CASH FLOW ANALYSIS USING DATA MINING FOR DECISION SUPPORT SYSTEM CONSTRUCTION IN CV. DWI DAYA AGOMAS

Rudmel, Felix Fellieyanto (2021) CASH FLOW ANALYSIS USING DATA MINING FOR DECISION SUPPORT SYSTEM CONSTRUCTION IN CV. DWI DAYA AGOMAS. S1 thesis, Universitas Atma Jaya Yogyakarta.

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Abstract

In Indonesia, there are a lot of industries that are currently undergoing a big changes in the term of their development. A specific industry such as the palm oil industry is one of the industries that are very common to be found in West Borneo province. Crude palm oil is a commodity that can be easily found in our daily life. Behind the product that is based on the palm fruit itself, exist many parties that are involved in the industry. One of the parties that are taken into focus is a holding ramp. A holding ramp is a company that purchases crude palm fruit from the farmers and sells it to the factory that processes it. Inside a holding ramp business, there exists a constant purchasing activity to ensure that a ramp can hold as many palm fruit from the farmer that can be sold to the processing factory. Taking the point of view from the owner of the company in preparing their funds, there exists a problem where the fund that is utilized for purchasing activity is often unavailable. Therefore, a research is conducted to find the best solution to solve this problem. In this research, a holding ramp became the object to be taken into focus. The main focus of this research is to create a decision support system for a holding ramp in managing their fund utilization especially in preparing the budget for purchasing activity. In the first step of the research, a data collection activity is conducted by interviewing the company owner and requesting the necessary data such as the company transaction data. Using data mining as the method to extract information from the data, various insights and findings can be obtained and later used for the development of the decision support system itself. The method utilized to find the information from the data is by using various tools such as R Studio to find the type of data distribution from the obtained data. The approach is by using Maximum Likelihood Estimation to find the best type of data distribution that fits the data that was analyzed. The result of this research is a decision support system in the form of purchasing activity simulation based on the company’s purchasing behavior. The simulation is constructed in Microsoft Excel and showing predictions of various variables such as the amount of goods purchased, the timing of selling the goods, and the amount of bank account balance of the company. Throughout the development of the decision support system itself, many discussion were conducted with the company owner to gain much information such as the company’s financial condition and the market condition of the crude palm oil industry. By having constant communication with the owner, there are many adjustments made to the decision support. The decision support system developed was used as the tool by the company owner to determine the amount of many needed to be prepared before purchasing the goods for a consecutive amount of time.

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