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Prevalensi Kejadian Anemia pada Siswi SMP Negeri 1 Kintamani Ni Putu Diah Witari; Sri Ratna Dewi; Fransiscus Fiano Anthony Kerans; Aanak Agung Ayu Asri Prima Dewi; Ida Kurniawati; Komang Trisna Sumadewi; Luh Gde Evayanti; Dewa Ayu Agung Alit Suka Astini
Jurnal Ilmu Kedokteran dan Kesehatan Indonesia Vol. 5 No. 3 (2025): November : Jurnal Ilmu Kedokteran dan Kesehatan Indonesia
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jikki.v5i3.7411

Abstract

Anemia is a condition characterized by low levels of hemoglobin or red blood cell counts in the bloodstream, resulting in a decreased ability of the blood to transport oxygen throughout the body. The prevalence of anemia is relatively high, especially in developing countries. In Indonesia, there has been an increase in the prevalence of anemia among adolescents aged 15-24 years, reaching 13.6%. In Bali, the recorded prevalence of anemia is 21.9%, with Bangli Regency ranking second. Kintamani is one of the sub-districts located in Bangli Regency, and SMP Negeri 1 Kintamani is one of the middle schools in the area. This study aims to identify the prevalence of anemia among female students of SMP Negeri 1 Kintamani. The method used is a cross-sectional study involving 147 respondents. Hemoglobin levels were measured using the Easy Touch GCHb device. The results indicate that the prevalence of anemia among female students at SMP Negeri 1 Kintamani is 18.37%, with mild anemia at 12.24% and moderate anemia at 6.12%. The majority of respondents are 12 years old.
Pengaruh Pengetahuan dan Kepatuhan Ibu Hamil Minum Tablet Tambah Darah di Desa Selulung Kabupaten Bangli Anny Eka Pratiwi; Sri Ratna Dewi; Tangking Widarsa; I Wayan Darwata
JURNAL RISET RUMPUN ILMU KESEHATAN Vol. 4 No. 2 (2025): Agustus : Jurnal Riset Rumpun Ilmu Kesehatan
Publisher : Pusat riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jurrikes.v4i2.5414

Abstract

Anemia in pregnant women is one of the contributing factors to stunting in toddlers. The consumption of iron (Fe) tablets by pregnant women requires supervision from family members to support the success of the stunting reduction program in Bangli Regency. Iron tablet intervention in pregnant women has been proven to reduce the risk of complications, lower the incidence of low birth weight in infants, and decrease maternal mortality during childbirth. This study used a cross-sectional survey design, involving 48 pregnant women. Data collection was conducted using total sampling during the period from January 2024 to January 2025 at Kintamani IV Public Health Center. Bivariate data analysis was carried out using the chi-square test. The results of the study showed that 68% of pregnant women experienced mild anemia. Most pregnancies were in the third trimester (39%), and 43% of the participants were in their first pregnancy. The majority of the pregnant women had good knowledge levels. There was a significant relationship between pregnant women’s knowledge and their adherence to consuming iron tablets, with a p-value of 0.019. The odds ratio (OR = 5.014) indicated that pregnant women with good knowledge were five times more likely to adhere to iron tablet consumption compared to those with limited knowledge. Support and monitoring of the nutritional status of pregnant women are essential to reduce the incidence of low birth weight and stunting among toddlers in Selulung Village, Kintamani District.  
Noise Exposure-Induced Functional Anatomical Changes: Impact on Superoxide Dismutase, Tumor Necrosis Factor-Alpha, and Adiponectin Suka Astini, Dewa Ayu Agung Alit; Luh Gde Evayanti; Sri Ratna Dewi
JURNAL KESEHATAN LINGKUNGAN Vol. 18 No. 1 (2026): JURNAL KESEHATAN LINGKUNGAN
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jkl.v18i1.2026.1-9

Abstract

Introduction: Environmental noise is a non-auditory stressor that can trigger inflammatory and oxidative responses in the body. Continuous noise exposure is associated with increased production of pro-inflammatory cytokines and reactive oxygen species (ROS). This can disrupt the body's cellular balance. This study aimed to determine the effects of chronic noise exposure on serum superoxide dismutase (SOD), tumor necrosis factor-alpha (TNF-α), and adiponectin levels in wistar rats. Methods: This study used a laboratory based experimental design, involving twenty-four adult male Wistar rats. The rats were randomly divided into two groups: a control group and a treatment group. The treatment group was exposed to 95 dB noise for four hours daily for 14 consecutive days, while the control group received no exposure. SOD, TNF-α, and adiponectin levels were determined using ELISA. The independent t-test was used for statistical analysis. Results and Discussion: TNF-α was significantly higher (p < 0.05) and adiponectin was significantly lower (p < 0.05) in the treatment group than in the control group. SOD levels did not differ significantly across groups (p > 0.05). Noise exposure causes metabolic and inflammatory disruptions, as evidenced by the rise in TNF-α and fall in adiponectin, but the SOD levels remain unchanged, suggesting a limited antioxidant response. Conclusion: An inflammatory response and decreased adiponectin were caused by noise exposure at 95 dB for 14 days, suggesting a possible risk of metabolic dysfunction. Nonetheless, the stability of SOD levels indicates that enzymatic antioxidant action is maintained in these circumstances.
Penerapan Komputer dalam Identifikasi Barang di E-Commerce Berbasis AI Trisatin Panggabean; Salsabila Yusra; Sri Ratna Dewi
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 3 No. 1 (2025): Februari : Jurnal Sistem Informasi dan Ilmu Komputer
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59581/jusiik-widyakarya.v3i1.4455

Abstract

This research explores the implementation of computer vision technology in AI-based e-commerce platforms to enhance product identification and improve user experience. The study specifically examines the use of deep learning algorithms, particularly Convolutional Neural Networks (CNN), to automate product recognition and classification. The results indicate that AI-driven image search features significantly increase the speed and accuracy of product search, leading to greater customer engagement. However, challenges such as the need for high-quality datasets, varying image quality, and high initial investment costs were identified as barriers to effective implementation. The findings suggest that overcoming these obstacles can lead to improved operational efficiency and customer satisfaction. The success of AI in e-commerce depends on robust infrastructure, data quality, and skilled workforce training.