Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal Viva Medika: Jurnal Kesehatan, Kebidanan dan Keperawatan Java Nursing Journal
Anton Suhendro
Unknown Affiliation
Health Professions Medicine & Pharmacology Nursing Public Health

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
DESCRIPTION OF THE LEVEL OF STRESS OF STUDENTS IN FACING THE THESIS AT ANESTHESIOLOGY NURSING STUDY PROGRAM APPLIED UNDERGRADUATE PROGRAM AT UNIVERSITY OF HOPE NATION PURWOKERTO Ramadhan, Iqbal; Nova Handayani, Rahmaya; Burhan, Asmat; Anton Suhendro
Java Nursing Journal Vol. 2 No. 1 (2024): November - February 2024
Publisher : Global Indonesia Health Care (GOICARE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61716/jnj.v2i1.27

Abstract

Background: Final year students often experience stress with final assignments, especially health students who are temporarily working on a thesis. Health students are also prone to experiencing stress when compiling a thesis and if not handled properly it will have an impact on the obstruction of thesis preparation, decreasing academic grades, and graduating not on time. Student stress can have a negative impact on academic grades, depression, and can even lead to dangerous actions such as suicide. Purpose: This study aims to determine the level of student stress in facing the thesis in the anesthesiology nursing study program of the applied undergraduate program at Harapan Bangsa University. Methods: This research includes descriptive quantitative research. This type of research is descriptive observational research with a cross sectional approach. Data analysis using Univariate analysis. The sampling technique in this study used convenience sampling. Result: Based on the results of this study, students who experienced a normal level of stress were 42 (42%) respondents, a description of the characteristics of respondents based on gender and age at the stress level of Applied Bachelor of Anesthesiology Nursing students at Harapan Bangsa University found that 24 (38.1%) female respondents experienced a normal level of stress and 40 (40.8%) respondents aged 22 years experienced a normal level of stress. Conclusion: The conclusion of this study is that students experience normal levels of stress.
A Scoping Review of Machine Learning Applications in Nursing Practice: Clinical Decision Support, Risk Prediction, and Workflow Optimization Anton Suhendro; Wahyu Caesarendra; Purwono, Purwono
Viva Medika Vol 18 No 3 (2025)
Publisher : LPPM Universitas Harapan Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35960/vm.v18i3.2222

Abstract

Machine learning (ML) is rapidly transforming nursing practice by enabling advancements in clinical decision support, risk prediction, and workflow optimization. This scoping review synthesizes evidence from empirical studies, reviews, and implementation reports published between 2018 and 2025, identified through Scopus and ScienceDirect. The findings indicate that supervised learning algorithms, deep learning, and natural language processing are widely utilized for risk assessment, early detection of patient deterioration, and enhancement of administrative efficiency. Natural language processing (NLP) also supports automation of nursing documentation and improved data quality. Despite favorable performance metrics, including AUROC values above 0.85 in many applications, most studies are limited by single-institution data, insufficient external validation, and heterogeneous reporting standards. Major barriers include ethical and legal concerns, data quality issues, algorithmic bias, infrastructural limitations, and limited nurse involvement in model development. Enhancing AI literacy and fostering nurse engagement in system design are highlighted as critical for successful clinical integration. Future research priorities include multicenter validation, development of explainable AI, adoption of standardized reporting guidelines, and interdisciplinary collaboration to address ethical, technical, and regulatory challenges. Overall, this scoping review demonstrates that machine learning offers substantial potential to improve patient outcomes and nursing operations, but responsible adoption requires rigorous validation, transparent governance, and active participation of nursing professionals throughout the technology lifecycle
Co-Authors Burhan, Asmat Iqbal Ramadhan, Iqbal Nova Handayani, Rahmaya Purwono Purwono, Purwono Wahyu Caesarendra