Forecasting the Number of Students in Multiple Linear Regressions
DOI:
https://doi.org/10.30812/matrik.v21i2.1348Keywords:
Big data, Data Mining, Multiple linear regressions, ForecastingAbstract
The most important element of higher education was students, therefore every university must continue to improve services in the future, and one of them was by using decision support. This case could be done by utilizing the University of Big Data. Predicting the number of prospective students in higher education was done by utilizing data mining and multiple linear regression approaches. By using 2 independent variables, namely administration costs (X1), accreditation score (X2), and the number of students who was registered each year as dependent variable (Y). For the test data, it used database for the last 13 years. By using multiple linear regression, the intercept value was sought and the coefficient of determination until the regression coefficient was obtained with the equation Y = 45.28 + -0.02.X1 + 121.58.X2, noted that if X2 was constant, the increasing of one unit was in X1 would have the effect of increasing -0.02 units on Y. Secondly, if X1 was constant, the increasing of one unit was in X2, would have the effect of increasing 121.58 units in Y. Thirdly, if X1 and X2 were equal to zero, the magnitude of Y was 45.28 units. Therefore, the proposed approach could be provided the acceptable predictive results.
Downloads
References
[2] B. Furht and F. Villanustre, “Big data technologies and applications,†Big Data Technol. Appl., pp. 1–400, 2016.
[3] R. Dautov and S. Distefano, “Quantifying volume, velocity, and variety to support (Big) data-intensive application development,†Proc. - 2017 IEEE Int. Conf. Big Data, Big Data 2017, vol. 2018-January, pp. 2843–2852, 2017.
[4] I. A. T. Hashem et al., “The role of big data in smart city,†Int. J. Inf. Manage., vol. 36, no. 5, pp. 748–758, 2016.
[5] T. M. Song and J. Song, “Prediction of risk factors of cyberbullying-related words in Korea: Application of data mining using social big data,†Telemat. Informatics, vol. 58, p. 101524, 2021.
[6] T. GajdoÅ¡Ãk, “Big Data Analytics in Smart Tourism Destinations. A New Tool for Destination Management Organizations?,†pp. 15–33, 2019.
[7] A. Gandomi and M. Haider, “Beyond the hype: Big data concepts, methods, and analytics,†Int. J. Inf. Manage., vol. 35, no. 2, pp. 137–144, 2015.
[8] D. Wang, X. Robert, and Y. Li, “China’s ‘Smart Tourism Destination’ Initiative : A Taste Of the Service-Dominant Logic,†J. Destin. Mark. Manag., vol. 2, no. 2, pp. 59–61, 2013.
[9] A. Yang, Y. Han, C.-S. Liu, J.-H. Wu, and D.-B. Hua, “D-TSVR Recurrence Prediction Driven by Medical Big Data in Cancer,†IEEE Trans. Ind. Informatics, vol. 3203, no. c, pp. 1–1, 2020.
[10] A. Dridi, M. M. Gaber, R. M. A. Azad, and J. Bhogal, “Scholarly data mining: A systematic review of its applications,†Wiley Interdiscip. Rev. Data Min. Knowl. Discov., no. October, pp. 1–23, 2020.
[11] Y. Ge and H. Wu, “Prediction of corn price fluctuation based on multiple linear regression analysis model under big data,†Neural Comput. Appl., vol. 32, no. 22, pp. 16843–16855, 2020.
[12] J. Hong, Z. Wang, W. Chen, L. Y. Wang, and C. Qu, “Online joint-prediction of multi-forward-step battery SOC using LSTM neural networks and multiple linear regression for real-world electric vehicles,†J. Energy Storage, vol. 30, no. February, p. 101459, 2020.
[13] K. L. L. Khine and T. T. S. Nyunt, Predictive big data analytics using multiple linear regression model, vol. 744. Springer Singapore, 2019.
[14] X. Xu, Z. Sun, L. Wang, J. Fu, and C. Wang, “A Comparative Study of Customer Complaint Prediction Model of Time Series, Multiple Linear Regression and BP Neural Network,†J. Phys. Conf. Ser., vol. 1187, no. 5, 2019.
[15] F. Wang, Z. Shi, A. Biswas, S. Yang, and J. Ding, “Multi-algorithm comparison for predicting soil salinity,†Geoderma, vol. 365, no. February 2019, p. 114211, 2020.
[16] H. Rawashdeh et al., “Intelligent system based on data mining techniques for prediction of preterm birth for women with cervical cerclage,†Comput. Biol. Chem., vol. 85, no. February, p. 107233, 2020.
[17] Y. S. Lee, J. R. Wang, J. W. Zhan, and J. M. Zhang, “Data Mining Analysis of Overall Team Information Based on Internet of Things,†IEEE Access, vol. 8, pp. 41822–41829, 2020.
[18] C. N. Burger, T. L. Grobler, and W. Kleynhans, “Discrete Kalman Filter and Linear Regression Comparison for Vessel Coordinate Prediction,†Proc. - IEEE Int. Conf. Mob. Data Manag., vol. 2020-June, no. Mdm, pp. 269–274, 2020.
[19] Y. S. Kong, S. Abdullah, D. Schramm, M. Z. Omar, and S. M. Haris, “Development of multiple linear regression-based models for fatigue life evaluation of automotive coil springs,†Mech. Syst. Signal Process., vol. 118, pp. 675–695, 2019.
[20] Bochumer Institut für Technologie GmbH, Data Science - Data Science, no. September 2016. 2018.
[21] Liu, C., Jin, R., Gong, E., Liu, Y., Yue, M., “Prediction for the Performance of Gas Turbine Units Using Multiple Linear Regression,â€Proc.- Of the Chinese Society of Electrical Engineering., vol. 37, pp. 4731-4738, Aug 2017.
[22] X. Li, H. Dong, and S. Han, “Multiple Linear Regression with Kalman Filter for Predicting End Prices of Online Auctions,†2020 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech), Aug. 2020.
Downloads
Published
Issue
Section
How to Cite
Similar Articles
- Vivin Nur Aziza, Utami Dyah Syafitri, Anwar Fitrianto, Optimizing Currency Circulation Forecasts in Indonesia: A Hybrid Prophet- Long Short Term Memory Model with Hyperparameter Tuning , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 24 No. 1 (2024)
- Sucipto Sucipto, Didik Dwi Prasetya, Triyanna Widiyaningtyas, Educational Data Mining: Multiple Choice Question Classification in Vocational School , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 23 No. 2 (2024)
- Fadhilah Dwi Ananda, Yoga Pristyanto, Analisis Sentimen Pengguna Twitter Terhadap Layanan Internet Provider Menggunakan Algoritma Support Vector Machine , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 20 No. 2 (2021)
- M Safii, Rika Setiana, Population Prediction Using Multiple Regression and Geometry Models Based on Demographic Data , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 24 No. 1 (2024)
- Rahmaddeni Rahmaddeni, M. Teguh Wicaksono, Denok Wulandari, Agustriono Agustriono, Sang Adji Ibrahim, Enhancing Multiple Linear Regression with Stacking Ensemble for Dissolved Oxygen Estimation , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 24 No. 1 (2024)
- Mamluatul Hani'ah, Moch Zawaruddin Abdullah, Wilda Imama Sabilla, Syafaat Akbar, Dikky Rahmad Shafara, Google Trends and Technical Indicator based Machine Learning for Stock Market Prediction , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 22 No. 2 (2023)
- Mardiana Mardiana, Eka Hartati, Analisis Pengukuran Tingkat Kepuasan Pengguna Terhadap Penerapan Aplikasi SISKEUDES Pada Kabupaten Banyuasin Sumatera Selatan , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 19 No. 1 (2019)
- Hadi Santoso, Hilyah Magdalena, Helna Wardhana, Aplikasi Dynamic Cluster pada K-Means BerbasisWeb untuk Klasifikasi Data Industri Rumahan , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 21 No. 3 (2022)
- Donny Kurniawan, Anthony Anggrawan, Hairani Hairani, Graduation Prediction System on Students Using C4.5 Algorithm , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 19 No. 2 (2020)
- Amir Ali, Klasterisasi Data Rekam Medis Pasien Menggunakan Metode K-Means Clustering di Rumah Sakit Anwar Medika Balong Bendo Sidoarjo , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 19 No. 1 (2019)
You may also start an advanced similarity search for this article.
Most read articles by the same author(s)
- Hengki Tamando Sihotang, Fristi Riandari, Pilisman Buulolo, Husain Husain, Sistem Pakar untuk Identifikasi Kandungan Formalin dan Boraks pada Makanan dengan Menggunakan Metode Certainty Factor , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 21 No. 1 (2021)
- Husain Husain, I Putu Hariyadi, Kurniadin Abd Latif, Galih Tri Aditya, Implementation of Port Knocking with Telegram Notifications to Protect Against Scanner Vulnerabilities , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 23 No. 1 (2023)
- Desi Vinsensia, Siskawati Amri, Jonhariono Sihotang, Hengki Tamando Sihotang, New Method for Identification and Response to Infectious Disease Patterns Based on Comprehensive Health Service Data , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 23 No. 3 (2024)
- Husain Husain, Pulung Nurtantio Andono, M. Arif Soeleman, Perspektif Baru Enterprise Architecture Pemerintahan Kota Mataram Berbasis TOGAF ADM , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 16 No. 2 (2017)
- Susandri susandri, Sarjon Defit, Fristi Riandari, Bosker Sinaga, Ekplorasi Timeline : Waktu Respon Pesan Terbaik WhatSapp Group “Gurauan kita STMIK Amik†, MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 20 No. 2 (2021)