Abstract
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.
Highlights
Determination of graduation status is often faced by lecturers in every university
This study aims to develop an analytical model in the process of determining student graduation using the Hybrid Decision Support System (DSS)
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%
Summary
Tabel 1 Menjelaskan bahwa kriteria yang digunakan dalam penilaian diinisialisasi dengan kode C1, C2, C3, C4, C5, C6, C7, C8, C9, dan C10. Yang satu lebih penting dari elemen lainnya. Satu elemen jelas lebih mutlak penting dari pada elemen lainnya. Pengalaman dan penilaian sangat kuat menyokong satu elemen dibandingkan elemen yang lainnya. Jika untuk aktivitas i mendapatkan satu angka dibanding dengan aktivitas j, maka j mempunyai nilai kebalikannya dibandingkan dengan i 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. Jika nilai rasio consistency (CR) ≤ 0,1 maka penilaian yang dilakukan adalah konsisten, dengan menggunakan Persamaan 1&2 [35]: dengan i = 1, 2, 3, ..., m; dan j = 1, 2, 3, ..., n; dimana vij adalah elemen dari matriks keputusan yang ternormalisasi terbobot V. wij adalah bobot dari kriteria ke-j.
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