İstatistiksel Veri Madenciliği Teknikleri ile Kamu Alımları Sektöründe Satış Tahmini
Özet
In today's economic conditions, states must cooperate with the private sector in economic
situations where it is not possible for them to offer public services. At this point where
states and private sector meet, the concept of public procurement is emerging. Today
public procurement is carried out within the framework of "Public Procurement Law".
Public procurement, which plays an important role in improving the quality of services
provided by the state, indirect savings, encouraging innovation in the private sector,
closing the current account deficit and reducing corruption, undoubtedly has a very
important share for the country's economies.
In this study, it was aimed to forecast the sales of State Supply Office, which is authorized
as central procurement institution within the scope of "exception" concept and to act as
intermediary between private sector and public sector, and to investigate the sensitivities
of these forecast in order to sustain public procurement effectively and efficiently with
various parameters. These data, forecasted by statistical data mining techniques, will be
integrated into the decision support system and the strategic goals of the institution will
be realized and followed.
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In addition, it was planned to model the sales forecasts with linear model, generalized
linear model and random trees and xgboost trees algorithms which ara decision trees ,
using the historical data of 2007-2018 . Thus, it is considered that the key performance
indicators included in the institutional strategic plan will be provided and academic
contribution will be made to increase the efficiency of public procurement sector.
