Diagnosa Tingkat Depresi Mahasiswa Akhir Terhadap Penelitian Ilmiah Menggunakan Algoritma K-Nearest Neighbor

 (*)Bernadus Gunawan Sudarsono Mail (Universitas Bung Karno Jakarta, Indonesia)
 Sri Poedji Lestari (Universitas Bung Karno Jakarta, Indonesia)

(*) Corresponding Author

Submitted: September 1, 2020; Published: October 20, 2020

DOI: http://dx.doi.org/10.30865/mib.v4i4.2448

Abstract

The achievement of a success is considered not an easy thing, such as reversing between a leaf and another, success must be achieved with sincerity, even risking everything that is in a person to achieve success and a lot of success can be obtained through higher education, higher education is a way Reaching goals, companies, industry and government prioritize higher education as trusted human resources, many final students experience depression due to many demands and several factors, excessive levels of depression result in all efforts and efforts will cause all chaos and can make someone making the wrong decision to result in death, a system is needed in diagnosing the level of depression in final students to reduce the risk of continuous depression using the k-Nearest Neighbor algorithm approach, with this algorithm it is il in the form of a decision on the level of depression experienced by final students

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Diagnosa Tingkat Depresi Mahasiswa Akhir Terhadap Penelitian Ilmiah Menggunakan Algoritma K-Nearest Neighbor

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