Simulation Technique in Determining Student Attendance Using The Monte Carlo Method
Klara Bonita Madao(1*), I Gusti Ayu Ngurah Kade Sukiastini(2), Engelina Prisca Kalensun(3)
(1) Computer Engineering Study Program; STMIKAgamua Wamena, Papua
(2) Computer Engineering Study Program; STMIKAgamua Wamena, Papua
(3) Information Systems Study Program; STMIKAgamua Wamena, Papua
(*) Corresponding Author
Abstract
In lectures, attendance is one of the assessment points that play an important role in determining a student's graduation. When a student is in the upper semester their attendance rate at lectures starts to decrease. The attendance prediction simulation is an estimate of the calculation of student attendance in lectures. This type of research is quantitative research using data collection techniques using observation and documentation study. In the process of analysis, the observed data were attendance data of 5th-semester computer engineering study program students and a sample of 83 people as research subjects. The stages of the monte carlo simulation are used: Determining variable frequency; Calculating cumulative probabilities; Determining random number intervals; Creating a simulation to determine student attendance; Generating random numbers; Make a simulation of the experimental circuit. The simulation is carried out by comparing and entering random numbers that have been generated into a comparison simulation of attendance and absence data for 5th-semester computer engineering study program students at the STMIK Agamua Wamena Papua Campus, starting from October 3 to October 31, 2022. Based on a series of experimental data that has The simulation results obtained predicted attendance and absence of computer engineering study program students at the STMIK Agamua Wamena campus from November 7 to December 19, 2022 with an average attendance of above 50%.
Keywords
Full Text:
PDFReferences
[1] H. Iftitah and Y. Yunus, “Prediksi Tingkat Penerimaan Lulusan Siswa Kejuruan dalam Dunia Usaha dan Industri Menggunakan Metode Monte Carlo,” J. Sistim Inf. dan Teknol., vol. 2, no. 3, pp. 84–89, 2020, doi: 10.37034/jsisfotek.v2i3.27.
[2] L. G. Suhaidir, Sumijan, and Y. Yunus, “Prediksi Tingkat Pemahaman Siswa terhadap Data Nominatif Menggunakan Metode Monte Carlo,” J. Sistim Inf. dan Teknol., vol. 2, no. 3, pp. 90–95, 2020.
[3] E. Novalia, J. Na’am, G. W. Nurcahyo, and A. Voutama, “Website Implementation with the Monte Carlo Method as a Media for Predicting Sales of Cashier Applications,” vol. 2, no. 3, pp. 118–131, 2020.
[4] R. Y. Astia, J. Santony, and Sumijan, “Prediction Of Amount Of Use Of Planning Family Contraception Equipment Using Monte Carlo Method ( Case Study In Linggo Sari Baganti District ) Prediction Of Amount Of Use Of Planning Family Contraception Equipment Using Monte Carlo Method ( Case Study In,” Indones. J. Artif. Intell. Data Min., no. April, 2019, doi: 10.24014/ijaidm.v2i1.5825.
[5] F. Dharma, Shabrina, A. Noviana, M. Tahir, N. Hendrastuty, and Wahyono, “Prediction of Indonesian Inflation Rate Using Regression Model Based on Genetic Algorithms,” JOIN (Jurnal Online Inform., vol. 5, no. 1, pp. 45–52, 2020, doi: 10.15575/join.
[6] S. H. Suryawan, N. R. Fadhliana, A. J. Latipah, Y. T. Kusumawati, and A. Saputra, “Prediksi permintaan pupuk kompos pada umkm sukses sehati menggunakan metode monte carlo,” J. Sains Terap. Teknol. Inf., vol. 14, no. 2, pp. 67–72, 2022.
[7] H. D. Hutahaean, “ANALISA SIMULASI MONTE CARLO UNTUK MEMPREDIKSI TINGKAT KEHADIRAN MAHASISWA DALAM PERKULIAHAN (studi Kasus : STMIK PELITA NUSANTARA),” J. Inform. Pelita Nusant., vol. 3, no. 1, pp. 41–45, 2018.
[8] D. A. Kaligis, “Monitoring Perkuliahan Mahasiswa Mata Kuliah Arsitektur Komputer Menggunakan Monte Carlo,” Musamus J. Res. Inf. Commun. Technol., vol. 1, no. 2, pp. 69–74, 2019.
[9] E. Desi and S. Aliyah, “Perancangan Sistem Absensi Berbasis Web Untuk Memprediksi Tingkat Kehadiran Mahasiswa Dengan Metode Monte Carlo,” J. Tek. Inform., vol. 04, no. 02, pp. 10–18, 2020.
[10] K. Alfikrizal, “Simulasi Monte Carlo dalam Prediksi Jumlah Penumpang Angkutan Massal Bus Rapid Transit Kota Padang,” J. Inform., vol. 3, no. 2, pp. 78–82, 2021, doi: 10.37034/infeb.v3i2.72.
[11] R. Darnis, G. Widi Nurcahyo, and Y. Yunus, “Simulasi Monte Carlo untuk Memprediksi Persediaan Darah,” J. Teknol. dan Inf., vol. 2, no. 4, pp. 139–144, 2020.
[12] S. D. Anggraini and G. W. Nurcahyo, “Prediksi Peningkatan Jumlah Pelanggan dengan Simulasi Monte Carlo,” J. Inform. Ekon. Bisnis, vol. 3, no. 3, pp. 95–100, 2021.
[13] D. N. Hasnah, D. Andriani, E. Sahpitri, and Z. R. A. Harahap, “MONTE CARLO SIMULATION IN PREDICTING THE SPREAD OF COVID-19,” J. Math. Sci. Comput. with Appl., vol. 2, no. December 2019, pp. 28–34, 2021.
[14] S. A. Putri, B. Subartini, and Sukono, “The Use of Quasi Monte Carlo Method with Halton Random Number Sequence in Determining the Price of European Type Options ( Case in PT Telekomunikasi Indonesia Stock ’ s ),” Int. J. Glob. Oper. Res., vol. 3, no. 4, pp. 116–124, 2022.
[15] M. Apri, D. Aldo, and Hariselmi, “SIMULASI MONTE CARLO UNTUK MEMPREDIKSI JUMLAH KUNJUNGAN PASIEN,” 2019.
[16] E. Frinosta, “Optimalisasi Penggunaan Anggaran dalam Menunjang Proses Tri Darma Pendidikan pada Perguruan Tinggi,” J. Inform. Ekon. Bisnis, vol. 3, no. 3, pp. 83–88, 2021, doi: 10.37034/infeb.v3i3.78.
[17] J. Santony, “Simulasi Penjadwalan Proyek Pembangunan Jembatan Gantung dengan Metode Monte Carlo,” J. Inf. Teknol., vol. 2, pp. 36–42, 2020, doi: 10.37034/jidt.v2i1.34.
[18] G. H. D. Sinaga, S. A. Purba, and A. F. Simanullang, “Coulomb Stress Analysis And Monte Carlo Simulation In Predicting Sinabung Pyroclastic Flow,” World J. Adv. Res. Rev., no. 7, 2022.
[19] R. R. Margana, “SIMULATION OF MONTE CARLO TO PREDICT WRITING PRODUCTION CAPACITY IN PT . SINAR DUNIA,” PalArch’s J. Archaeol. Egypt/Egyptology, vol. 17, no. 10, pp. 1977–1984, 2020.
[20] H. Ramadan, P. U. Gio, and E. Rosmaini, “Monte Carlo Simulation Approach to Determine the Optimal Solution of Probabilistic Supply Cost,” J. Res. Math. Trends Technol., vol. 2, no. 1, pp. 1–6, 2020, doi: 10.32734/jormtt.v2i1.3752.
[21] F. A. Nasution, “Simulasi Monte Carlo Dalam Penentuan Tingkat Kedatangan Pengunjung ( Studi Kasus di Happy Kiddy Rantauprapat ),” J. Comput. Sci. Inf. Technol., vol. 3, no. 1, pp. 43–53, 2022.
[22] M. Aziz, Z. Ilmi, Y. P. Hakim, D. C. Darma, and M. Qodri, “‘ Monte Carlo Simulation ’ Predicting on the Movement of Investments – During the Covid Pandemic in Indonesia Prediksi Simulasi ‘ Monte Carlo ’ untuk Pergerakan Investasi – Selama,” J. Din. Manaj., vol. 12, no. 85, pp. 262–274, 2021.
[23] D. Ferdinal, S. Defit, and Y. Yunus, “Prediksi Bed Occupancy Ratio (BOR) Menggunakan Metode Monte Carlo,” J. Inf. dan Teknol., vol. 3, no. 1, pp. 1–9, 2020, doi: 10.37034/jidt.v3i1.80.
[24] Z. U. Rizqi, A. Khairunisa, and A. Maulani, “Financial Assessment on Designing Inventory Policy by Considering Demand , Lead Time , and Defective Product Uncertainties : A Monte Carlo Simulation,” Indones. Sch. Sci. Summit Taiwan Proceeding, pp. 36–42, 2021.
[25] I. Pamungkas, Arhami, and M. Dirhamsyah, “Monte Carlo simulation for predicting the reliability of a boiler in the Nagan Raya steam power plant Monte Carlo simulation for predicting the reliability of a boiler in the Nagan Raya steam power plant,” IOP Conf. Ser. Mater. Sci. Eng., pp. 4–10, 2019, doi: 10.1088/1757-899X/523/1/012071.
DOI: https://doi.org/10.22146/ijccs.83891
Article Metrics
Abstract views : 1327 | views : 1127Refbacks
- There are currently no refbacks.
Copyright (c) 2023 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