Analisa Validitas Penentuan Predikat Kelulusan Berdasarkan Data Individu Mahasiswa di Institut Teknologi Dirgantara Adisutjipto (ITDA)

Dwi Nugraheny; Anton Setiawan Honggowibowo

Authors

Dwi Nugraheny Institut Teknologi Dirgantara Adisutjipto, Yogyakarta
Anton Setiawan Honggowibowo Institut Teknologi Dirgantara Adisutjipto, Yogyakarta

Keywords:

k-nearest neighbor, graduation, parents' income

Abstract

The world of education will never be separated from student data and graduation data. Student data is usually obtained at the time of registration of new students to an institution. Various individual data and parental data will be stored in the student's individual data archive. It is unfortunate if the data is not used and only as an archive. In this study, students will utilize individual data in the form of parental income data and data on student visits to the library. Which individual data will be associated with the student's cumulative achievement index to determine the validity of the student's graduation predicate. One method that can be used is the K-Nearest Neighbor method. The K-Nearest Neighbor method is a method for classifying objects based on the training data that is closest to the object. This study aims to analyze the validity of the student graduation predicate based on individual data such as parental income data and student library visit data using the K-Nearest Neighbor method. The case study was conducted by taking data from the Adisutjipto Aerospace Technology Institute

References

D. Sebastian. (2019). Implementasi Algoritma K-Nearest Neighbor untuk Melakukan Klasifikasi Produk dari beberapa E-marketplace, Jurnal Jutisi. Vol. 5, no. 1, pp. 51–61.

Deny Nugroho Triwibowo, Ahmad Kurniadi, Siti Hartinah. (2019). Sistem Pendukung Keputusan Pemilihan Mahasiswa Penerima Beasiswa dengan K-NN dan ELECTRE. Jurnal Inspiration, Vol 9, No 2.

Desi Ratna Sari, Agus Perdana Windarto, Dedy Hartama, Solikhun. (2018). Sistem Pendukung Keputusan untuk Rekomendasi Kelulusan Sidang Skripsi Menggunakan Metode AHP-TOPSIS. Jurnal Jtsiskom, Vol 6, No 1.

Nugraheny D., Yuliani Indrianingsih, Aldio Bima Saifullah. (2020). Measuring The Website Quality of Adisutjipto College of Technology Based on Three Dimensions (Usability, Information Quality and Service Interaction). Jurnal Compiler. Vol 9. No 2.

Kusumadewi, 2007 Diktat Artificial Intelligence Lecture, Department of Informatics, Faculty of Industrial Technology, Islamic University of Indonesia. John Creswell (1996) Fuzzy Multi-Attribute Decision Making (FUZZY MADM). Yogyakarta: Graha Ilmu Publisher.

N. H. A. Sari, M. A. F. Fauzi, and P. P. Adikara. (2018). Klasifikasi Dokumen Sambat Online Menggunakan Metode K-Nearest Klasifikasi Dokumen Sambat Online Menggunakan Metode K-Nearest Neighbor dan Features Selection Berbasis Categorical Proportional Difference, Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, vol. 2, no 8. pp. 2449–2454.

R. Siringoringo. (2018). Klasifikasi Data Tidak Seimbang Menggunakan Algoritma SMOTE dan k-Nearest Neighbor, Jurnal ISD, vol. 3, no. 1, pp. 44–49.

Reni, Widodo, dan Bambang Prasetya Adhi. 2020. Sistem Pendukung Keputusan Untuk Memprediksi Kelulusan Mahasiswa Pada Program Studi Pendidikan Teknik Informatika Dan Komputer Dengan Menggunakan Algoritma Naïve Bayes. Jurnal Pinter, Vol 4, No 1.

Rogayah Rogayah, Julia Fajaryanti, Lintang Yuniar Banowosari. 2017. Implementasi Metode Naïve Bayes pada SPK untuk Memprediksi Pola Kelulusan Mahasiswa Perguruan Tinggi Swasta. Sembas Inotek, Vol 1, No 1.

Santoso, Budi, 2007, Data Mining : Pemanfaatan Data untuk Keperluan Bisnis. Graha Ilmu. Yogyakarta.

Tia Imandasari, Agus Perdana Windarto, 2017. Sistem Pendukung Keputusan dalam Merekomendasikan Unit Terbaik di PDAM Tirta Lihou Menggunakan Metode Promethee, Jurnal Teknologi dan Sistem Komputer, Vol. 5, no. 4, pp. 159-165.