Article Per Year (5 Year)
p-Index From 2020 - 2025
0.659
P-Index
This Author published in this journals
All Journal Jurnal Promkes: The Indonesian Journal of Health Promotion and Health Education Indonesian Journal of Cardiology Pediatric Sciences Journal
Muharrom, Muhammad Aji
Unknown Affiliation
Health Professions Medicine & Pharmacology Public Health

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
CERIA: A Community Empowerment as Dementia Preventive Measure among Elderly Afidjati, Hera; Ronoatmodjo, Sudarto; Muharrom, Muhammad Aji; Deslanthy, Belinda Thania; Khaerani, Ayu Suciah; Adre Mayza
Jurnal Promkes: The Indonesian Journal of Health Promotion and Health Education Vol. 12 No. SI1 (2024): Jurnal Promkes: The Indonesian Journal of Health Promotion and Health Educat
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jpk.V12.ISI1.2024.51-56

Abstract

Background: Dementia is predicted to double in the next 15 years and causes adverse socioeconomic effects, yet the clinical therapy for dementia has not shown satisfactory results for many years. Preventive efforts involving the active role of the elderly and supported by the development of information technology are strongly needed. Method: This is a quasi-experimental study aimed to evaluate the effectiveness of CERIA as community-based intervention and to increase the awareness of dementia. CERIA (Cerdas Hindari Demensia) was implemented for 32 elderlies in Pasar Minggu District, South Jakarta who were willing to participate. The interventions implemented were memory training, brain vitalization gymnastics, playing angklung, and storytelling to toddlers. We measured the pre-and post-intervention scores of the elderly using an assessment tool of dementia screening, then compared the results using Student T-test. We also created a dementia prevention manual book (Buku Panda) and built a smartphone app for educational purposes. Results: As many as 97% of the elderly have a good daily activity score and 90.9% have a good body balance. Assessment of pre-intervention cognitive function showed a mean value of 27 and increased to 29 after intervention. The pre-intervention emotional assessment showed a mean value of 1 and decreased in post-intervention to 0. Some of the most afflicted diseases of the elderlies were hypertension (30,3%) and diabetes mellitus (18,2%). Conclusion: This dementia prevention program has a strong potential to be implemented in wider scope. Further improvement involving parties such as the Ministry of Health is needed to replicate this effort.
The Use of Artificial Intelligence (AI) to Predict Heart Failure in Type II Diabetes Mellitus Patients: A Systematic Review Liastuti, Lies Dina; Suwana, Averina Geffanie; Muharrom, Muhammad Aji; Irfannadhira, Aruni Cahya; Nursakina, Yosilia
Jurnal Kardiologi Indonesia Vol 44 No 4 (2023): Indonesian Journal of Cardiology: October - December 2023
Publisher : The Indonesian Heart Association

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30701/ijc.1689

Abstract

Heart failure (HF) is a critical concern for individuals with Type II Diabetes Mellitus (T2DM), significantly increasing morbidity and mortality rates. Artificial Intelligence (AI) and machine learning hold promise in enhancing predictive capabilities and guiding personalised interventions. This systematic review evaluates existing AI models' effectiveness in predicting HF complications in T2DM patients. A comprehensive literature search identified 8 relevant studies, predominantly from European, North American, and Southeastern populations. These studies utilised multi-centered registries and electronic medical records to develop AI models predominantly focused on supervised learning algorithms. While the AI models had promising performance, these models lack external validation with diverse populations and reproducibility, hindering their clinical applicability. Moreover, variations in outcome definitions and input features underscore the need for standardised approaches. Despite these limitations, AI models offer valuable insights into HF risk assessment in T2DM, highlighting the importance of further validation and reproducibility for clinical integration.
The effect of breastfeeding compared with formula milk on the growth of infants with congenital heart disease: Evidence-based case report Melinda; Permadi, Prasetya Ismail; Yuliarto, Saptadi; Kadafi, Kurniawan Taufiq; Koentartiwi, Dyahris; Rahmadany, Aulya Farra; Fauzi, Muhammad Rizki; Muharrom, Muhammad Aji
Pediatric Sciences Journal Vol. 6 No. 1 (2025): Available online : 1 June 2025
Publisher : Medical Faculty of Brawijaya University, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51559/pedscij.v6i1.123

Abstract

Introduction: Children with Congenital Heart Disease are at high risk of feeding and growth problems. Nutrition practices for children with CHD still vary widely across institutions, including breastfeeding. This study aims to conduct a critical review to compare the effects of breastfeeding versus formula on the growth of infants with congenital heart disease. Methods: The article search was conducted online using the PubMed, EBSCO, and ProQuest databases with the keywords “Congenital Heart Disease,” “Human Milk,” “Formula,” and “Growth.” Result: Two articles were obtained in the form of systematic review studies. Results of the study stated that in infants with CHD with breastfeeding compared to formula milk Weight for age score is better with breastfeeding because breast milk is easier to digest Conclusion. Breast milk has been shown to have significant benefits on the growth of infants with CHD compared to formula, especially in terms of weight-for-age z-score.
Co-Authors Adre Mayza Afidjati, Hera Deslanthy, Belinda Thania Fauzi, Muhammad Rizki Irfannadhira, Aruni Cahya Khaerani, Ayu Suciah Koentartiwi, Dyahris Kurniawan Taufiq Kadafi Liastuti, Lies Dina Melinda Nursakina, Yosilia Permadi, Prasetya Ismail Rahmadany, Aulya Farra Saptadi Yuliarto Sudarto Ronoatmodjo Suwana, Averina Geffanie