Psychological Capital as a Predictor of Organizational Citizenship Behaviour in the Personnel and Human Resources Development Agency employees in West Kalimantan

This research starts from an indication of the low Organizational Citizenship Behavioral (OCB) of government agency employees at the Personnel and Human Resources Development Agency (BKPSDM) in West Kalimantan. Previous research explains that the predictor of employee OCB level is psychological capital. Therefore, this study aims to determine psychological capital as a predictor of organizational citizenship behavior in the Civil Service Agency and Human Resources Development employees in West Kalimantan. This research uses quantitative with ex-post facto type. The sample used was 52 BKPSDM employees in West Kalimantan. The instrument validation technique uses construct validation and previous research reliability. The data analysis technique uses descriptive and inferential analysis consisting of classical assumption tests and hypothesis testing. The results of this study indicate inferential analysis in the simultaneous test (F test) psychological capital variables become predictors of OCB. Then a partial test (T test) the hope dimension had no effect, the optimism dimension had no effect, the resilience dimension had no effect, and the self-efficacy dimension was the only predictor of psychological capital on OCB.

Authors

Institutions

Publication Details

Journal
Devotion Journal of Research and Community Service
Published
2024-12-20
DOI
https://doi.org/10.59188/devotion.v5i12.25384
Primary Topic
Emotional Intelligence and Performance
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Psychological Capital as a Predictor of Organizational Citizenship Behaviour in the Personnel and Human Resources Development Agency employees in West Kalimantan

Rosita Endang Kusmaryani, Rahbel Rahman
Devotion Journal of Research and Community Service
Emotional Intelligence and Performance
article

Psychological Capital as a Predictor of Organizational Citizenship Behaviour in the Personnel and Human Resources Development Agency employees in West Kalimantan

Rosita Endang Kusmaryani, Rahbel Rahman
article en

Abstract

This research starts from an indication of the low Organizational Citizenship Behavioral (OCB) of government agency employees at the Personnel and Human Resources Development Agency (BKPSDM) in West Kalimantan. Previous research explains that the predictor of employee OCB level is psychological capital. Therefore, this study aims to determine psychological capital as a predictor of organizational citizenship behavior in the Civil Service Agency and Human Resources Development employees in West Kalimantan. This research uses quantitative with ex-post facto type. The sample used was 52 BKPSDM employees in West Kalimantan. The instrument validation technique uses construct validation and previous research reliability. The data analysis technique uses descriptive and inferential analysis consisting of classical assumption tests and hypothesis testing. The results of this study indicate inferential analysis in the simultaneous test (F test) psychological capital variables become predictors of OCB. Then a partial test (T test) the hope dimension had no effect, the optimism dimension had no effect, the resilience dimension had no effect, and the self-efficacy dimension was the only predictor of psychological capital on OCB.

Devotion Journal of Research and Community ServiceVol. 5(12)
Yogyakarta State University (ID)
Openalex Percentile: Top 69%
Emotional Intelligence and Performance
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.