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THE INFLUENCE OF GRADUATES' COMPETENCE FROM

UNIVERSITAS DARUSSALAM GONTOR ON THE RELEVANCE

LEVEL BETWEEN FIELDS OF STUDY AND EMPLOYMENT

Ahmad Niayatulloh, Muhammad Haikal, Idris Rochmadi

Universitas Darussalam Gontor, Indonesia

Email: ahmad[email protected]ntor.ac.id, muhammad.haikal@unida.gontor.ac.id,

idris.rochmad[email protected]

Abstract

The success of higher education institutions is often measured by their competitiveness and the quality of their

graduates in the job market. The concept of competitiveness, particularly in terms of educational relevance, is a

fundamental consideration outlined in Law No. 12 related to higher education. One of the mechanisms for

assessing this educational relevance involves conducting tracer studies among graduates. The objective of this

research is to examine the individual (partial) and combined (simultaneous) effects of Grade Point Average

(GPA) and Academic Supporting Credit for Students (AKPAM) on the alignment between graduates' fields of

study and their subsequent employment. This study focuses on alumni from Darussalam Gontor University in

the year 2019. The research is conducted through a survey-based approach, and the data collected through tracer

study questionnaires. The findings indicate that while GPA exhibits an insignificant influence on the degree of

alignment between fields of study and employment, AKPAM significantly affects this alignment. Moreover,

when considered together, both GPA and AKPAM exert a significant influence on the alignment between

graduates' fields of study and their employment choices.

Keywords: GPA, AKPAM, Treasure Study

INTRODUCTION

Universitas Darussalam (UNIDA) Gontor stands as a prominent center for Islamic

boarding school-based higher education in Indonesia. As an institution characterized by its

pesantren (Islamic boarding school) values, UNIDA Gontor plays a pivotal role in nurturing

accomplished student-scholars who can excel amidst global challenges. Therefore, UNIDA

Gontor must adopt strategic approaches to fulfill this mission, aiming to elevate academic

quality while concurrently enhancing the caliber of graduates who can competitively engage

in the realms of knowledge and technology (Prasetiyo, 2020). These graduates are envisioned

to possess virtuous character and morals, equipping them to become future leaders. The

measurement of graduate quality is accomplished through the alumni tracing process,

commonly known as a tracer study (CALIBO & CABALLERO, 2017). This empirical research

seeks to provide insights into the educational quality at Unida Darussalam University. The

effectiveness of the tracer process is assessed through the gathering of information about the

alumni, encompassing their professionalism, knowledge, and expertise. This data is then linked

with the university's curriculum, establishing a feedback loop that influences academic

programs and the university itself (Rifandi, 2013; Rutherford et al., 2012). The outcomes of

tracer studies, as evaluated at Unida Darussalam Gontor, facilitate an efficient, effective, and

productive educational journey, ultimately enhancing the competitiveness of UNIDA Gontor's

graduates (Julaeha, 2016).

Furthermore, observing this tracer study process, the researcher has formulated several

inquiries regarding the relationships among the variables within the tracer study. Firstly,

whether Grade Point Average (GPA) influences the alignment level between field of study and

occupation; secondly, whether Academic Supporting Credit for Students (AKPAM) affects the

level of alignment between field of study and occupation; and thirdly, whether there is a

combined effect of IPK and AKPAM on the alignment level between field of study and

Injuruty: Interdiciplinary Journal and Humanity

Volume 3, Number 1, January 2024

e-ISSN: 2963-4113 and p-ISSN: 2963-3397

The Influence of Graduates' Competence from Universitas Darussalam Gontor on the

Relevance Level Between Fields of Study and Employment

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occupation. The primary aim of this research is to ascertain the level of relevance between

employment and educational background, and to assess graduates' competencies. Given the

phenomenon of alumni tracing, the researcher has chosen to conduct a study titled "Analysis

of the Influence of Competence among 2019 UNIDA Gontor Graduates on the Relevance Level

between Fields of Study and Employment (UNIDA, 2019).

The enhancement of alumni competencies is often discerned through tracer studies. In

theory, competence comprises a combination of knowledge, values, skills, and attitudes

reflected in thinking and actions (Mulyasa, 2019). Arifin defined competence as a unique

fusion of knowledge and skills. Meanwhile, according to Employment Law No. 13 of 2003,

competence is defined as an individual's work capability, encompassing knowledge, skills, and

work attitudes in alignment with established standards. Sadjad et al., (2002) contended that

relevance is the crucial determinant of the existence of an educational institution. Tritjahjo

proposes that the enhancement of higher education relevance can be achieved through a series

of activities involving education, teaching, research, and community service (Tritjahjo, 2005).

Regarding performance theory, Aslami et al., (2018) states that performance is the outcome of

both physical and non-physical job execution. Similarly, Anwar et al., (2016) aligns

performance with the concept of "performance," essentially depicting the realization of tasks

as a responsibility and the actualization of possessed competencies.

The analysis of the influence of 2018 UNIDA Gontor Graduates' Competence on the

Relevance Level between Fields of Study and Employment has emerged as a distinctive

phenomenon within tracer study research. Here are some relevant studies found in the

literature: A comparative analysis of tracer study results in the international relations and public

administration programs (Fanani et al., 2017).

The objective of the above study was to address issues related to graduates' absorption

into the job market and the waiting period for alumni to secure employment after completing

their studies. The findings revealed that the international relations and public administration

programs were considered priorities among six prominent universities in East Java. The

research outcomes suggested the opening of international relations and public administration

programs as an effort to develop the Faculty of Social and Political Sciences at the Islamic

State University of Walisongo.

RESEARCH METHOD

This research was conducted using a quantitative approach, wherein a survey was

administered to a cohort of alumni, constituting both the population and sample under

investigation (Sugiyono, 2020). The study was executed in February 2021, entailing the

dissemination of a tracer study questionnaire to the alumni of UNIDA Gontor who graduated

in 2019. Secondary data, obtained from an auxiliary source as an archival repository of UNIDA

Gontor's tracer study institution, was the principal data type utilized. This secondary data

encompassed the outcomes derived from UNIDA Gontor's 2019 tracer study. For data

collection, a tracer study research instrument was employed. The university systematically

dispatched the instrument to all alumni of the 2019 cohort via an online submission portal.

Respondents, comprising alumni, diligently responded to the tracer study questionnaire within

the stipulated time frame. The research encompassed a population comprising alumni of

UNIDA Gontor's 2019 graduating class. Furthermore, the sampling procedure adopted a

probability sampling technique, specifically employing a stratified random sampling

methodology across the diverse faculties of UNIDA Gontor. This process entailed the random

selection of participants from each distinct data subgroup or category. The total cohort of

alumni graduating in the year 2019 amounted to 496 individuals. The determination of the

The Influence of Graduates' Competence from Universitas Darussalam Gontor on the

Relevance Level Between Fields of Study and Employment

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sample size was executed employing the Slovin formula, resulting in a final sample size of 205

alumni. Three operational definitions were derived from various research variables in this

study, namely:

Table 1: Operational definitions of variables

Variabel

Definition

Scale

GPA (X1)

GPA is the cumulative value of course

grades received by a student over the

entirety of their academic semesters.

Ordinal

AKPAM (X2)

AKPAM is a numerical value or point

system assigned by the university to

recognize and quantify the participation

of students in designated activities

throughout their academic semesters.

Ordinal

The Level of

Relevance

Between Field

of Study and

Employment

(Y)

The level of alignment of alumni

performance after graduation with the

competencies acquired in their

respective study programs

Ordinal

The purpose of the analysis in this study is to determine the extent of the influence of

GPA and AKPAM on the level of relevance between student performance and their respective

study programs. Several analyses utilized in this study are outlined as follows:

Assumption Tests

a. Normality Test

The normality test aims to assess the regression model for the presence of disturbances

or residuals within its normal distribution (Ghozali, 2013). Just like the T and F tests, it

assumes that the residual values follow a normal distribution. Any violations could render

the statistical testing process invalid.

b. Multicollinearity Test

The multicollinearity test serves the purpose of examining the regression model for

correlations among independent variables. An ideal regression model should ideally show

no significant correlations among independent variables.

c. Heteroskedasticity Test

Heteroskedasticity testing aims to evaluate the regression model for unequal variance

of residuals across different observations. If the residual variances remain constant, it is

referred to as homoskedasticity, while if they differ, it is referred to as heteroskedasticity. A

model is considered sound when it exhibits homoskedasticity or the absence of

heteroskedasticity.

d. Linearity Test

The linearity test is employed to determine if the regression model can be

approximated by a linear equation. This test is utilized as a prerequisite for linear regression

correlation analysis (Lupiyoadi & Ikhsan, 2015).

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Relevance Level Between Fields of Study and Employment

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Multiple Linear Regression Analysis

Multiple regression analysis in this study aimed to ascertain the correlation between

independent variables and the dependent variable. The multiple linear regression equation is

outlined as follows:

Y = a + b1X1+b2X2 + e

Where:

– (Y) = The Level of Relevance

– (a) = Constant term

– (b1) & (b2) = The regression coefficients

– (X1) = GPA

– (X2) = AKPAM

– (e) = The standard error

Hypothesis Testing

a. F-Test (Simultaneous Test)

The simultaneous test of regression coefficients, also known as the model test,

assesses the joint significance of the regression coefficients. The test statistic used for this

purpose is the F-statistic, computed using the formula.

b. T-Test (Partial Test)

The partial test calculations essentially analyze the extent to which each individual

independent variable affects the dependent variable. To establish and understand the

individual influence of each independent variable on the dependent variable, a T-test is

employed.

c. Coefficient of Determination Test

The coefficient of determination R is also known as the multiple coefficients of

determination, closely resembling the r2 coefficient. While R is nearly identical to r, they

are not the same in terms of their function (except in simple linear regression). R elucidates

the portion of variance in the dependent variable Y explained by the independent variables

(X1, X2, ..., Xk) successively.

d. The Theoretical Framework

Drawing upon the presented literature review, the theoretical framework of this

research can be depicted as follows:

Figure 1. Theoretical Framework

Information:

- (E) : Error

- (H1) & (H2) : Partial Effects

- (H3) : Simultaneous Effect

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RESULT AND DISCUSSION

The 2020 tracer study conducted by UNIDA Gontor focused on the alumni from the 2019

graduating class. This investigation was executed in line with the University of Darussalam

Gontor's utilization of the TS-1 system to delineate the study's subject. Notably, the 2019 batch

of alumni constituted a total of 495 individuals. From this cohort, 374 alumni completed the

questionnaire, yielding a response rate of 75.5%. This level of participation is particularly

commendable, considering that this tracer study marks the second instance of its execution at

UNIDA Gontor.

Figure 2. Achievements of the 2019 Tracer Study

The envisaged total number of respondents for the tracer study was 495 individuals.

Nevertheless, an analysis of the illustrated outcomes indicates that 374 participants (75.5%)

diligently completed the questionnaire, while the remaining 121 individuals (24.5%) abstained

from participation. The significant figure of 75.5%, indicating the proportion of respondents

who engaged with the tracer study questionnaire, surpassed those who refrained from

participation. This outcome serves as an attestation to the ongoing interest of alumni in the

tracer study initiatives orchestrated by UNIDA Gontor.

Figure 3. The percentage of tracer study achievements from each faculty

Figure 3 illustrates the attainment levels of the UNIDA Gontor tracer study, revealing

the following outcomes: The Faculty of Health Sciences has successfully reached its target,

achieving 100% response rate from the alumni who participated in the study, indicating

complete questionnaire submission. Similarly, the faculties of Graduate Studies and Science &

Technology have achieved commendable percentages, with 86% and 80% respectively. In

contrast, the Faculty of Economics and Management demonstrates a comparatively lower

engagement, with a response rate of 48%.

The Influence of Graduates' Competence from Universitas Darussalam Gontor on the

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Classic Assumption Test

Table 2. One sample kolmogorov smirnov test

Unstandarized

residual

205

Normal

parameter

a,b

Mean

.000000

Standar deviasi

.68559480

Most

extreme

differences

Absolute

.087

Positif

.087

Negatif

-.061

Test statistic

.087

Asympt . sig. ( 2 taoled )

.001

Monte

carlo. sig. (2

tailed)

sig.

.080

99%

Confidence

Interval

Lowe

Bound

.073

Upper

bound

.086

Information:

– Test for Normal Distribution

– Data Analysis and Computation

– Employing the Lilliefors Significance Correction

– Conducted using SPSS version 22 (2021)

Table 2 above demonstrates the outcomes of the normality test conducted through the

Monte Carlo approach, yielding a two-tailed significance value of 0.080. Consequently, the

normality test outcomes carry significance in relation to the Kolmogorov-Smirnov method,

surpassing the 0.05 threshold. As a result, it can be reasonably inferred that the research dataset

conforms to a normal distribution.

Multicollinearity Assumption Test

Table 3. Multikolinearitas Assumption Test result

Coefficients

Model

Collinearity statistics

Tolerance

Vif

AKPAM

.989

1.011

IPK

.989

1.011

Dependent variable: Relevance

The results of the multicollinearity test presented in Table 3 indicate that each variable

exhibits a tolerance value exceeding 0.10, alongside a VIF value below 10. Specifically, for

the variable X1 (AKPAM), the tolerance value is recorded as 0.989, and for X2 (GPA), it also

stands at 0.989, both surpassing the minimum threshold of 0.10. Additionally, the VIF values

for X1 (AKPAM) and X2 (GPA) are calculated as 1.011 for each variable, both falling well

below the 10 benchmarks. Consequently, it can be deduced that the employed regression model

is devoid of multicollinearity concerns.

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Heteroscedasticity Assumption Test

Table 4. Heterokedastisitas Assumption Test Result

Coefficients

Model

Unstandardized

Coefficients

Standardized

Coefficients

Sig.

Std.Error

Beta

(constans)

.140

.592

.236

.814

AKPAM

.083

.059

.100

1.415

.159

IPK

.067

.171

.027

.389

.698

a. dependent variable: res_abs

The outcome of the heteroscedasticity test, conducted through the Glejser method,

yielded a notable significance for the independent variables X1 (Akpam) and X2 (GPA),

surpassing the established threshold for heteroscedasticity significance with values exceeding

0.05. This observation indicates the absence of heteroscedasticity indications.

Linierity Test

Table 5. Linierity Assumption Test of AKPAM

Sum of

squares

Mean

Square

Sig.

RELEVANCE

* AKPAM

Between

Groups

(Combined)

95.368

108

.883

2.238

.000

Linearity

37.362

94.681

.000

Deviation

from

Linearity

58.006

107

.542

1.374

.057

Within Groups

37.883

.395

Total

133.25

204

Table 6. Linierity Assumption Test of GPA

Sum of

squares

Mean

Square

Sig.

RELEVANCE

* GPA

Between

Groups

(Combined)

31.867

108

.540

.772

.870

Linearity

.370

.529

.468

Deviation

from

Linearity

31.497

107

.543

.777

.863

Within Groups

101.384

145

.699

Total

133.251

204

The outcomes of the linearity test, as presented in Table 5 and Table 6, indicate that the

deviations from linearity for variables X1 (AKPAM) and X2 (GPA) are statistically significant.

Hence, based on these findings, it can be inferred that the appropriate model for the data is

indeed a linear model.

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Multiple Linear Regression Analysis

Table 7. Multiple linear regression analysis method

Model

Unstandardized

Coefficients

Standardized

Coefficients

Sig

Std. Error

Beta

Constant

.613

1.095

.560

.576

IPK

-.012

.316

-.002

-.038

.970

AKPAM

.958

.109

.530

.000

a. Dependent Variable : RELEVANSI

The multiple regression table in table 7 above produces the following multiple linear

regression equation:

Y = 0.613 – 0.12)X1 – 0.958 X2 + e

Test the F test hypothesis

Table 8. F Test Result

Anova

Model

Sum of

squares

Mean

square

1 Regression

37.363

18.681

39.355

Residual

95.888

202

.475

Total

133.251

204

a. Dependent variabel: Relevansi

b. Predictors: (constant), Akpam, GPA

The outcomes presented in Table 8 unveil compelling insights. The calculated F value of

39.355, derived from the difference between the sample size (n) and the number of predictors

(k), namely 2 (k-1), indicates a noteworthy pattern. With a population size of 205, applying the

formula N-K/205-2 leads to a computed value for df2, equating to 203, and an associated F

table value of 3.04. Remarkably, the computed F value of 39.355 surpasses the critical F table

value of 3.04. Consequently, the null hypothesis (HO) is rejected, and the alternative hypothesis

(Ha) is accepted. Furthermore, it is crucial to emphasize that the significance value (sig)

registered a value of 0.000, denoting that sig (F) 0.000 is markedly less than the conventional

threshold of 0.05. This outcome underscores a robust statistical significance in the interplay

between the independent and dependent variables. This pronounced significance is

corroborated by the acceptance of Ha and the simultaneous rejection of Ho. In synthesis, the

collective impact of AKPAM and GPA on the alignment between academic disciplines and

professional vocations emerges as undeniably substantial.

T Test

Table 9. T Test Result

Coefficients

Model

Unstandardized

Coefficients

Standardized

Coefficients

Sig

Std. Error

Beta

Constant

.613

1.095

.560

.576

IPK

-.012

.316

-.002

-.038

.970

AKPAM

.958

.109

.530

.000

b. Dependent Variable : RELEVANSI

Table 9 above distinctly demonstrates the influence of the paired independent/dependent

variables on the correlation between academic specialization and occupational alignment.

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Computed from df1 (n-k-1), with n as 205 and k as 3, the resulting df value of 203 is utilized

for a two-tailed significance test. Notably, for the AKPAM variable, the t-score of -0.038 falls

short of the critical t-table value of 1.285, with a significance value of 0.970 above the 0.05

threshold, leading to the acceptance of null hypothesis Ho1 and the rejection of alternative

hypothesis H2. Conversely, the t-score for Akpam at 8.828 significantly exceeds the t-table

value, accompanied by a remarkably low significance value of 0.00, thereby rejecting Ho2 and

confirming the acceptance of Ha2. In summary, while GPA exerts minimal impact on

academic-vocational alignment, Akpam distinctly influences the level of relevance between

these domains.

Coefficient of Determination

Table 10. Coefficient of Determination Test (R)

Model summry

Model

square

Adjusted

R square

Std. error

of the

estimate

.530

.280

.273

.68898

a. Predictors: (Constant), AKPAM, GPA

Drawing insights from table 10, the adjusted R-squared value of 0.273 becomes evident,

signifying that the Akpam and GPA variables collectively contribute to a 27.3% impact on the

alignment between academic specialization and occupational relevance. A substantial portion

of 72.7% is attributed to other unaccounted factors outside the scope of this study.

CONCLUSION

Based on the comprehensive discussion presented, the following conclusions can be

deduced The outcomes of the combined analysis and the F-test unequivocally demonstrate that

both Akpam and GPA exert a noteworthy and statistically significant influence on the

congruence between academic disciplines and professional domains among the alumni of

University of Darussalam Gontor from the 2019 graduating cohort. Further insights from the

individualized partial analysis, utilizing the T-test, reveal distinct patterns: Firstly, the analysis

indicates that GPA does not exhibit a discernible impact on the alignment between academic

pursuits and vocational spheres. In contrast, Akpam emerges as a significant determinant,

substantiating its influence on fostering a heightened correlation between fields of study and

work environments.

Considering the research outcomes and the ensuing discussions, several

recommendations are proposed for consideration, aiming to facilitate continuous evaluation

and improvement UNIDA Gontor, as the custodian of policy direction, is advised to give

careful attention to enhancing the supporting elements that augment the impact of the student

academic journey on the outcomes of graduates. This involves a concerted focus on refining

the educational ecosystem to better align with professional requirements. For faculties and

academic programs, acting as pivotal education practitioners, there exists a prime opportunity

to elevate the management of the teaching and learning process. A dedicated effort towards

enhancing graduate competencies is paramount, enabling them to seamlessly adapt to real-

world scenarios upon graduation. Acknowledging the current research's limitation, which

centers around the 2019 alumni population, future researchers are encouraged to explore a

broader spectrum. The suggestion is to diversify the research population by aligning with

varying graduation years, thus providing a comprehensive overview of tracer study progress

over time. It's noteworthy that this study encompasses only two variables, yielding an adjusted

R-square value of 28%, implying that additional factors contribute to the alignment between

fields of study and work. To glean a more holistic perspective, further research endeavors are

The Influence of Graduates' Competence from Universitas Darussalam Gontor on the

Relevance Level Between Fields of Study and Employment

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recommended to incorporate a wider array of variables. By doing so, an enriched understanding

of the multifaceted determinants influencing the level of relevance can be attained.

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Ahmad Niayatulloh, Muhammad Haikal, Idris Rochmadi (2023)

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