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All Journal JIF Indonesian Journal of Physiotherapy International Transactions on Artificial Intelligence (ITALIC)
Noviati, Nuraini Diah
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Computer Science & IT Control & Systems Engineering Health Professions Library & Information Science Medicine & Pharmacology Neuroscience Public Health

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PERBEDAAN KINESIOTAPPING DENGAN PEMBERIAN MASSAGE PADA IBU HAMIL DALAM MENURUNKAN NYERI PINGGANG PADA TRIMESTER 3 Wibowo, Berliana Windi; Munawwarah, Muthiah; Amir, Trisia Lusiana; Noviati, Nuraini Diah
Jurnal Ilmiah Fisioterapi Vol 7 No 1 (2024): Jurnal Ilmiah Fisioterapi
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/jif.v7i1.4418

Abstract

Objective: To determine the different effects of kinesiotapping and massage to reduce low back pain in pregnant women in the 3rd trimester. Methods: This study is quasi-experimental with a pre-post test group design, where pain is measured using Numeric Rating Scale (NRS). The sample consisted of 14 people at Dinar Kusuma Dewi Midwife Practice in Karawang. The sample was divided into 2 treatment groups: treatment group I consisted of 7 people given kinesiotapping intervention and treatment group II consisted of 7 people given massage intervention. Results: The normality test using the Shapiro Wilk test found that the data was not normally distributed with a p value < 0.05, while the homogeneity test using Levene's test found that the data was homogeneous with a p value > 0.05. The results of hypothesis testing I using the Wilcoxon test obtained a value of p = 0.017 with median (min-max) before and after amounting to 5 (4-6) and 3 (1-3). The results of hypothesis II using the Wilcoxon test obtained a p value = 0.016 with median (min-max) before and after of 5 (4-8) and 1 (0-3). The results of hypothesis III test using Mann Whitney test obtained p value = 0.006 with a median (min-max) before and after of 3 (2-4) and 4 (4-6). Conclusion: There is a significant difference between kinesiotapping intervention and massage to reduce low back pain in 3rd trimester pregnant women.
Smart Grids: Integrating AI for Efficient Renewable Energy Utilization Noviati, Nuraini Diah; Maulina, Sondang Deri; Smith, Sarah
International Transactions on Artificial Intelligence Vol. 3 No. 1 (2024): International Transactions on Artificial Intelligence
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/italic.v3i1.644

Abstract

The urgent global shift from fossil fuels to renewable energy sources necessitates innovative solutions to address energy system management challenges. Smart grids, equipped with sophisticated infrastructures, play a crucial role in this transition. This study integrates Artificial Intelligence (AI) into smart grids to enhance their efficiency and reliability, directly supporting the United Nations Sustainable Development Goals (SDGs), particularly SDG 7 (Affordable and Clean Energy), SDG 9 (Industry, Innovation, and Infrastructure), and SDG 11 (Sustainable Cities and Communities). Employing a mixed-methods approach, the research utilizes historical and real-time data, applying machine learning algorithms such as Linear Regression, Support Vector Regression (SVR), Recurrent Neural Networks (RNN), and Long ShortxTerm Memory (LSTM) for predictive accuracy in energy management. Optimization techniques like Genetic Algorithms and Particle Swarm Optimization (PSO) are also implemented for resource scheduling and grid balancing. The results demonstrate significant improvements, with an 11.76% increase in energy efficiency and grid stability, a 66.67% reduction in prediction errors, and a 20% decrease in operational costs compared to conventional systems. These enhancements highlight the transformative potential of AI in smart grids, promoting more efficient and sustainable energy utilization. The study concludes that AI-driven smart grids are pivotal in achieving the SDGs by providing scalable and efficient solutions for renewable energy integration, thereby fostering sustainable development and reducing environmental impacts.
The relationship of stride length and walking pain to the dynamic balance of the elderly: The relationship of stride length and walking pain to the dynamic balance of the elderly -, Nabila Tri Lestari; Munawwarah, Muthiah; Meidian, Abdul Chalik; Noviati, Nuraini Diah
Indonesian Journal of Physiotherapy Vol 5 No 2 (2025): Indonesian Journal of Physiotherapy
Publisher : Universitas Pembangunan Nasional Veteran Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52019/ijpt.v5i2.8515

Abstract

Background: Changes in stride length are something that is closely related to unhealthy conditions and is a decrease in the ability to carry out activities independently. Nearly 50% of people over the age of 65 have problems walking. Method: This is a cross sectional study, the sample consisted of 34 people at Posyandu for the Elderly Melati Putih RW 02 East Jakarta. The sample was measured for stride length using a meterline with units measured in cm and dynamic balance was measured using the TUG test with units of time measured in seconds using a stopwatch. Results: The mean ± SD value for the step length variable was 79.14 ± 12.63, the mean value for the walking pain variable was 4.97 ± 1.62 and the mean value for the dynamic balance variable was 21.18 ± 6.63. Testing normality using the Shapiro Wilk Test, the data obtained a normal distribution of 2 and abnormally 1, while with hypothesis testing using Spearman Rank Correlation, the p value was <0.05 and had a value of r -0.738 for step length on dynamic balance and r 0.617 for walking pain on balance. dynamic, thus showing that Ha is accepted, meaning there is a relationship between step length, walking pain and dynamic balance in the elderly. Conclusion: There is a relationship between stride length, walking pain and dynamic balance in the elderly. Keywords: Stride Length; Dynamic Balance; Pain; Fall Risk
Co-Authors -, Nabila Tri Lestari Abdul chalik meidian Amir, Trisia Lusiana Maulina, Sondang Deri Muthiah Munawwarah Smith, Sarah Wibowo, Berliana Windi