Fuzzy Logic to Determine the Effect of Parental Attention and Peer Environment on Mathematics Learning Outcomes

Authors

  • Supratman Universitas Sembilanbelas November Kolaka
  • Andi Mariani Ramlan Universitas Sembilanbelas November Kolaka
  • Raden Sulaiman Universitas Negeri Surabaya

DOI:

https://doi.org/10.55927/ijsmr.v1i7.5361

Keywords:

Fuzzy Logic, Parental Attention, Peer Environment, Mathematics Learning Outcomes

Abstract

The results of learning mathematics is a process of changing new behavior which is the result of giving experiences received by students in the learning process which includes cognitive, affective, and psychomotor aspects whose success can be measured through written and oral tests. The learning outcomes achieved can be good or bad depending on the factors that influence them, including learning motivation and environmental factors study. This study aims to determine the effect of parental attention and peer environment on student learning outcomes at SMA Negeri 1 Kolaka in 2022 using the Fuzzy logic of the Tsukamoto method. The data obtained in this study came from a questionnaire for the attention of parents and peers that had been filled out by students as well as mathematics learning outcomes obtained through the results of the even semester 2022 daily test scores. Based on the research results obtained in fuzzy calculations consisting of people's attention questionnaires parents and peer environment, it was found that the mathematics learning outcomes achieved were not good at 34.87 towards good mathematics learning outcomes at 65.12.

Downloads

Download data is not yet available.

References

Abidah, S. (2016). Analisis Komparasi Metode Tsukamoto dan Sugeno dalam Prediksi Jumlah Siswa Baru. Journal Speed – Sentra Penelitian Engineering dan Edukasi, 8(2), 1–8.

Astuti, D. P. P., & Mashuri. (2020). Penerapan Metode Fuzzy Tsukamoto dan Fuzzy Sugeno dalam Penentuan Harga Jual Sepeda Motor. UNNES Journal of Mathematics, 9(2), 74–78.

Ayuningtias, L. P., Irfan, M., & Jumadi. (2017). Analisa Perbandingan Logic Fuzzy Metode Tsukamoto, Sugeno, dan Mamdani (Studi Kasus : Prediksi Jumlah Pendaftar Mahasiswa Baru Fakultas Sains dan Teknologi Universitas Islam Negeri Sunan Gunung Djati Bandung). JURNAL TEKNIK INFORMATIKA, 1(April), 9–16.

Carlsson, C., & Fuller, R. (2001). Optimization under fuzzy if – then rules. Fuzzy Sets and Systems, 119, 111–120.

Danish, E., & Onder, M. (2020). Application of Fuzzy Logic for Predicting of Mine Fire in Underground Coal Mine. Safety and Health at Work, 11(3), 322–334. https://doi.org/10.1016/j.shaw.2020.06.005

Fauzyah, R. (2019). Pengaruh Kelompok Teman Sebaya dan Perhatian Orang Tua Terhadap Motivasi Belajar Peserta Didik. Jurnal Informasi dan Komunikasi Administrasi Perkantoran, 3(1), 19–36.

Gupta, P. K., & Muhuri, P. K. (2019). Extended Tsukamoto’s inference method for solving multi-objective linguistic optimization problems. Fuzzy Sets and Systems, 1, 1–23. https://doi.org/10.1016/j.fss.2019.02.022

Kaswidjanti, W., Aribowo, A. S., & Wicaksono, C. B. (2014). Implementasi Fuzzy Inference System Metode Tsukamoto Pada Pengambilan Keputusan Pemberian Kredit Pemilikan Rumah. TELEMATIKA, 10(2), 137–146.

Kusumadewi, S. (2004). Penentuan Tingkat Resiko Penyakit Menggunakan Tsukamoto Fuzzy Inference System. SEMINAR NASIONAL II: THE APPLICATION OF TECHNOLOGY TOWARD A BETTER LIFE, 19–25.

Mitrofani, I. Α., Emiris, D. M., & Koulouriotis, D. E. (2021). An Industrial Maintenance Decision Support System based on Fuzzy Inference to Optimize Scope Definition. Procedia Manufacturing, 51(2019), 1538–1543. https://doi.org/10.1016/j.promfg.2020.10.214

Parwata, K. Y. L., Sudiatmika, A. A. I. A. R., & Devi, N. L. P. L. (2018). Pengaruh Teman Sebaya, Orang Tua, dan Guru Terhadap Masalah Belajar Anak Superior. JPPSI: Jurnal Pendidikan dan Pembelajaran Sains Indonesia, 1(April), 1–11.

Purnomo, R., Priatna, W., & Fathurrozi, A. (2019). Perbandingan Logika Fuzzy dan Analytic Hierarchy Process untuk Menilai Kinerja Dosen. Jurnal Teknologi Informasi ESIT, XIV(1), 48–59.

Ragestu, F. D., & Sibarani, A. J. P. (2020). Penerapan Metode Fuzzy Tsukamoto Dalam Pemilihan Siswa Teladan di Sekolah. TEKNIKA, 9(1), 9–15. https://doi.org/10.34148/teknika.v9i1.251

Rahmadi, M. A., & Mustafidah, H. (2014). Sistem Inferensi Fuzzy untuk Mengetahui Pengaruh Motivasi Belajar dan Lingkungan Belajar terhadap Prestasi Belajar Mahasiswa. Juita, III(1), 19–24.

Tambunan, R. I. (2018). Pengaruh Perhatian Orang Tua dan Lingkungan Teman Sebaya Terhadap Prestasi Belajar Ekonomi. Liabilities Jurnal Pendidikan Akuntansi, 1(2), 112–124.

Ula, M. (2014). Implementasi Logika Fuzzy Dalam Optimasi Jumlah Pengadaan Barang Menggunakan Metode Tsukamoto (Studi Kasus : Toko Kain My Text). Jurnal ECOTIPE, 1(2), 36–46.

Wibowo, S. A., Mustafidah, H., Wicaksono, A. P., & Aryanto, D. (2013). Analisis Motivasi Belajar dan Kehadiran terhadap Nilai Kuliah Mahasiswa Menggunakan Teori Kuantifikasi Fuzzy (Analysis of Learning Motivation and the Attendance Against of Students Achievement Using Fuzzy Quantification Theory). JUITA, II(3), 175–181.

Wu, Y., Lur, Y., Wen, C., & Lee, S. (2021). Analytical method for solving max-min inverse fuzzy relation. Fuzzy Sets and Systems, 1(1), 1–21. https://doi.org/10.1016/j.fss.2021.08.019

Downloads

Published

2023-08-30

How to Cite

Supratman, Andi Mariani Ramlan, & Raden Sulaiman. (2023). Fuzzy Logic to Determine the Effect of Parental Attention and Peer Environment on Mathematics Learning Outcomes. International Journal of Scientific Multidisciplinary Research, 1(7), 813–832. https://doi.org/10.55927/ijsmr.v1i7.5361

Issue

Section

Articles