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Factors Influencing the Study Period of Students of the Mathematics Study Program at Udayana University Ulfatun Farika Novitasari; Adinda Audy Sita Mayzandy; Miltiades Dewifortuna Pulo; Juliani Tandi Tumbiri; Nurul Ilma; Made Susilawati
International Journal of Applied Mathematics and Computing Vol. 2 No. 1 (2025): January: International Journal of Applied Mathematics and Computing
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijamc.v2i1.92

Abstract

The student study period is one of the important aspects to measure the quality of a higher education institution. The length of the student study period can be assumed to come from internal factors and external factors, so it is necessary to conduct research that aims to identify and model the factors that affect the student study period. The method used in this research is logistic regression and the data used is primary data obtained from distributing questionnaires. The target of this research is aimed at alumni students from the Mathematics Study Programme of Udayana University from 2011 to 2019. In this study, the best model produced has a classification accuracy of 98.17% and the independent variables that have a significant effect on the study period are gender, tuition fees and interest in majors.
Penentuan Probabilitas Perubahan Nilai Dari Mata Kuliah Prasyarat Statistika Matematika Ii Menggunakan Proses Rantai Markov I Putu Eka Suarsa; Made Novita Dewi; Ni Kade Hindu Pertiwi; Ulfatun Farika Novitasari; Dyan Ayu Wijayanti; I Gusti Ayu Made Srinadi; Made Ayu Dwi Octavanny
Konstanta : Jurnal Matematika dan Ilmu Pengetahuan Alam Vol. 2 No. 2 (2024): Juni : Jurnal Matematika dan Ilmu Pengetahuan Alam
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59581/konstanta.v2i2.3183

Abstract

This research aims to determine the probability of changes in grades from the prerequisite course Mathematical Statistics II using the Markov chain process method. Prerequisite courses are an important component in the higher education curriculum, because they influence student success in advanced courses. In this study, student grade data was collected and analyzed to map the transition between grade categories from one semester to the next. The Markov chain model is applied to predict patterns of value change, with the assumption that the future state of value depends only on the current state. It is hoped that the results of this research will provide insight into the pattern of grade transition, assist in academic decision making, and identify factors that contribute to an increase or decrease in student performance. Thus, this study can contribute to improving learning strategies and more effective academic policies.
Penerapan Metode Saw dan Topsis pada Pemilihan Lokasi Kuliner di Kota Denpasar Ulfatun Farika Novitasari; Eka N. Kencana; I GN Lanang Wijayakusuma
Konstanta : Jurnal Matematika dan Ilmu Pengetahuan Alam Vol. 2 No. 4 (2024): Desember : Jurnal Matematika dan Ilmu Pengetahuan Alam
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59581/konstanta.v2i4.4193

Abstract

Bali is a renowned tourist destination that attracts visitors from around the world, particularly for its natural beauty, rich culture, and delicious cuisine. The increasing number of tourists in Bali has driven rapid growth in the culinary industry. In Denpasar City, selecting the right location is a key factor for the success of culinary businesses, as each location has different characteristics and potentials. This study employs the Multiple Attribute Decision Making (MADM) model, combining the Simple Additive Weighting (SAW) and Technique for Orders Preference by Similarity to Ideal Solution (TOPSIS) methods, to determine the optimal location for culinary businesses in Denpasar City. Data were collected through surveys of 154 culinary business owners, considering eight criteria: Accessibility, Visibility, Traffic, Facilities, Expansion, Environment, Competition, and Regulations. The study's findings indicate that both SAW and TOPSIS methods identify high population density areas as the best choice. The SAW and TOPSIS method provides the highest preference value of 0,8815 and 0.7082 respectively, making it the more effective method for recommending optimal culinary locations in Denpasar City.