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Hubungan tingkat pengetahuan terhadap perilaku swamedikasi penggunaan obat analgesik di Banjar Baluk II Kecamatan Negara: The relationship between knowledge level and self-medication behavior in the use of analgesic drugs in Banjar Baluk II, Negara District Buana, Putu Negia Suci Cahyani; Wintariani, Ni Putu; Reganata, Gde Palguna; Sutema, Ida Ayu Manik Partha
Widya Kesehatan Vol. 7 No. 2 (2025): Widya Kesehatan
Publisher : Universitas Hindu Indonesia (UNHI) Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32795/v6kdej02

Abstract

Latar belakang: Pengobatan sendiri adalah praktik lokal untuk menyelesaikan perawatan kesehatan untuk diri sendiri tanpa berkonsultasi dengan ahli kesehatan. Tujuan: Tujuan dari penelitian ini adalah untuk memahami hubungan antara tingkat informasi dan perilaku pengobatan sendiri obat penghilang rasa sakit di Banjar Baluk II, Wilayah Negara, dan hubungan sosiodemografi antara tingkat informasi dan pengobatan sendiri. Penelitian menggabungkan pendekatan cross-sectional untuk penyelidikan kuantitatif. Metode: Penelitian ini termasuk kuantitatif jenis penelitian observasional analitik dengan pendekatan cross sectional. 95 responden dijadikan sebagai contoh penelitian. Lokasi penelitian ini dilakukan di Banjar Baluk II Kecamatan Negara dilakukan pada bulan Maret sampai bulan Mei tahun 2023. Analisis statistik menggunakan pengujian analisis korelasi pada uji Spearmen’s Rank. Hasil: Terdapat 42 (44,2%) responden yang memiliki informasi kurang, 46 (48,4%) yang memiliki informasi cukup, dan 7 (7,4%) yang memiliki informasi sangat baik. Ada 57 responden (60,0%) yang berperilaku baik saat menggunakan obat penghilang rasa sakit untuk pengobatan sendiri, dan 38 responden (40,0%) berperilaku baik. Tingkat pengetahuan terhadap perilaku terdapat nilai Spearmen’s Rank yang positif sebesar 0,514 termasuk dalam kategori sedang dengan signifikansi sebesar 0,000 (0,000<0,05). Terdapat hubungan antara usia (r=0, 0,334), pendidikan (r= 0,443) dan pekerjaan (r= 0,303) (p-value= 0,000). Kesimpulan: Terdapat hubungan signifikan antara tingkat pengetahuan terhadap perilaku swamedikasi obat analgesik di Banjar Baluk II Kecamatan Negara adalah cukup baik serta terdapat hubungan yang signifikan antara usia, pendidikan dan pekerjaan.
Analysis of Factors Affecting Healing of Acute Pharyngitis Viral Patients in Puskesmas I, Klungkung-Bali Ida Ayu Manik Partha Sutema; Made Sudiari; I Gede Palguna Reganata
WMJ (Warmadewa Medical Journal) Vol 7 No 2 (2022): November 2022
Publisher : Warmadewa University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22225/wmj.7.2.4753.60-69

Abstract

Abstract Antibiotic resistance is closely related to the inappropriate use of antibiotics, namely the indication, dose, frequency, and duration of use. Permenkes No. 5 of 2014 states that acute pharyngitis is given antibiotic therapy if it meets the diagnostic criteria using the center criteria, but this criterion is difficult to apply because doctors take longer to diagnose. Previous research at the Klungkung I Primary Health Center used diagnosis utilizing a swab test. It was found that 100% of bacterial pharyngitis patients were negative. The strategy of delaying antibiotics for 3 days can prevent antibiotic resistance, but in therapy, without antibiotics, it is important to increase the effectiveness of therapy, it is deemed necessary by the researchers to conduct a study to analyze the factors that affect the recovery of patients with acute pharyngitis, which are mainly caused by viruses. Analyzing the factors that affect the recovery of viral pharyngitis patients. The design of the cross-sectional study was through observation of the medical record data of patients who came to the Klungkung Primary Health Center I for 3 months and got diagnostic facilities using the swab test. Patients who got a negative swab test were analyzed for the factors that influenced their recovery. Anti-inflammatory variables, rest, and paracetamol significantly affected the recovery of acute pharyngitis patients (p <0.05), and the importance index in CART analysis found that paracetamol was the most influential, followed by rest, administration of vitamins, and anti-inflammatory. Antibiotics, anti-allergies, and cough medicines do not affect the recovery of patients with acute pharyngitis viral. Paracetamol has the most effect on patient recovery, followed by rest and administration of vitamins, anti-inflammatory has very little effect on the recovery in patients of acute pharyngitis viral. Keywords: acute pharyngitis, cure, CART.
Analisis Ketahanan Lightweight Audio Spectrogram Transformer pada Identifikasi Pembicara Kondisi Berderau I Kadek Arya Sugianta; Gde Palguna Reganata
JISKA (Jurnal Informatika Sunan Kalijaga) Vol. 11 No. 2 (2026): May 2026
Publisher : UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/jiska.6170

Abstract

The use of deep learning models for speaker identification on devices with limited computational resources requires significant architectural optimization. This study evaluates the performance and robustness of the Lightweight Audio Spectrogram Transformer (AST) architecture, which has been extremely compressed to 570,536 parameters. The proposed method uses low-resolution Mel-Spectrogram representations (64x64 pixels) as input for a global self-attention mechanism. Testing was conducted using a 5-Fold Cross Validation scheme on a dataset injected with non-stationary environmental noise from the ESC-50 corpus at various Signal-to-Noise Ratio (SNR) levels. Experimental results show that under ideal conditions, the model achieves a solid average validation accuracy of 70.86% ± 2.69% with a Macro Average F1-score of 0.68 ± 0.03. However, the model’s performance degrades sharply to 17.61% at an SNR of 5 dB and drops to 9.21% under extreme conditions at an SNR of 0 dB. These findings reveal a critical trade-off where radical parameter compression leads to the loss of spectral feature redundancy that acts as an implicit noise filter. This study concludes that while lightweight Transformer mechanisms are highly efficient for Edge AI, the integration of pre-processing modules or noise-robust training strategies is an absolute necessity to maintain identification integrity in noisy real-world environments.