that it becomes helpful for the concerned countries and this attempt has become a successful one. It is found that more than 98% of the international shipping traders follow these legislations. IMO’s another important function is to protect the environment from the hazards of shipping because the extracts of the shipping activities which flows to the sea is very harmful which creates water pollution. Thus, these set of laws helps to prevent the sea water from pollution. IMO also provides safety training to avoid accidents occurring in the sea. The measures taken by IMO have been successful and the rate of serious hazards rate has been reducing from the last twenty years. The oil from the ships which used to enter into the sea also has reduced by considerable extent. Since human resources are the most important resource of the shipping industry so it has become an important task of IMO to improve and develop the human resources. With the opening of the ISM Code, it has made safety a prime concern. This code explains the responsibility for safety and implementation of this code has become tremendously successful. The IMO has also implemented training programmes and has provided modern guidelines to their marine educational institutions through various technical programmes. Thus it can be concluded that IMO provides detailed guidelines and direction which are essential to

Stock photography Essay Example | Topics and Well Written Essays - 500 words

Stock photography - Essay Example Stock photography in this case becomes highly cost effective and of great use at the right time. Moreover, hiring and explaining while training the photographer as to what the company actually needs out of his work takes a lot of time and still cannot assure the desired results. Therefore in order to minimize the risk of getting the wrong outcomes, most of the companies go for stock photography (Highton, 244). The use of stock photography is most commonly found in the advertising, design or such related agencies which have more of a creative and artistic work to do. Although this type of photography seems easy but it has some serious criterion related to it. Such photographers always have to keep on following certain criteria so that their images can match up to the standards which most of the reputed and well established companies desire (Gross, 185). This type of photography is best utilized by those companies which are purely involved in their core business and can hardly manage these advertising and promotional aspects on their own.Stock photography is of great value both to the photographer as well as the employer as it mutually benefits both parties not only in financial terms but also in terms of saving valuable time of both parties. The success of stock photography entirely depends upon the effectiveness and efficiency of the photographer. If the portfolio of his or her pictures is diverse and caters almost everything that can match the needs of his target clients, then it would definitely get him a huge business. Similarly, he would not be in need of updating the portfolio of new pictures every now and then. The trend of the stock photography started a long time back, nearly in the nineteen twenties. But now the things have changed drastically. It has not just been limited to photography but a number of agencies have been established

West Side Story Essay Example for Free

West Side Story Essay Do you believe that everyone has a reason to hate someone or something just because of the way they look? May racism be the starting point to hatred? In â€Å"West Side Story†, author Irving Shulman gives us nothing but clues to these questions. The Sharks and the Jets are in a â€Å" turf † war. But two people, one from each side fall deeply in love. Irving Shulman writes how interracial relationships cause hate to increase in an instant and how racism leads up to hate. The story tells the reader how the Puerto Ricans and the Jets cause the world to shake because of racial prejudice. West Side Story† shows how racial prejudice and interracial relationships cause hate to grow. â€Å"West Side Story† shows hate between almost anyone and yet we have no answers on why people hate. After reading â€Å"West Side Story† it made me believe that racism caused by interracial relationships may be what causes hate in this story. In â€Å"West Side Story† two gangs, the Jets and the Puerto Ricans hate each other just because of the way they look, where they are from, and how they live. Racism is a big part in this story. The main part of hate came from an interracial relationship that began between a man of American descent and a Puerto Rican woman, which caused hate to grow between two gangs in the streets of New York. Racial prejudice was very bad in the time this story was written. Anyone can relate to racial remarks. This story truly shows how people used to be and how much the idea of interracial relationships happening changed. Now, it doesn’t matter if two people fall in love even though they are not from the same race. From this you can infer that racism might be what inaugurates hate. Racism might seem like just a word but it’s more powerful than just a word. It only leads to no good in â€Å"West Side Story†. Hate, what is the definition of hate? Everyone has a different perspective of it, but no one can really see what it can lead up to. I don’t understand why people hate for no reason. I think that they are influenced by what they see. Racism is a terrible thing in this story. It makes hate grow a thousand times bigger and causes a huge impact in others’ lifes. Throughout the story there was a part where both gangs went to a dance and one of the gangs were dancing on the contrary side of the building so they wouldn’t mix with the other race. This shows some sort of proof of how both gangs show hate towards one another. Even those that weren’t in any of the gang’s side were involved in discrimination against the other race because they were following what the others were doing. This made me think about how racism begins. It can be caused by those around you, which might be the influence. Racism is an organization in our country. It has existed since our country’s beginning, and there is not much that anyone can do to stop it but ignore it. Anywhere and everywhere you go, there will be someone different but this doesn’t mean you have to hate or criticize those who are different. Towards the ending of â€Å"West Side Story†, the unexpected happened. There was a death and I can conclude that hate and racism were the leading products to this horrific tragedy. For example, Tony had died and Maria was devastated without him. These violent delights have violent ends. Maria had then realized what had killed him and said, We all killed him I can kill now because I hate now. This shows how the racism and hatred of the two gangs lead to event of Tony’s death. People have to understand that love happens. It doesn’t make sense how some people despise the love that happens between two races. It doesn’t matter if both of the people are from a different race. You can’t keep hating on interracial relationships your entire life and being racist against them. Because like this story much of your hatred and racism can lead onto a terrible catastrophic event such as the deaths that happened in â€Å"West Side Story†. Everyone needs to understand that racism isn’t a pretty thing to live with and it’s as bad as hating someone without a purpose. Even if you had a purpose, hate is an evil and powerful thing that can control someone’s mind and influence others. Not only Tony had died in this story but Bernardo, Maria’s brother died too. That is how hate influenced Maria’s supposed to be husband to murder Tony. This interracial relationship caused hates to grow in everyone’s eyes and no one refused to let go of on whose fault it was. It led on, to bigger tragedies. To conclude, the hate that goes towards interracial relationships and racist remarks cause hate to expand in â€Å"West. My final thoughts for this story are that hate and racial prejudice remarks are not the way to situate things, because all they do is hurt others. I want the world to love everyone for who they are. Nothing makes sense anymore, because many are being influenced by hate. How can someone hate two that fell in love? In my opinion the definition for hate is death, because I feel that hate will always lead up to death. You will end up alone in life. Racism is a synonym for hate and even though we can’t do anything about racism we should at least try not to influence it. â€Å"West Side Story† made me think twice about life and that everyone is different and yet equal in the same way, we are all human beings. As I stated earlier racism and interracial relationships cause hate to grow in this world and should be avoided everyday. The world isn’t perfect but we can at least try to make it perfect.

Important and application of data mining

Important and application of data mining Important and application of Data Mining Abstract Today, people in business area gain a lot of profit as it can be increase year by year through consistent approach should be apply accordingly. Thus, performing data mining process can lead to utilize in assist to make decision making process within the organization. This paper elaborate in detail the level of importance and also the application the application of data mining which can be adopt for various fields depends on the objective, mission, goals and purpose of conducting the study within the organization. there are three main areas take as a example which are hotel, library and hotel to observe on how data mining works to these main field. Keywords: Data Mining, KDD Process, Decision Trees, Ant Colony Clustering Algorithm; Association Rules, Neural Network, Rough Set, 1.0 Introduction As we know, organization which conducts business transaction is keeps massive of document or data in a specific database for further retrieval. The data are combine from are a few departments that carried out different task and each of their function parallel with the mission and vision of organization. According (Imberman, 2001) the number of fields in large databases can approach magnitudes of 102 to 103. Therefore, it is necessary to make proper decision making or strategic planning using the existing data where these plays important role in order to ensure any action that are taken place does not given an impact especially bring loss to the organization. Other than that, data became obsolete when it keeps on changing and easily out dated as the user requirement shifting depends on factors such as trends, money, needs and so forth. One way to analyze data is using of data mining technique which enable to assist organization by emphasize several steps to produce the valuable output in short period of time compare with the traditional method which may involves more than one methodologies and it derive to longer of time to accomplish the investigation towards a portion of data. Thus, in the business area an action should be done quickly in order to compete with other competitors and to improve performance both in giving service and produce a high quality product. Moreover, process interpretation of the result involves group of people to inject some of the creativity and synthesis which can lead to the solutions on the problem or tasks. Obviously, data mining a lot assist in various fields with different purposes and depend on the objectives that want to achieve. The rest of this paper is organized as follows. Section 2 tells about definition of data mining. Section 3 determines the importance of data mining. Section 4 explains the application of data mining in various fields. Section 5 draws the conclusions. 2.0 Definition of Data Mining There are abroad definitions listed by a few researcher and academician according to their view and opinion based on the study they have done. Moreover, these will help to understand or giving an idea before discusses more in depth towards data mining technique. Basically, the main purpose use of data mining is to manipulate huge amount of data either existence or store in the databases by determine suitable variables which is contribute to the quality of prediction that will be use to solve problem. Define by Gargano Raggad, 1999. Data mining searches for hidden relationships, patterns, correlations, and interdependencies in large databases that traditional information gathering methods (e.g. report creation, pie and bar graph generation, user querying, decision support systems (DSSs), etc.) might overlook. Besides that, another author also agreed with opinion toward the data mining definition which is to seek hidden pattern, orientation and also trend. Through (Palace, 1996) added to the previous is: Data mining is the process of finding correlations or patterns among dozens of fields in large relational databases. Moreover, data mining also define as process to squeeze of knowledge or information using appropriate framework or model to analyze until produce an output that assist in fulfill the objective of the study. From Imberman, 2001: As knowledge extraction, information discovery, information harvesting, exploratory data analysis, data archeology, data pattern processing, and functional dependency analysis. The statement above agreed and adds that the framework or model that adopt definitely to expose the real circumstance. Define by Ma, Chou Yen, 2000: Data mining is the process of applying artificial intelligence techniques (such as advanced modeling and rule induction) to a large data set in order to determine patterns in the data. In the other hand, data mining is taken a few steps during analysis and this step is depending on the methodology that is chosen. Each of the methodology is not much differ from other methodology. Through Forcht Cochran, 1999: Data mining is an interactive process that involves assembling the data into a format conducive to analysis. Once the data are configured, they must be cleaned by checking for obvious errors or flaws (such as an item that is an extreme outlier) and simply removing them. 3.0 Important of Data Mining As discusses above, it can be seen that data mining will be beneficial a lot of party and multiple range of level in the organization as the model or framework that is apply can reduce time and cost. Then, the results allow the responsible knowledge worker to transform into the strategic value of information effectively by critically analyze the result. The process should be done carefully to avoid the useful variables or algorithm being removes or not be included in the extraction of reliable data. Data mining techniques will help in select a portion of data using appropriate tools to filter outliers and anomalies within the set of data. According to Gargano Raggad, 1999, there are a few others important of data mining consist of:  · To facilitate the explication of previously hidden information includes the capabilities to discover rules, classify, partition, associate and optimize. According to (Goebel Gruenwald, 1999) in order to seek the pattern of data, a few methodologies are use in clarify the vagueness as well as to identifying the relation among one variables and other variables within the databases whereas the outcome will guide in making decision or to forecast the impact when the action were take into consideration. The chosen of methodologies should be determined in a proper way suit with the rules and condition towards the data which is to be analyzed. The methodologies include: Statistical Methods: focused mainly on testing of preconceived hypotheses and on fitting models to data. Case-Based Reasoning (CBR): technology that tries to solve a given problem by making direct use of past experiences and solutions. Neural Networks: formed from large numbers of simulated neurons, connected to each other in a manner similar to brain neurons which enables the network to learn. Decision Trees: each non-terminal node represents a test or decision on the considered data item and can also be interpreted as a special form of a rule set, characterized by their hierarchical organization of rules. Rule Induction: Rules state a statistical correlation between the occurrences of certain attributes in a data item, or between certain data items in a data set. Bayesian Belief Networks: graphical representations of probability distributions derived from co-occurrence counts in the set of data items. Genetic algorithms / Evolutionary Programming: formulate hypotheses about dependencies between variables, in the form of association rules or some other internal formalism. Fuzzy Sets: constitute a powerful approach to deal not only with incomplete, noisy or imprecise data, but may also be helpful in developing uncertain models of the data that provide smarter and smoother performance than traditional systems. Rough Sets: rough sets are a mathematical concept dealing with uncertainty in data and used as a stand-alone solution or combined with other methods such as rule induction, classification, or clustering methods  · The ability to seamlessly automate and embed some of mundane, repetitive, tedious decision steps not requiring continuous human intervention. Several steps are taken in processes or analyzes on selected data where the process involves of filtering, transforming, testing, modeling, visualization and documented the result or store accordingly in the databases or data warehouse. Each of the steps functions differently and has responsibility in carries out the process with the purpose to easier and produce the high quality of assumption by automate generate towards specific conditions. For example, data warehouse also keep previous analysis and this allow eliminating the redundant output at certain steps. Through Ma, Chou Yen, 2000, they stress the characteristics of data mining define how it assist to reach the end process of analyzing. It comprises: Data pattern determination: Data-access languages or data-manipulation languages (DMLs) identify the specific data that users want to pull into the program for processing or display. It also enables users to input query specifications. Therefore, users simply select the desired information from the menus, and the system builds the SQL command automatically. Formatting capability: It generates raw data formats, tabular, spreadsheet form, multidimensional-display and visualization. Content analysis capability: Data mining also has a strong content analysis capability that enables the user to process the specifications written by the end-users. Synthesis capability: Data mining allows data synthesis to be timely executed.  · Simultaneously reducing cost and potential error encountered in the decision making process. Basically, data mining can minimize the error of forecasting by following the steps of selected methodology in well manner to avoid delaying in making decision where this situation will giving big impact for the business area. Therefore, it must be careful in handling the data throughout the steps involves whereby the strategic plan should take into consideration includes of the objectives to done the analysis, the amount of data, the variables, the relationship between variables, test adopted, and so forth. Moreover, if there is need to discuss with the professional towards the study conducted and it should be included in the planning part. In the context of organization, usually a unit or group of people are given responsible to carries this duty to discover the hidden pattern for another department. Hence, the continuously meeting should be done between the professional and researchers to ensure the end result fulfill their requirement as well as to improve the performance of work er, department and organization. In term of reducing a cost, compare to the traditional research which take time in acquiring the data from respondents and it depend on the methodologies that are use and the number of sampling. If the questionnaire method, it can be done quickly and less time consuming but if the interviewing method is adopted, it surely take time and researcher have to meets the respondent more than one time, if there is an ambiguity or the answers not meet with the requirement. For certain study, the sampling are involves from the different location which require the researcher to travel in order to gain the genuine opinion from them and this will cost a lot involves of accommodation, food, flight ticket and so forth. For data mining, it uses the existence of data (for example, data of customer transaction, data of student registration, data of patient undergo the operation process and so on) that keep in data warehouse which mostly reduce cost in aspect of acquiring data. Other than that, researc her take first action by search for the study in the data warehouse when the objective being determine at the beginning of study because previous study are store in the data warehouse. If it is found tally, a few step will be skip or easily decided towards the data and it prove that data mining can reducing the cost as well as time. Refer to Gargano Raggad, 1999, data mining also derive long term benefit which the cost incurred due to the development, implementation, and maintenance of such systems by a wide margin. 4.0 The application of Data Mining Nowadays, data mining is widely use especially to those organization that focuses on consumer orientation. For example, retail, financial, communication, and marketing organizations (Palace, 1996). Besides it, healthcare area also gain benefit by apply the data mining into the daily operations. These various of field shows each of the organization carries different transaction where all of details keep in the databases which enables to perform analysis for multiple purpose likes to increase revenue, gain more customer, improve customer satisfaction and others. Moreover, again through (Palace, 1996) the existence data allow to determine relationships among internal factor consists price, product positioning or staff skills and external factor consists economic indicators, competition and customer demographic. Hence, there three examples of data minings application in different areas which are hotel sector, library scope and also hospital with the goals to reduce or eliminate the weakness by address it using the result that is interpret in well manner to assist in making decision for the best solutions. The examples are as follows:  · A data mining approach to developing the profiles of hotel customers. A study conduct by Min, Min Ahmed Emam, 2002 with the objective to target some of the valued customers for special treatment based on their anticipated future profitability to the hotel. There are a few questions regarding to the customer profiling: Which customers are likely to return to the same hotel as repeat guests? Which customers are at greatest risk of defecting to other competing hotels? Which service attributes are more important to which customers? How to segment the customer population into profitable or unprofitable customers? Which segment of the customers best fits the current service capacities of the hotels? The researchers adopt decision trees for analyzing the data from the abroad method of data mining methodology because the ability to generate appropriate rules using visualization and simplicity. There are three steps having to follows in this process and it includes: Data collection: the process of select data that suit with objective from the previous survey. Moreover, remove the unwanted data from databases by filtering out the excel file. Data formatting: the process of converted all data in the spreadsheet to Statistical Packages for Social Sciences (SPSS) for the purpose of classification accuracy. Rules induction: the process of selection of algorithms to building decision trees which is C5.0 to generate sets of rules that bring important clues in order for hotel manager to take further action. As the result, the researcher found that if-then rules as a useful in formulating a customer retention strategy with a predictive ranging from 80.9 per cent to 93.7 per cent whereas a predictive accuracy reflect to the rules conditions that affect by times (percentage).  · Using data mining technology to provide a recommendation service in the digital library. A study conducted by Chen Chen, 2006 with the purpose to provide recommendation system architecture to promote digital library service in electronic libraries. There are abroad of digital publication format likes audio, video, picture, etc. thus, it lead difficulties in analyzing or defining the keyword and content in order to gain information from the user to improve the service in the digital libraries. In the methodology section, there are two data mining models selected which consist o Ant Colony Clustering Algorithm; This model is capable to find the shortest path or reduce time to find the best output fit with the problem that existence in the organizations. Each of the steps has different function to enable they too see the relation among the variables It takes a few steps which are: Step 0: parameters and initialize pheromone trails. Step 1: Each ant constructs its solution Step 2: Calculate the scores of all solutions Step 3: Update the pheromone trails. Step 4: If the best solution has not been changed after some predefined iterations, terminate the algorithm; otherwise go to step 2. o Association rules to discover the hidden pattern. This model enables to find co-purchase items and assist in uncovered relationship algorithms in form of association rules. There are two main steps as follows: Step 1: Find all large item sets Step 2; use the large items set generated in the first step to generate all the effective association rules. As the results, these two models encounter more than one solutions and enable to gain a lot of recommendation that can be manipulate into various problem that exists in conducting digital libraries as well as to promote the usage in multiple level of user using the appropriate mechanism and providing suitable services.  · Using KDD process to forecast the duration of surgery. A study conducted by Combas, Meskens Vandamme, 2007 with the aim is to identify classes of surgery likely to take different lengths of time according to the patients profile as well as to allow the use of the operating theatre to be better scheduled. There are many issues arise in this field that lead to the study. For example, an endoscopy unit use of endoscopy tube (shared resources) during the surgery. However their availability is limited because it takes 30-45min to clean and sterilize each one. The scheduling of endoscopies (and all other operating theatre procedures) must obviously take into account the availability of these different resources. The researchers adopt Knowledge Discovery in Databases (KDD) process to analyze this massive data from the databases. The step as follows: Step 1: data preparation which the selected data must be fulfill of requirement includes secondary diagnoses, Previous active history and system affected. Step 2: data cleaning where filter data by concerning surgical procedures that had been performed at least 40 times (at least 20 times for combinations involving both surgery and specific surgeons). Step 3: data mining which to decide appropriate method to test on the portion of data which it involves rough set and neural network. Step 4: validation by comparison consist process of interpretation by comparing the result from two methods that perform data analysis in order to observe the rate of good classification. Then, researcher added up another three steps in order to fit with the objective that is proposed and to produce the best outcomes to forecast the durations of surgery. It consists of: o Step 5: Measuring the impact of predicting the duration of surgery on planning which in this step the duration of surgery supplied by the prediction models (empirical laws, rule-based laws, etc.) based on information stored in the database is used to feed a series of algorithms and heuristics for planning purposes o Step 6: Simulation involves the present time will allow to simulate the activity of the different theatre suites in terms of the operating sequence determined by planning methods on the two scenarios which are operating data and patients profile o Step 7: validation selection of the best model where the results supplied by the simulation model should enable to assess the quality of scheduling on the basis of a series of performance indicators likes the length of time for which the operating theatres are not in use, the number of potential additional hours, and errors in predicting the duration of surgery. As the results, researchers are not particularly satisfactory. The main problem seems to be the choice of variable grouping, which might possibly have an effect on prediction quality. 5.0 Conclusion As a conclusion, data mining can be consider as an effective and efficient way to discover or to transform the invisible to visible data that retrieve from databases which have capabilities to store huge amount of data by using the right tools in assist or enable to analyze, synthesis and manipulate the content of data for various purposes and often depend on the main businesses that carries out to define the target. From the discussion above, it can be seen that there are a lot of advantages when perform data mining especially in the business area which allow the organization to predict the trends, customer requirement, the relationship and so forth as early preparation can be identify in order to seek another or a few others way to ensure that organization can still operate their daily operation after determine that organization not agree towards the result have been gain. In order to produce the end result that satisfying the organization and minimize the error as it successfully implement the information in order to perform business transaction. The key variables should be assign in well manner meet or suitable with the objective that propose in conducting the study because it have to repeat the procedures when found the errors as the decision making process could not been done according to the timeline. 6.0 References Chen, Chia-Chen Chen, An-Pin. (2006 ). Using data mining technology to provide a recommendation service in the digital library. The Electronic Library. 25(6): 711-734. Combas, C., Meskens, N Vandamme, J. P. (2007). Using a KDD process to forecast the duration of surgery. International Journal of Production Economics. 112: 279-293. Forcht., Karen A. Cochran, Kevin. (1999). Using data mining and datawarehousing techniques. Industrial Management Data Systems. 99(5), 189-196. Gargano., Michael L. Raggad, Bel G. (1999). Data mining a powerful information creating tool. OCLC Systems Services. 15(2), 81-90. Goebel, Michael Gruenwald, Le. (1999). A survey of data mining and knowledge discovery software tools. ACM SIGKDD Explorations Newsletter. 1: 20 33. Imberman, Susan P. (2001) Effective Use of the KDD Process and Data Mining for Computer Performance Professionals. in International Computer Measurement Group Conference. Anaheim: USA, 611-620. Ma, Catherine, Chou, David C. .Yen, David C. (2000). Data warehousing, technology assessment and management. Industrial Management Data Systems. 100(3), 125-135. Min, Hokey., Min, Hyesung Ahmed Emam. (2002). A data mining approach to developing the profiles of hotel customers. International Journal of Contemporary Hospitality Management. 14(6): 274-285. Palace, Bill. (1996, Spring). Data Mining: What is Data Mining? retrieved March 2, 2010, from: http://www.anderson.ucla.edu/faculty/jason.frand/teacher/technologies/palace/datamining.htm