The limited capacity of State Universities creates great opportunities for private universities. The private universities was established and even grew so fast when compared to the growth of State Universities. Even now, the number of private universities in Indonesia is more than ten times. Likewise with the development of private universities in North Sumatra Province, especially in the city of Medan.

The Medan is the provincial capital as well as the metropolitan city in North Sumatra Province as well as the surrounding provinces. So it's no wonder the city of Medan is the main attraction for prospective students in studying. There are so many private universities in the city of Medan City with the various advantages they display in attracting prospective students to study at their institutions. Based on data from Region I Higher Education Service Institutions in 2019, there are 144 private universities in the city of Medan, consisting of 48 Academies, 9 Polytechnics, 59 High Schools, 4 Institutes and 24 Universities.

A university is a college that provides education in many fields of science, both exact and social, so that the number of students is relatively higher compared to other levels. With 24 universities in the city of Medan, it causes various statuses starting from differences in accreditation, the diversity of study programs offered and the facilities provided by the private universities. From that difference, students must be observant in determining which private universities they will enter. Good accreditation is not a guarantee that it will increase the number of students and even decrease the number of students. Here are some private universities in the form of universities that have experienced a decline in students in the last five years.

Table 1: Private Universities That Have Decreased Number of Active Students in the city of Medan City

Source: processed data, 2019

Formulation of the Problem

Based on the background and description developed above, the problems to be studied are formulated as follows:

• What are the factors that influence students to decide to study at private universities in the city of Medan

• Among these factors, which factors have the dominant influence on student decisions to choose to study at private universities in the city of Medan

Research Purposes

• To identify and analyze the factors that influence student decisions to choose to study at private universities in the city of Medan

• To identify and analyze the factors that have the most dominant influence on student decisions to study at private universities in the city of Medan

Literature Review and Hypotheses:

Consumer Behavior Theory: Consumer behavior is a process that is closely related to the purchasing process. At that time, consumers carry out activities such as searching, researching, and evaluating products. Consumer behavior is the things that underlie consumers to make purchase decisions. What is included in consumer behavior is the quality of the product, the price of the product or service.

According to Mowen and Minor [1] defines consumer behavior as a study of buying units and  exchange processes  that  involve the  acquisition,  consumption of  various  products, services and experiences as well as ideas. According to Lamb, et al. in Sumarwan [2] states that consumer behavior is the process of a customer in making decisions to buy, use and consume purchased goods and services, including factors that influence purchasing decisions and product use. According to Lawson [3], consumer behavior is an action that is directly involved in obtaining, consuming and consuming products and services including the decision process that precedes and follows these actions.

Factors That Influence Consumer Behavior

According to Kotler and Keller [4], consumer purchasing behavior is influenced by cultural, social, personal and psychological factors.

Buying Decision Process

According to Kotler and Keller [4], the stages that a buyer passes to reach a buying decision pass through five stages, namely: 

• Problem recognition 

• Information search 

• Alternative evaluation 

• Buying decisions

• Post-purchase behavior

Hypotheses

• H1:  Service factors, physical evidence, reputation, satisfaction, trust and commitment influence student decisions in choosing private tertiary institutions in the city of Medan

• H2:   The  commitment factor  has  the most  dominant  influence on  student  decisions in choosing private universities in the city of the city of Medan

Research Method

In this study the researchers took the research locations at five universities, namely: Muhammadiyah University of North Sumatra, Muslim Nusantara University, Dharmawangsa University, Al-Wasliyah University and Quality University. Taking the location refers to the research objective to find out and analyze the factors that influence students in choosing private universities in the city of the city of Medan. The choice of research object was because in the last five years the university had decreased students. The research used here is an exploratory research, namely research that explores and analyzes the factors that influence students in choosing private universities in the city of Medan.

Data and Analysis

Data obtained using sampling or survey methods. Surveys are limited to studies in which data are collected from a sample over a population to represent the entire population. In this study, the analyzed students at five universities in the city of Medan City. Primary data were collected using interview techniques and questionnaires. Interviews were conducted with the deans and academic departments of the five sample universities while the questionnaire was given to students who were selected as samples.

Conceptual Framework and Hypotheses

Figure 1: Factors Influencing Students’ Choice in Medan

Population and Sample

The population of this research is active students at five universities in the city of Medan City at least who have been in college for four semesters, totaling 26,358 people. The sampling technique used accidental sampling, by means of 5 x indicators. The number of indicators in this study was 27, so the sampling was 5 x 27 = 135 samples.

Factor Analysis: 

KMO and Bartlett's value: Table 2 shows that the KMO value is still in the interval 0.5 - 1.0, which is 0.896, and the significance value is 0.000 (<0.05), which means that it can be analyzed further.

Determination of the Number of Factors

Eigenvalues greater than 1.0 were retained and entered in the model. All eigenvalues are more than 1.0 which means that all factors are included in the model. The eigenvalues can be seen in Table 3.

Classification of Components into Factors

Factor After Rotation

Factor Analysis Results: A summary of the loading factors obtained by each indicator can be seen in Table 8. Based on Table 8, factor 1 includes seven indicators, factor 2 includes seven indicators, factor 3 includes five indicators, factor 4 includes three indicators, factor 5 includes three indicators and factor six includes two indicators. Below is a table for all the factors and indicators.

New Factor Naming

The new factors that were previously referred to as factors 1, 2, 3, 4, 5 and 6 will be named according to the largest loading factor obtained from the indicators in these factors, the following explanation can be seen in Table 6.

Table 2: Value of KMO and Bartlett's Test

Source: Output SPSS, 2020

Table 3: Indicator-Wise MSA (Measurement System Analysis) Values

Source: Output SPSS, 2020

Table 4: Total Variance Explained

Source: Output SPSS, 2020

Table 5: Rotated Component Matrix

Source: Output SPSS, 2020

Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. a. Rotation converged in 8 iterations.

Based on Table 6, these factors are named as follows:

• Factor  1:  Service,  the eigenvalue  obtained  by factor  1  is 12.105  with  a variance contribution of 44,832 has seven indicators, each loading factor≥0.5. The service factor naming based on the biggest loading factor is obtained by the service indicator as promised (X1.10) of 0.846 so that according to the initial explanation X1.10 is part of the service factor

• Factor 2: physical evidence, the eigenvalue obtained by factor 2 is 2,721 with a variance contribution of 10,078 having seven indicators, each loading factor≥0.5. The naming of the physical evidence factor based on the largest loading factor is obtained by the neat lecture hall indicator (X1.2) of 0.878 so that the 2 factor is called the physical evidence factor according to the initial concept

• Factor 3: Reputation, the eigenvalue obtained by factor 3 is 1.610 with a variance contribution of 5,962 has five indicators, each loading factor≥0.5. The naming of the university's reputation factor based on the largest loading factor is obtained by the indicator of the various study programs offered (X2.2) of 0.787 so that this factor of 3 is called the reputation factor

Table 6: Factor Analysis

Source: Output SPSS, 2020

• Factor 4: Satisfaction, the eigenvalue obtained by factor 4 is 1.350 with a variance contribution of 5,001 having three indicators, each loading factor≥0.5. The naming of student satisfaction factors based on the biggest loading factor is obtained by the private universities service indicator in accordance with student expectations (Z1.2) of 0.823 so that this factor 4 is called the satisfaction factor

• Factor 5: Trust, eigenvalue obtained by factor 5 is 1.146 with a variance contribution of 6.365 having two indicators, each loading factor≥0.5. Naming the student trust factor based on the biggest loading factor is obtained by the indicator of obtaining information about the quality of the restaurant (X2.1) of 0.825 so that this factor of 5 is called the trust factor

• Factor 6: Commitment, the eigenvalue obtained by factor 5 is 1.146 with a variance contribution of 6.365 having two indicators, each loading factor≥0.5. The naming of the affective commitment factor based on the largest loading factor is obtained by the indicator of feeling proud to be able to study at this private university (Z3.2) of 0.831 so that this factor of 6 is called the affective commitment factor

In this study using factor analysis method. Based on the results of factor analysis, conclusions can be drawn from the factors that influence student decisions in choosing to study in the city of Medan as follows:

• The results of the factor analysis show that from 27 indicators into six factors, namely service, physical evidence, reputation, satisfaction, trust and commitment

• Through factor analysis, it can be seen that the most dominant factor affecting student decisions in choosing to study at private tertiary institutions in the city of Medan is commitment

Suggestions

Based on the results of research using factor analysis, it can be suggested that the service factor is the main factor influencing student decisions in choosing to study at private tertiary institutions in Medan City. So an effective step for administrators of private higher education institutions in Medan City is to further improve services to students so that they will be satisfied. Satisfaction at a high level will make students make a commitment to themselves and if students are satisfied then they will have a high commitment to the campus where they study so that in the end they will also recommend the campus to others.

1. Mowen, J.C. and M. Minor. Consumer behavior. Prentice-Hall, 2009. https://doi.org/10.5005/jp/books/11120_9.

2. Sumarwan, U. Perilaku konsumen. PT Ghalia Indonesia, 2011. https://doi.org/10.31227/osf.io/pfjhz.

3. Lawson, R. Consumer behaviour. Marketing theory: A student text. Dryden Press, 2010. https://doi.org/10.4135/978144 6280096.n12.

4. Kotler, Philip, et al. Marketing management. Pearson, 2012.