
INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)
ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume IX Issue X October 2025
www.rsisinternational.org
and Composite Reliability, with threshold values above 0.70, indicating acceptable internal consistency (Hair et
al. 2021; Ali et al. 2023).
Data Analysis Technique
Data were analyzed using structural equation Modeling based on Partial Least Squares (SEM-PLS) with
SmartPLS version 4. SEM-PLS was selected because it is robust with relatively small sample sizes, does not
require normally distributed data, and can be used to estimate complex models involving mediating variables
(Henseler 2023; Sarstedt et al. 2022). The analysis involved two stages: the evaluation of the measurement model
and the evaluation of the structural model. The validity and reliability of the measurement model were tested,
whereas the structural model tested the significance of the hypothesized relationships. Bootstrapping with 5,000
subsamples was conducted to generate t-statistics and p-values for hypothesis testing (Hair et al. 2021; Kline
2023).
RESULT
Descriptive Demographic Analysis of Respondents
Data were obtained from 127 respondents who agreed to complete the questionnaire. The respondents were
employees of a professional inspection and certification service company in Balikpapan City. The demographic
characteristics analyzed included age, sex, length of service, and the highest level of education. Based on the age
group, the majority of respondents were in the 25–35 age range, amounting to 18 (51.4%). This reflects the
dominance of productive workforce, which has a high level of adaptability to work dynamics. Respondents aged
35 and over numbered 10 (28.6%), reflecting the presence of workers with more experience. Meanwhile,
respondents aged under 25 numbered seven people (20.0%), indicating the contribution of young workers who
have just entered the workforce.
In terms of gender, the study respondents were predominantly male (22 respondents, 62.9 percent), while 13
(37.1 percent) were female. This composition indicates that the professional inspection and certification services
sector still involves a relatively large male workforce, although women contribute significantly to company
operations. Based on the length of service, 17 respondents (48.6 percent) had tenures between one and five years.
This indicates the dominance of employees with relatively stable, medium-term work experience. Ten
respondents (28.6 percent) had tenure of more than five years, indicating the presence of an experienced
workforce, which is a crucial asset in supporting organizational sustainability. Eight respondents (22.9 percent)
had a tenure of less than one year, indicating a process of workforce regeneration and new recruitment.
In terms of their highest educational level, the majority of respondents had a bachelor's degree (S1), with 12
respondents (34.3 percent). Nine respondents (25.7 percent) had a senior high school degree, whereas eight (22.9
percent) had a diploma (D3). Six respondents (17.1 percent) had postgraduate degrees (S2/S3). This composition
reflects the diverse educational backgrounds of the workforce, enabling synergy between practical skills and
academic competencies to support organizational performance. Overall, the demographic distribution of the
respondents showed a balance between productive age, gender diversity, variations in work experience, and
educational backgrounds. This provided a representative picture of the human resource conditions of the research
subjects.
Descriptive Statistical Analysis and Confirmatory Factor Analysis
A descriptive analysis was conducted to obtain a general overview of respondents' perceptions of the research
variables. All variables were measured using a five-point Likert scale, ranging from strongly disagree to strongly
agree. The analysis showed that the average respondent's response was in the high category, reflecting a positive
trend toward communication, achievement motivation, affective commitment, and employee performance
indicators. Confirmatory Factor Analysis (CFA) was used to test construct validity by assessing the factor
loading of each indicator on the latent variable. An indicator is considered valid if the loading value is greater
than 0.70, while construct reliability is evaluated through a Composite Reliability (CR) value greater than 0.70
and an Average Variance Extracted (AVE) value greater than 0.50. The CFA results showed that all indicators