PENERAPAN DATA MINING UNTUK KLASIFIKASI SELEKSI CALON ANGGOTA HMIF AMIKOM YOGYAKARTA MENGGUNAKAN METODE ALGORITMA DECISION TREE C4.5 - Windha Mega Pradnya Dhuhita; Mita Pertiwi; Ervan Febriyanto; Zian Fahrudy (LPPM STMIK El Rahma Yogyakarta, 2019)
Members of the Amikom HMIF Organizational Committee then have the authority to carry out their vision and mission or main objectives at Amikom Yogyakarta University, one of which is the implementation of recruitment and placement according to requirements and procedures that have been determined by the Chairperson and other authorized members according to the needs of the formation in each organizational unit or body. Many cases have been found that the selection of members from the same year and during the interview. In the case of the initial C4.5 algorithm, in determining whether or not candidates are eligible to use graduation parameters, namely oral and written interviews, enthusiasm and achievement in organization in the history of education that has been followed. Data mining benefits can be implemented in data parts that contain data in large quantities. The technique used in data mining is a decision tree with a C45 decision tree. The results of the study used 80 data from prospective members who had registered. Producing experimental and evaluation results that C4.5 decision tree algorithm is accurate in determining whether or not prospective members pass.