STRATEGY FOR PREDICTING GRADUATION RATES OF MUHAMMADIYAH PONOROGO UNIVERSITY STUDENTS USING FUZZY TSUKAMOTO THEORY

Ranti Kurniasih (1), Annafi Awantagusnik (2), Muhammad Zia Alghar (3)
(1) Muhammadiyah University of Ponorogo, Indonesia,
(2) Universitas Al-Qolam Malang, Indonesia,
(3) State University og Malang, Indonesia

Abstract

The purpose of this research is to create a mathematical model related to fuzzy logic to predict student graduation rates starting in 2024. This type of research is applied research. The method used is the tsukamoto method in fuzzy analysis and checking the accuracy of forecasting with MAPE. Data collection techniques are carried out by collecting primary data and secondary data. The primary data used is data on new student admissions, many graduates, and many graduates from Muhammadiyah Ponorogo University in 2021, 2022, and 2023. Secondary data is obtained from books, articles, and documents relevant to Tsukamoto fuzzy. The results of the Tsukamoto fuzzy analysis with MAPE testing show that the fuzzy model built is at a percentage of 5.3%. This means that the fuzzy system has excellent forecasting capabilities in predicting student graduation rates in 2021, 2022, and 2023 and can be used to predict many graduates in 2024.

Full text article

Generated from XML file

References

Arifin, Muhammad Zainul, and Mega Nuris Salafinah. 2020. “Implementasi Teori Fuzzy Tsukamoto Untuk Memprediksi Tingkat Kelulusan Mahasiswa Institut Agama Islam Negeri Jember.” Aritmatika: Jurnal Riset Pendidikan Matematika 1(1): 22–35.

Asriningtias, Yuli, and Rodhyah Mardhiyah. 2014. “Aplikasi Data Mining Untuk Menampilkan Informasi Tingkat Kelulusan Mahasiswa.” Jurnal Informatika 8(1): 837–48.

Basriati, Sri, Elfira Safitri, and Putri Nofridayani. 2020. “Penerapan Metode Fuzzy Tsukamoto Dalam Menentukan Jumlah Produksi Tahu.” Jurnal Sains, Teknologi dan Industri 18(1): 120.

Bede, Barnabas. 2013. Mathematics of Fuzzy Sets and Fuzzy Logic. Berlin: Springer.

Chang, Pei Chann, Yen Wen Wang, and Chen Hao Liu. 2007. “The Development of a Weighted Evolving Fuzzy Neural Network for PCB Sales Forecasting.” Expert Systems with Applications 32(1): 86–96.

Kusumadewi, Sri, and Hari Purnomo. 2010. Aplikasi Logika Fuzzy Untuk Pendukung Keputusan. Yogyakarta: Graha Ilmu.

Masui, Chris et al. 2014. “Do Diligent Students Perform Better? Complex Relations between Student and Course Characteristics, Study Time, and Academic Performance in Higher Education.” Studies in Higher Education 39(4): 621–43.

Mulyatiningsih, Endang. 2011. Riset Terapan Bidang Pendidikan Dan Teknik. Yogyakarta: UNY press.

Plant, E Ashby, K Anders Ericsson, Len Hill, and Kia Asberg. 2005. “Why Study Time Does Not Predict Grade Point Average across College Students: Implications of Deliberate Practice for Academic Performance.” Contemporary educational psychology 30(1): 96–116.

Rindengan, Altien J, and Yohanes A R Langi. 2019. Sistem Fuzzy. Bandung: CV. Patra Media Grafindo.

Setiawan, Agung, Budi Yanto, and Kiki Yasdomi. 2018. Logika Fuzzy Dengan Matlab (Contoh Kasus Penelitian Penyakit Bayi Dengan Fuzzy Tsukamoto). Denpasar: Jayapangus Press Books. http://book.penerbit.org/index.php/JPB/article/view/122.

Setiyawan, Dio, Arbansyah Arbansyah, and Asslia Johar Latipah. 2023. “Fuzzy Inference System Metode Tsukamoto Untuk Penentuan Program Studi Fakultas Sains Dan Teknologi Di Universitas Muhammadiyah Kalimantan Timur.” Jurnal Informatika dan Komputer 7(1).

Sihaloho, Tulus Pramita, Mahyuddin K M Nasution, and Zakarias Situmorang. 2020. “Level of Student Satisfaction on Lecturer Performance with Fuzzy Inference System (FIS) Tsukamoto Method.” IOP Conference Series: Materials Science and Engineering 725(1): 12130.

Vivas, Eliana, Héctor Allende-Cid, and Rodrigo Salas. 2020. “A Systematic Review of Statistical and Machine Learning Methods for Electrical Power Forecasting with Reported Mape Score.” Entropy 22(12): 1412.

Zadeh, Lotfi Asker. 1965. “Fuzzy Sets.” Information and control 8(3): 338–53.

Authors

Ranti Kurniasih
rantikurniasih@umpo.ac.id (Primary Contact)
Annafi Awantagusnik
Muhammad Zia Alghar
Author Biography

Ranti Kurniasih, Muhammadiyah University of Ponorogo

S1 : State University Of Malang

S2 : State University Of Malang

Kurniasih, R., Awantagusnik, A., & Zia Alghar, M. (2024). STRATEGY FOR PREDICTING GRADUATION RATES OF MUHAMMADIYAH PONOROGO UNIVERSITY STUDENTS USING FUZZY TSUKAMOTO THEORY. MUST: Journal of Mathematics Education, Science and Technology, 9(1). https://doi.org/10.30651/must.v9i1.22830

Article Details

Similar Articles

1 2 3 4 > >> 

You may also start an advanced similarity search for this article.