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Yayın Milkminer: a dairy farm analysis and learning system(Işık Üniversitesi, 2014-01-23) Genç, Ayşenur; Ünel, Gülay; Işık Üniversitesi, Fen Bilimleri Enstitüsü, Enformasyon Teknolojileri Yüksek Lisans ProgramıAgriculture and animal breeding industry is getting its share from the rapid advances in technology which enables the world wide use of automation systems. The use of automatic milking systems in dairy farms for milking has also increased. The goal of this thesis is to contribute to the development of performance enhancing processes by analyzing the data collected in dairy farms for discovering new rules and relationships using data mining. The outputs of this thesis will be used by Triodor Company as an analysis and learning system. Currently, the data collected in various dairy farms all around the world that use automated systems is stored for use in local or global databases as a part of the automation projects. Since these automation technologies are still in the development phase, research and development on detailed study, analysis and relationship recognition among data is in early stages and limited. Currently, the central database populated by the software technologies developed by Triodor contains data about each individual farm such as key performance measurements collected daily from more than 30 countries and 4000 dairy farms for various types of users. This large scaled dataset is not used for any operation or analysis other than simple query answering. If this large database and external data sources (such as weather, vegetation) are analyzed for the detection of potential hidden relationships among data then it will be possible to realize improvements in these farms regarding various types of criteria such as performance, sustainability, and product quality. In this thesis, an analysis and learning system that works on the data collected from dairy farms is developed. In the implementation of this system, the dairy farm database design is analyzed in terms of the content to be used in analysis purposes, and then the database is analyzed using data mining methods. As a result, a system with quantitative analysis techniques via data mining methods is generated.Yayın Data mining techniques customer relationship management : a case study for Doğuş Otomotiv(Işık Üniversitesi, 2003-10) Gören, Olga Ufuk; Yarman, Bekir Sıddık Binboğa; Işık Üniversitesi, Fen Bilimleri Enstitüsü, Enformasyon Teknolojileri Yüksek Lisans ProgramıCustomer Relationship Managment has recently become a very important investment for many companies. The value of the customer is expressed more clearly with this new concept and it's demonstrated through its applications. The increased importance of focusing on the customer has been recognized in related academic studies in recent years. CRM has great importance in helping companies find the answers to questions such as ''What types of customers exist in which markers?'', ''What do they demand from companies?'', ''Who should be targeted as a customer?''. In fact it is a corporate strategy itself. In order to be successful, a company needs to combine the whole CRM concept with its vision. Furthermore, CRM is a strategy which aims to increase the improtance of every stakeholder of the company. With CRM, it is easy to realize the great value sone data for future of a company even though such data for the future of a company even though such data were not considered important in the past. CRM also provides ways of evaluating these data, and creating new goals out of results. The aim of this thesis is to study the CRM implementation process and show how customer data is being classified, analyzed and assessed, making use of the results of RFM analysis and demographical analysis as implemented in Doğuş Otomotiv. The importance of this thesis is that it keeps customers and their information in a data warehouse, so as to be available for effective use and analysis when needed. This analysis will help companies organize their marketing and sales activisties so as to respond to the right customer, at the rigth time, in the right way, and at the right place within their market.
