The Implementation of Restricted Boltzmann Machine in Choosing a Specialization for Informatics Students

Authors

  • Vinna Rahmayanti Setyaning Nastiti Department of Informatics, Universitas Muhammadiyah Malang, Indonesia, Indonesia
  • Zamah Sari Department of Informatics, Universitas Muhammadiyah Malang, Indonesia, Indonesia
  • Bella Chintia Eka Merita Department of Informatics, Universitas Muhammadiyah Malang, Indonesia, Indonesia

DOI:

https://doi.org/10.15575/join.v8i1.917

Keywords:

Classification, Deep Learning, Restricted Boltzmann Machine, SMOTE, Specialization

Abstract

Choosing a specialization was not an easy task for some students, especially for those who lacked confidence in their skill and ability. Specialization in tertiary education became the benchmark and key to success for students’ future careers. This study was conducted to provide the learning outcomes record, which showed the specialization classification for the Informatics students by using the data from the students of 2013-2015 who had graduated. The total data was 319 students. The classification method used for this study was the Restricted Boltzmann Machine (RBM). However, the data showed imbalanced class distribution because the number of each field differed greatly. Therefore, SMOTE was added to classify the imbalanced class. The accuracy obtained from the combination of RBM and SMOTE was 70% with a 0.4 mean squared error.

References

Y. S. Nugroho, “Klasifikasi dan Klastering Penjurusan Siswa SMA Negeri 3 Boyolali,” Khazanah Inform. J. Ilmu Komput. dan Inform., vol. 1, no. 1, pp. 1–6, Dec. 2015, doi: 10.23917/KHIF.V1I1.1175.

N. Fartindyyah and S. Subiyanto, “Sistem Pendukung Keputusan Peminatan SMAmenggunakan Metode Weighted Product (WP),” J. Kependidikan Penelit. Inov. Pembelajaran, vol. 44, no. 2, Sep. 2016, doi: 10.21831/jk.v44i2.5224.

E. Miranda, “Implementasi Data Warehouse dan Data Mining: Studi Kasus Analisis Peminatan Studi Siswa,” ComTech Comput. Math. Eng. Appl., vol. 2, no. 1, pp. 1–12, Jun. 2011, doi: 10.21512/COMTECH.V2I1.2705.

S. Maslihah, “Studi Tentang Hubungan Dukungan Sosial, Penyesuaian Sosial Di Lingkungan Sekolah Dan Prestasi Akademik Siswa Smpit Assyfa Boarding School Subang Jawa Barat,” J. Psikol., vol. 10, no. 2, pp. 103–114, 2011, doi: 10.14710/JPU.10.2.103-114.

S. Ari, “Penentuan Jurusan Sekolah Menengah Atas Menggunakan Metode K-Nearest Neighbor Classifier Pada SMAN 16 Semarang,” 2015.

T. B. Sasongko and O. Arifin, “Implementasi Metode Forward Selection pada Algoritma Support Vector Machine (SVM) dan Naive Bayes Classifier Kernel Density (Studi Kasus Klasifikasi Jalur Minat SMA),” J. Teknol. Inf. dan Ilmu Komput., vol. 6, no. 4, pp. 383–388, Jul. 2019, doi: 10.1016/j.ijar.2008.08.008.

N. Fuad, “Pemanfaatan Algoritma Fuzzy Naive Bayes Dalam Pemilihan Bidang Keahlian Mahasiswa Teknik Informatika Universitas Islam Lamongan,” J. Tek., vol. 11, no. 2, pp. 1117–1122, Sep. 2019, doi: 10.30736/JT.V11I2.342.

H. A. Majid and K. E. Dewi, “Signature Recognition Using Invariant Moment Method And Restricted Boltzmann Machine”.

S. Pirmoradi, M. Teshnehlab, N. Zarghami, and A. Sharifi, “The Self-Organizing Restricted Boltzmann Machine for Deep Representation with the Application on Classification Problems,” Expert Syst. Appl., vol. 149, p. 113286, Jul. 2020, doi: 10.1016/J.ESWA.2020.113286.

A. Decelle and C. Furtlehner, “Restricted Boltzmann Machine, recent advances and mean-field theory,” Chinese Phys. B, vol. 30, no. 4, Nov. 2020, doi: 10.1088/1674-1056/abd160.

H. Lee and J. Lee, “Scalable deep learning-based recommendation systems,” ICT Express, vol. 5, no. 2, pp. 84–88, Jun. 2019, doi: 10.1016/J.ICTE.2018.05.003.

R. Salakhutdinov, A. Mnih, and G. Hinton, “Restricted Boltzmann machines for collaborative filtering,” ACM Int. Conf. Proceeding Ser., vol. 227, pp. 791–798, 2007, doi: 10.1145/1273496.1273596.

T. Ojha, G. L. Heileman, M. Martinez-Ramon, and A. Slim, “Prediction of graduation delay based on student performance,” Proc. Int. Jt. Conf. Neural Networks, vol. 2017-May, pp. 3454–3460, Jun. 2017, doi: 10.1109/IJCNN.2017.7966290.

J. W. G. Putra, Pengenalan Pembelajaran Mesin dan Deep Learning. 2018. Accessed: Apr. 12, 2023. [Online]. Available: https://www.researchgate.net/publication/323700644_Pengenalan_Pembelajaran_Mesin_dan_Deep_Learning

F. Adi Nurcahyo, S. Azwar, and W. Martani, “Stimulus Gambar: Sebuah Kajian pada Instrumen Minat Vokasional,” Bul. Psikol., vol. 26, no. 2, pp. 111–125, Dec. 2018, doi: 10.22146/BULETINPSIKOLOGI.40361.

N. Zhang, S. Ding, J. Zhang, and Y. Xue, “An overview on Restricted Boltzmann Machines,” Neurocomputing, vol. 275, pp. 1186–1199, Jan. 2018, doi: 10.1016/J.NEUCOM.2017.09.065.

A. Pujahari and D. S. Sisodia, “Modeling Side Information in Preference Relation based Restricted Boltzmann Machine for recommender systems,” Inf. Sci. (Ny)., vol. 490, pp. 126–145, Jul. 2019, doi: 10.1016/J.INS.2019.03.064.

W. Zhang, H. Zou, L. Luo, Q. Liu, W. Wu, and W. Xiao, “Predicting potential side effects of drugs by recommender methods and ensemble learning,” Neurocomputing, vol. 173, pp. 979–987, Jan. 2016, doi: 10.1016/J.NEUCOM.2015.08.054.

U. Khan, P. Safari, and J. Hernando, “Restricted Boltzmann Machine Vectors for Speaker Clustering and Tracking Tasks in TV Broadcast Shows,” Appl. Sci. 2019, Vol. 9, Page 2761, vol. 9, no. 13, p. 2761, Jul. 2019, doi: 10.3390/APP9132761.

O. Heranova, “Synthetic Minority Oversampling Technique pada Averaged One Dependence Estimators untuk Klasifikasi Credit Scoring,” J. RESTI (Rekayasa Sist. dan Teknol. Informasi), vol. 3, no. 3, pp. 443–450, Dec. 2019, doi: 10.29207/RESTI.V3I3.1275.

D. Elreedy and A. F. Atiya, “A Comprehensive Analysis of Synthetic Minority Oversampling Technique (SMOTE) for handling class imbalance,” Inf. Sci. (Ny)., vol. 505, pp. 32–64, Dec. 2019, doi: 10.1016/J.INS.2019.07.070.

L. Swastina, “Penerapan Algoritma C4. 5 Untuk Penentuan Jurusan Mahasiswa,” J. Gema Aktual, vol. 2, no. 1, pp. 93–98, 2013, Accessed: Apr. 12, 2023. [Online]. Available: https://www.academia.edu/download/36752763/Penerapan_Algoritma_C4.5_Untuk_Penentuan_Jurusan_Mahasiswa.pdf

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Published

2023-06-28

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