Prediksi Predikat Kelulusan Mahasiswa dengan Rantai Markov dan Faktor-Faktor yang Mempengaruhi Indeks Prestasi Mahasiswa - Arfarani Rosalindari; Sufri Sufri; Gusmi Kholijah (AlphaMath : Journal of Mathematics Education, 2021)
Students' Achievement Index (IP) changes each semester, both increase and decrease. This affects the GPA obtained by graduation. IP obtained by students in even semester is only influenced by IP in odd semester. Based on nature of Markov Chain, if there are past and future events, then future events are independent of past events and only tied to current events. Markov chain is used to analyze probability of IP change each semester and to predict the predicate of graduation with state space used, namely: satisfactory predicate with GPA of 2.00 - 2.75 to state 0, satisfactory predicate with GPA of 2.76 - 3, 24 becomes state 1, predicate is very satisfactory with GPA of 3.25 - 3.79 being state 2, and cumlaude predicate with GPA of 3.80 - 4.00 being state 3. This study aims to predict the predicate of student graduation and to analyze factors that have significant effect on IP. Dummy regression is used to analyze factors that have significant effect on IP with the factors studied, namely: campus facilities and infrastructure, friendship, organizational activeness, internet use, and money. Results showed that predicate of graduation with satisfactory predicate, GPA range of 2.00-2.75 was 0.56%, students who graduated with satisfactory predicate GPA range 2.76-3.24 was 7.39%, students who graduated with very satisfactory predicate, GPA ranges 3.25-3.79 was 54.18%, and students who graduated with cumlaude predicate ranged from GPA 3.80-4.00 was 37.87%. Factors that have significant effect on student GPA are activeness in the organization and use of the internet.