Article Per Year (5 Year)
p-Index From 2020 - 2025
1.066
P-Index
This Author published in this journals
All Journal Journal of Tropical Life Science : International Journal of Theoretical, Experimental, and Applied Life Sciences Journal of Robotics and Control (JRC) International Journal of Robotics and Control Systems Sewagati Svāsthya: Trends in General Medicine and Public Health
Rangkuti, Rahmah Yasinta
Faculty Of Medicine And Health, Institut Teknologi Sepuluh Nopember
Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Immunology & microbiology Languange, Linguistic, Communication & Media Mechanical Engineering Medicine & Pharmacology Public Health Social Sciences Other

Published : 6 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 6 Documents
Search

 1 
Effect of Vitamin D3 Supplementation to 25(OH)D, IL-17, and HbA1c Level in Pediatric Type 1 Diabetes Mellitus Rangkuti, Rahmah Yasinta; Tjahjono, Harjoedi Adji
Journal of Tropical Life Science Vol 7, No 1 (2017)
Publisher : Journal of Tropical Life Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11594/jtls.07.01.06

Abstract

Type 1 Diabetes Mellitus (T1DM) is the consequence of autoimmune destruction process of β cells which associated with Th17 activity and low 25(OH)D level. This study was aimed to investigate the effect of vitamin D3 supplementation toward 25(OH)D level, Th17 activity (IL-17) and glycemic control (HbA1c) in pediatric T1DM. This study was designed as randomized clinical trials (RCT), double-blind, pre and post-test controlled study. Subject was children with T1DM who were divided into two groups: K1: subjects were treated with insulin 0.5–2 IU/day + vitamin D3 2000 IU/day for 3 months, K2: subjects were treated with insulin 0.5–2 IU/day + placebo for 3 months. Levels of 25(OH)D, IL-17 and HbA1c were evaluated after 3 months treatment using ELISA. After 3 months treatment, results showed that 25(OH)D level was significantly higher in K1 compared with K2 (p = 0.00), IL-17 level was significantly lower K1 compared with K2 (p= 0.022). Surprisingly, HbA1c level in K1 was not significantly different with K2 (p = 0.93). Furthermore, in vitamin D-treated group, 25(OH)D level was elevated significantly after 3 months treatment with vitamin D (p = 0.00), IL-17 level was reduced significantly after 3 months treatment with vitamin D (p= 0.001)  and HbA1c level was reduced insignificantly after 3 months treatment with vitamin D (p= 0.76). Correlation study showed that there was no correlation between 25(OH)D level with IL-17 level (p= 0.160, r= -0.284) and 25(OH)D with HbA1c (p= 0.62, r= -0.10). This study can be conclude that vitamin D3 supplementation may elevate the 25(OH)D and reduce IL-17 level but did not change HbA1c level in pediatric T1DM.
Pelatihan Kader PKK di Kota Probolinggo dalam Upaya Pencegahan Kematian Ibu dan Bayi serta Pencegahan Stunting Fadli, Sonny; Rangkuti , Rahmah Yasinta; Susilo, Imam; Furaidah, Erna
Sewagati Vol 8 No 4 (2024)
Publisher : Pusat Publikasi ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j26139960.v8i4.1015

Abstract

Indikator kesehatan seperti angka kematian ibu, angka kematian bayi, dan prevalensi stunting merupakan tolak ukur penting dalam pemantauan kesehatan masyarakat. Meskipun terdapat penurunan angka global dalam rasio kematian ibu, situasi di Indonesia masih mengkhawatirkan. Kegiatan pengabdian masyarakat dilakukan untuk meningkatkan pengetahuan kader PKK Kota Probolinggo dalam deteksi dini kehamilan risiko tinggi dengan menggunakan platform digital Hamilku.ID dan meningkatkan pengetahuan kader PKK tentang skrining tumbuh kembang untuk penceghan stunting. Kegiatan pengabdian kepada masyarakat dilaksanakan di Dinas Kesehatan dan P2KB Kota Probolinggo dengan diawali pre-test, pelatihan dan post-test yang melibatkan 50 kader PKK di Kota Probolinggo. Dari hasil pre-test dan post-test terhadap 30 kader PKK, didapatkan nilai mean dari 30 responden pada saaat pre-test yakni sebesar 51,3 sedangkan nilai mean dari 30 responden pada saat post-test sebesar 85,3 yang dapat menunjukkan peningkatan pengetahuan setelah dilakukan pelatihan. Dengan nilai pearson correlation sebesar 0,362 dan P(T<=t) two-tail sebesar 1,599. Terdapat peningkatan pengetahuan kader dalam hal deteksi kehamilan risiko tinggi menggunakan platform digital Hamilku.ID dan skrining tumbuh kembang pada kader PKK di Kota Probolinggo.
Nephritic syndrome and acute kidney injury following poststreptococcal glomerulonephritis in pediatric patients: A case report Endah Indriastuti; Rahmah Yasinta Rangkuti; Alvin Hartanto Kurniawan
Svāsthya: Trends in General Medicine and Public Health Vol. 1 No. 1 (2024): July 2024
Publisher : PT. Mega Science Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70347/svsthya.v1i1.14

Abstract

Acute kidney injury (AKI) is characterized by an abrupt decrease in glomerular filtration rate, manifesting as an increase in serum creatinine or oliguria. Nephritic syndrome, a manifestation of glomerulonephritis, presents with hematuria, hypertension, decreased urine output, and edema. This case report discusses an 11-year-old Asian boy who presented with decreased urination, shortness of breath, hypertension, and bilateral leg edema. Urinalysis revealed hematuria, proteinuria, and dysmorphic erythrocytes, while serum creatinine was elevated with a decreased estimated glomerular filtration rate (eGFR). The patient had a positive ASTO test, indicating poststreptococcal glomerulonephritis as the underlying cause of nephritic syndrome and AKI. Although most cases of poststreptococcal glomerulonephritis in children have a favorable outcome, some cases can develop into a serious, life-threatening condition that requires careful attention. This case highlights the importance of early detection and management of poststreptococcal glomerulonephritis to prevent progression to nephritic syndrome and AKI, especially in resource-limited settings. Modest examination modalities can facilitate early detection and faster patient management, particularly in developing countries, to reduce the risk of mortality associated with severe AKI in pediatric patients.
Pelatihan Psychological First Aid (PFA) dan Stress Management untuk Mahasiswa Kedokteran Tahun Pertama FKK ITS 2024 Syulthoni, Zain Budi; Haykal, Muhammad Nazhif; Eljatin, Dwinka Syafira; Haque, Sayidah Aulia Ul; Rangkuti, Rahmah Yasinta; Fadhlina, Afia Nuzila; Indriastuti, Endah; Radiansyah, Riva Satya; Putri, Atina Irani Wira; Sari, Desiana Widityaning; Indriani, Ratri Dwi; Siswanto, Putri Alief; Mahdi, Faizal
Sewagati Vol 9 No 1 (2025)
Publisher : Pusat Publikasi ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j26139960.v9i1.2413

Abstract

Mahasiswa kedokteran tahun pertama menghadapi banyak tantangan dalam menye-suaikan diri dengan lingkungan akademik baru, yang dapat memengaruhi kesehatan mental mereka. Tujuan dari penelitian ini adalah untuk meningkatkan kemampuan siswa dalam mengelola stres dan memberikan dukungan psikologis melalui pelatihan manajemen stres dan dukungan psikologis pertama / Psychological First Aid (PFA). 30 mahasiswa kedokteran semester 1 FKK ITS mengikuti pelatihan, yang berlangsung selama dua hari dan total 16 jam. Pelatihan juga dievaluasi melalui pretest dan posttest menggunakan kuesioner. Melalui simulasi kasus, peserta menunjukkan kemampuan yang baik dalam menggunakan strategi PFA dan manajemen stres. Hasil analisis menunjukkan peningkatan signifikan dalam pemahaman dan keterampilan peserta setelah mengikuti pelatihan (p=0.000). Pelatihan mencakup pemaparan teori dan praktik keterampilan PFA, seperti keterampilan mendengarkan yang aktif, keterampilan komunikasi, keterampilan empati, dan keterampilan bertahan hidup. Dua modul program ber-ISBN dan publikasi di media massa. Kesimpulan dari pengabdian masyarakat adalah bahwa terjadi peningkatan pemahaman dan kemampuan mahasiswa kedokteran tahun pertama terhadap Psychological First Aid dan Stress Management yang diharapkan lebih siap menghadapi tantangan akademik.
A Comprehensive Review of EEGLAB for EEG Signal Processing: Prospects and Limitations Pamungkas, Yuri; Rangkuti, Rahmah Yasinta; Triandini, Evi; Nakkliang, Kanittha; Yunanto, Wawan; Uda, Muhammad Nur Afnan; Hashim, Uda
Journal of Robotics and Control (JRC) Vol. 6 No. 4 (2025)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v6i4.27084

Abstract

EEGLAB is a MATLAB-based software that is widely used for EEG signal processing due to its complete features, analysis flexibility, and active open-source community. This review aims to evaluate the use of EEGLAB based on 55 research articles published between 2020 and 2024, and analyze its prospects and limitations in EEG processing. The articles were obtained from reputable databases, namely ScienceDirect, IEEE Xplore, SpringerLink, PubMed, Taylor & Francis, and Emerald Insight, and have gone through a strict study selection stage based on eligibility criteria, topic relevance, and methodological quality. The review results show that EEGLAB is widely used for EEG data preprocessing such as filtering, ICA, artifact removal, and advanced analysis such as ERP, ERSP, brain connectivity, and activity source estimation. EEGLAB has bright prospects in the development of neuroinformatics technology, machine learning integration, multimodal analysis, and large-scale EEG analysis which is increasingly needed. However, EEGLAB still has significant limitations, including a high reliance on manual inspection in preprocessing, low spatial resolution in source modeling, limited multimodal integration, low computational efficiency for large-scale EEG data, and a high learning curve for new users. To overcome these limitations, future research is recommended to focus on developing more accurate automation methods, increasing the spatial resolution of source analysis, more efficient multimodal integration, high computational support, and implementing open science with a standardized EEG data format. This review provides a novel contribution by systematically mapping EEGLAB’s usage trends and pinpointing critical technical and methodological gaps that must be addressed for broader neurotechnology adoption.
Recent Advances in Artificial Intelligence for Dyslexia Detection: A Systematic Review Pamungkas, Yuri; Rangkuti, Rahmah Yasinta; Karim, Abdul; Sangsawang, Thosporn
International Journal of Robotics and Control Systems Vol 5, No 3 (2025)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v5i3.2057

Abstract

The prevalence of dyslexia, a common neurodevelopmental learning disorder, poses ongoing challenges for early detection and intervention. With the advancement of artificial intelligence (AI) technologies in the fields of healthcare and education, AI has emerged as a promising tool for supporting dyslexia screening and diagnosis. This systematic review aimed to identify recent developments in AI applications for dyslexia detection, focusing on the methods used, types of algorithms, datasets, and their performance outcomes. A comprehensive literature search was conducted in 2025 across databases including ScienceDirect, IEEE Xplore, and PubMed using a combination of relevant MeSH terms. The article selection process followed the PRISMA guidelines, resulting in the inclusion of 31 eligible studies. Data were extracted on AI approaches, algorithm types, dataset characteristics, and key performance metrics. The results revealed that machine learning (ML) was the most widely applied method (58.06%), followed by multi-method (22.58%), deep learning (16.13%), and large language models (3.23%). Among the ML algorithms, Random Forest and Decision Tree were the most commonly used due to their robustness and performance on structured datasets. In the deep learning category, CNN were the most frequently used models, especially for image-based and sequential input data. The datasets varied widely, including digital cognitive tasks, EEG, MRI, handwriting, and eye-tracking data, with several studies employing multimodal combinations. Ensemble and hybrid models demonstrated superior performance, with some achieving accuracy rates exceeding 98%. This review highlights that AI, particularly ML and multimodal ensemble methods, holds strong potential for improving the accuracy, scalability, and accessibility of dyslexia detection. Future research should prioritize large-scale, multimodal datasets, interpretable models, and adaptive learning systems to enhance real-world implementation.
Co-Authors Abdul Karim Abdurahman Abdurrahman Adhi Dharma Wibawa, Adhi Dharma Alvin Hartanto Kurniawan Dwinka Syafira Eljatin Endah Indriastuti Evi Triandini Fadhlina, Afia Nuzila Fadli, Sonny Fitriani, Fatimah Nur Furaidah, Erna Haque, Sayidah Aulia Ul Harjoedi Adji Tjahjono, Harjoedi Adji Hashim, Uda Haykal, Muhammad Nazhif Hedianto, Tri Hidayah, Rizka Nurul Imam Susilo Indriani, Ratri Dwi Indriastuti, Endah Karimah, Rumman Mahdi, Faizal Nakkliang, Kanittha Njoto, Edwin Nugroho Pamungkas, Yuri Parlindungan, Putra Gelar Putra, Gumilar Fardhani Ami Putri Alief Siswanto Putri, Atina Irani Wira Radiansyah, Riva Satya Ridhoi, Ahmad Sakina Sangsawang, Thosporn Sari, Desiana Widityaning Syulthoni, Zain Budi Uda, Muhammad Nur Afnan Wawan Yunanto