Kajian Model Prediksi Ketepatan Kelulusan Mahasiswa: Sebuah Literatur Review

Heryana, Nono; Ghassani, Fildzah Zia; Usrahmawan, Muhammad Andhika; Juardi, Didi; Solehudin, Arip

doi:10.35706/syji.v9i1.3388

Cited by 4 publications

(5 citation statements)

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“…Dalam proses menempuh pendidikan akan banyak ditemukan kendala, dari kendala-kendala ini diharapkan pelajar atau mahasiswa dapat menerapkan ilmu yang didapatkannya dan menemukan solusi untuk menyelesaikannya. Selain ilmu pengetahuan, hal lain yang didambakan pelajar atau mahasiswa adalah dapat lulus dengan tepat waktu (Heryana et al, 2020) Ketepatan waktu lulus ini merupakan impian dari mahasiswa, sebagai wujud atau bentuk dari perjuangan mereka selama beberapa tahun belajar di bangku kuliah. Selain ketepatan waktu kuliah ini penting bagi mahasiswa, penting juga bagi perguruan tinggi, hal ini disebabkan karena aspek kelulusan mahasiswa merupakan salah satu aspek penilaian dalam sebuah proses akreditasi institusi suatu perguruan tinggi untuk menunjukan kualitasnya (S.A Amosea, 2021) Kualitas dari perguruan tinggi ini dapat dilihat dari banyak aspek, selain dilihat dari rata-rata lama waktu alumninya mendapatkan pekerjaan, aspek penilaian lainnya yang tak kalah penting adalah presentase ketepatan waktu lulus dari mahasiswanya (Jananto, 2021) Jumlah besar persentase mahasiswa yang bisa menuntaskan masa study tepat waktu akan membuat tingkat evaluasi akreditasi naik.…”

Section: Pendahuluanunclassified

Penerapan Teknik Random Oversampling Untuk Memprediksi Ketepatan Waktu Lulus Menggunakan Algoritma Random Forest

Diantika,

Nalatissifa,

Maulidah

et al. 2024

co-science

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Punctuality of graduation is something that students yearn for, besides being important for students, punctuality of graduation is also very important for universities, this is because the aspect of student graduation is one aspect of assessment in an institutional accreditation process of a university to show its quality. One of the obstacles faced to find out whether a student can graduate on time or not is because the study period cannot be detected early, this will have an impact on late student graduation. To analyze this, a lot of research was conducted on the accuracy of student graduation, through the cumulative grade point average (GPA) obtained by students during their studies. This research on the prediction of student graduation timeliness uses a random forest algorithm model. The data used in this research object has an unbalanced number of data classes, to overcome this, a random oversampling (ROS) resampling technique is applied and also applies Split validation or division between learning data by 50% for test data and 50%. To evaluate the model built, the author uses evaluation metrics such as accuracy, recall, and precision. The results of the study showed that the proposed model can well predict compared to other models, namely with the results precision of 87.05%, accuracy test values of 90.04%, recall of 90.04%.From these results, it can be interpreted that the random forest algorithm is considered good in predicting the timeliness of a student's graduation

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Section: Pendahuluanunclassified

Penerapan Teknik Random Oversampling Untuk Memprediksi Ketepatan Waktu Lulus Menggunakan Algoritma Random Forest

Diantika,

Nalatissifa,

Maulidah

et al. 2024

co-science

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“…Sedangkan tujuan dari metode ini adalah sama dengan regresi linear yaitu memperoleh model prediksi yang baik dengan ditunjukkan dengan tingkat akurasi yang rendah. Pemodelan prediksi keberhasilan mahasiswa dibutuhkan demi mengetahui apakah sistem pembelajaran yang dilakukan sudah cukup baik atau tidak (Guswandi et al, 2021;Heryana et al, 2020).…”

Section: Pendahuluanunclassified

Pengujian akurasi model regresi logistik multinomial untuk memprediksi keberhasilan mahasiswa di perguruan tinggi menggunakan r

Baskoro

Suhartono

Chamidy

et al. 2022

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Higher education institute should have maintained its student’s success in their academic field. Therefore, higher education institute should make a model to predict its success as early as possible. To have such model, the impacting factors should be determined, which factor are in the forms of continuous dan categorized data. This research is aimed to build logistic regression model based on compounded data from continuous and categorized data, which then test the model accuracy to predict the student’s success in such institute. Research data is using 68 student’s data. There are 6 research steps, first, data preparation and collection, second, data analysis, third, building the logistic multinomial regression model, fourth, data testing and validation, fifth, measure the model accuracy, and the sixth step is drawing the conclusion based on the analysis output. The result of prediction analysis dan accuracy test using logistic multinomial regression is the best model with significant factors that influence the study time are gender, department and selection track, while prediction accuracy model for each study time response variable is 96.4%.

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“…5 No. 6 (2021) 1127 -1136 DOI: https://doi.org/10.29207/resti.v5i6.3587 Lisensi: Creative Commons Attribution 4.0 International (CC BY 4.0) 1128 analisis yang digunakan sebagai alat dalam sebuah pengambilan keputusan [4].…”

Section: Pendahuluanunclassified

“…Adapun variable indikator yang digunakan dapat dilihat pada Tabel 1. (4) dengan i = 1, 2, 3, ..., m; dan j = 1, 2, 3, ..., n; dimana 𝑟𝑖𝑗 adalah elemen dari matriks keputusan yang ternormalisasi R. 𝑥𝑖𝑗 adalah elemen matriks dari keputusan X.…”

Section: Metodologi Penelitianunclassified

Analisis Hybrid Decision Support System dalam Penentuan Status Kelulusan Mahasiswa

Guswandi

Yanto

Hafizh

et al. 2021

RESTI

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Determination of graduation status is often faced by lecturers in every university. The facts show that many of the decisions still have a fairly high error rate in determining graduation status. This study aims to develop an analytical model in the process of determining student graduation using the Hybrid Decision Support System (DSS). The methods used in the analysis process are Analytical Hierarchy Process (AHP) and Technique for Others Preference by Similarity to Ideal Solution (TOPSIS). The performance of AHP can determine the value of the weight criteria and TOPSIS performs rankings to produce solutions in determining. The criteria indicators used to consist of Depth (C1), Material Breadth (C2), Answer Accuracy (C3), Fluency of Answers (C4), Scientific Attitude (C5), Logical Consistency of Content (C6), Authenticity (C7), Scientific Quality ( C8), Language (C9), and Writing (C10). The results of this study indicate that the Analytical Hierarchy Process (AHP) method provides a weighting value for each criterion with a fairly good accuracy rate of 85,86%. These results conclude that each criterion has a consistent level of relationship in determining student graduation. Based on the output of the TOPSIS analysis, the results presented can determine the student's graduation status correctly and accurately.

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Kajian Model Prediksi Ketepatan Kelulusan Mahasiswa: Sebuah Literatur Review

Cited by 4 publications

References 0 publications

Penerapan Teknik Random Oversampling Untuk Memprediksi Ketepatan Waktu Lulus Menggunakan Algoritma Random Forest

Penerapan Teknik Random Oversampling Untuk Memprediksi Ketepatan Waktu Lulus Menggunakan Algoritma Random Forest

Pengujian akurasi model regresi logistik multinomial untuk memprediksi keberhasilan mahasiswa di perguruan tinggi menggunakan r

Analisis Hybrid Decision Support System dalam Penentuan Status Kelulusan Mahasiswa

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