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All Journal Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Deny Stevefanus Chandra
Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

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Aplikasi Berbasis M-KNN untuk Mendukung Keputusan Perekrutan Pemain yang Sesuai dengan Kebutuhan Tim Sepakbola Deny Stevefanus Chandra; Mardji Mardji; Indriati Indriati
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 6 (2018): Juni 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Football is each team or squad trying to control the ball, inserting the ball into the opposing goal as much as possible, and try to break the opponent's attack to protect or keep his goal so as not to concede the ball. From the explanation it can be seen that the purpose of playing football is to score numbers or goals. Each player has a different function that is the attacker or the front player serves as an attacker, therefore a 3 front player is required to be able to score against the opponent's goal. Then the midfielder or midfielder serves as a ball feeder or it could be a midfielder in charge of assisting the attacker to insert the ball into the goal. In addition, there is also a defender or defender who serves to keep the goal defense from attack the opponents. However, in addition to serving as defensive, defender or more often called a defender can also be tasked to assist the attack. Because each player has a function or task of each different, of course it affects the kicks of each player depending on the position they have. MkNN is a development of the k-Nearest Neighbor (kNN) method. MkNN class labels on test data based on the validated training data and weight of each training data, not just based on the nearest distance as done on kNN. MkNN provides a greater opportunity for training data that has high validity, so the classification is not too affected on data that is less stable or have low validity. The result of MkNN calculation done by decision support system is same with result of calculation manually. The accuracy of this decision support system application in determining the player's position gets 90% results.
Co-Authors Indriati Indriati Mardji Mardji