* Corresponding Author
Hide
Show all
Prediction of Length of Study of Student Applicants Using Case Based Reasoning
https://doi.org/10.22146/ijccs.28076 Ulfi Saidata Aesyi(1*), Retantyo Wardoyo(2)
(1) Department of Information Systems, FTTI UNJANI, Yogyakarta,
(2) Departemen Ilmu Komputer dan Elektronika, FMIPA UGM, Yogyakarta
(*) Corresponding Author
Abstract
Graduation is important matter in college. Length of study can be used to evaluate curriculum. It affect accreditation score of the sutdy program. Based on Akreditasi Program Studi Magister Buku V Pedoman Penilaian Instrumen Akreditasi 3rd standard there is rule about students and graduation, such as profile of the graduates including average length of study time and gpa (grade point average) of graduates.
In this study, system built to predict Gadjah Mada University Master of Computer Science student applicant’s length of study. It used new case with 13 features from applicant that will be predict as new case, then calculate local similarity using euclidean distance and hamming distance while global similarity using nearest neighbor. Maximum value of global similarity taken as solution while revised will be done if it’s value below threshold.
Result of this study show that system can help study program to manage educational process. It show 76% accuracy of 50 data.
Keywords
Full Text:
PDFReferences
[1]
S. Salmu and A. Solichin, "Prediction of Timeliness Graduation of Students Using Naive Bayes: A Case Study at Islamic State University Syarif Hidayatullah Jakarta," Prosiding Seminar Nasional Multidisiplin Ilmu, pp. 701-709, 2017.
[2]
X. Hu, B. Xia, M. Skitmore and Q. Chen, "The Application of Case-Based Reasoning in Construction Management Research: An Overview," Automation in Construction, no. 72, pp. 65-74, 2016.
[3]
E. Wahyudi and S. Hartati, "Case-Based Reasoning untuk Diagnosis Penyakit Jantung," IJCCS (Indonesian Journal of Computing and Cybernetics Systems), vol. 1, no. 11, pp. 1-10, 2017.
[4]
T. Rismawan and S. Hartati, "Case-Based Reasoning untuk Diagnosa Penyakit THT (Telinga Hidung dan Tenggorokan)," IJCCS (Indonesian Journal of Computing and Cybernetics Systems), vol. 6, no. 2, pp. 67-68, 2013.
[5]
S. Kosasi, "Penerapan Metodologi Penalaran Berbasis Kasus dalam Mendiagnosa Kerusakan Komputer," TECHSI, vol. 7, no. 2, pp. 187-202, 2015.
[6]
M. T. Rezvan, A. Z. Hamadani and A. Shalbafzadeh, "Case-Based Reasoning for Classification in the Mixed Data Sets Employing the Compound Distance Methods," Engineering Applications of Artificial Intelligence, vol. 26, no. 9, pp. 2001-2009, 2013.
[7]
N. Krisandi, Helmi and B. Prihandono, "Algoritma k-Nearest Neighbor dalam Klasifikasi Data Hasil Produksi Kelapa Sawit pada PT. Minamas Kecamatan Parindu," Buletin Ilmiah Math. Stat. dan Terapannya (Bimaster), vol. 2, no. 1, pp. 33-38, 2013.
[8]
K. J. Cios, P. Witold, R. W. Swiniarski and L. A. Kurgan, Data Mining: A Knowledge Discovery Approach, Springer, 2007.
[9]
L. S. Putro, R. Saptono and R. Anggrainingsih, "Penerapan Kombinasi Algoritma Minhash dan BInary Hamming Distance pada Hybrid Perekomendasi LAgu," Jurnal ITSMART, vol. 2, no. 1, pp. 36-43, 2013.
[10]
W. Liu, G. Hu and J. Li, "Emergency Resources Demand Prediction using Case-Based Reasoning," Safety Science, vol. 50, no. 3, pp. 530-534, 2017.
[11]
E. Wahyudi, Case-Based Reasoning untuk Diagnosis Penyakit Jantung, Yogyakarta: Gadjah Mada University, 2015.
DOI: https://doi.org/10.22146/ijccs.28076
Article Metrics
Abstract views : 3010
| 
views : 2952
Refbacks
- There are currently no refbacks.
Copyright (c) 2019 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
View My Stats1