SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN KOTA SURAKARTA SEBAGAI TEMPAT STUDI LANJUT BAGI CALON MAHASISWA BARU
Keywords:
Decision Support System, College Selection, Analytical Hierarchy Process, Prospective Students, WebqualAbstract
According to (Edra, 2019) in a post in Ruang Guru, Surakarta is the first choice of city for studying and is quite ogled by many prospective students because it has several campuses with good standards and also the cost of living is not high. According to data from the Central Java Statistics Agency, Surakarta has 43 universities. Further studies at the university level are very important in education. However, many prospective students are confused about choosing a university that fits the criteria of prospective students.
Therefore, a system is needed that can provide decisions to support decisions in selecting universities at Surakarta according to the criteria for prospective students. The Decision Support System for Selection of Higher Education in Surakarta uses the Analytical Hierarchy Process (AHP) method to carry out the decision-making process and improve the quality of decisions to reduce errors in college selection.
There are 30 AHP training data from respondents of high school students equivalent with the results of the ranking of the Islam Batik University appearing 17 times, Slamet Riyadi University 4 times, and Setia Budi University appearing 3 times. Testing of this decision support system website is carried out using the webqual method. The results of testing the DSS system with 36 respondents show that the X1 (Usability Quality) variable has a value of t count < t table that is 1.139 < 2.037, so it can be concluded that the H1 hypothesis is not accepted. It means that there is no effect of X1 (Usability Quality) on Y (Overall View of The Website). Testing the variable X2 (Information Quality) has a value of t count > t table that is 3.151 > 2.037, so it can be concluded that the H2 hypothesis is accepted. It means the effect of X2 (Information Quality) on Y (Overall View of The Website). Testing the X3 (Service Interaction) variable has a t count < t table with 0.1517 < 2.037, so it can be concluded that the H3 hypothesis is not accepted, and it means that there is no effect of X3 (Service Interaction) on Y (Overall View of The Website).