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HUBUNGAN PENGETAHUAN TENTANG MANAJEMEN STRES DENGAN KESEHATAN MENTAL MAHASISWA AKHIR FAKULTAS KEDOKTERAN Saputri, Deby Indah
Jurnal Kesehatan Tambusai Vol. 6 No. 2 (2025): JUNI 2025
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jkt.v6i2.43676

Abstract

Stres akademik merupakan kondisi yang membuat mahasiswa tingkat akhir lebih rentan terhadap masalah kesehatan mental, seperti tingkat stres, kecemasan, dan depresi. Stres yang tinggi Berdasarkan latar belakang tersebut, penelitian ini bertujuan untuk mempelajari hubungan antara pengetahuan mahasiswa akhir Fakultas Kedokteran dengan kesehatan mental. Metode penelitian ini merupakan penelitian kuantitatif dengan pendekatan cross-sectional. Penelitian ini dilakukan di Fakultas Kedokteran Universitas Mulawarman yang berlokasi di Jl. Krayan Samarinda. Waktu penelitian berlangsung selama 1 bulan November 2024, Populasi Mahasiswa Tingkat Akhir Fakultas Kedokteran Universitas Mulawarman yang terdaftar pada semester 7, semester akhir. Sampel penelitian sebanyak 86 mahasiswa akhir dengan menggunakan Teknik Proportional Random Sampling. Pengumpulan data dilakukan secara online dengan menggunakan Google form yang disebarkan kepada Responden melalui pesan WhatsApp. Hasil penelitian untuk tingkat Pengetahuan Sedang sebesar 36 (56,3%) dan tingkat stres Normal sebesar 20(51,3%). Karena p-value < 0,05 maka terdapat perbedaan yang signifikan antara pengetahuan dengan tingkat stres, artinya tingkat pengetahuan mempengaruhi tingkat stres individu.
Gambaran Kasus Gondongan pada Siswa SD Normal Islam Samarinda Wardani, Nunuk Kusuma; Saputri, Deby Indah; Nugraha, Purwa; Nozomi, Alwan Zakki; Noor, Muhammad; Wisnuwardani, Ratih Wirapuspita; Pakki, Irfansyah Baharuddin
Jurnal Epidemiologi Kesehatan Komunitas Vol 10, No 3: Agustus 2025
Publisher : Master of Epidemiology, Faculty of Public Health, Diponegoro University, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jekk.v10i3.25482

Abstract

Background: Mumps is a contagious disease caused by paramyxovirus infection that primarily affects children and adolescents. In 2024, a surge of mumps cases was reported in Samarinda, particularly at Sekolah Dasar Normal Islam Samarinda. This study aimed to describe the characteristics of mumps cases based on age, sex, and epidemiological distribution at the school during October–November 2024.Methods: This descriptive observational study utilized primary and secondary data. Purposive sampling was applied to include students who met the clinical diagnostic criteria for mumps, identified through school health reports and direct observation. Data collection covered number of cases, age, sex, symptoms, and transmission patterns. Analysis was performed descriptively using Microsoft Excel. A total of 78 students were identified with mumps symptoms. The index case was reported on October 3, 2024, in a male fifth-grade student presenting parotid gland swelling, fever, and history of close contact within the past 25 days.Results: The majority of cases occurred among male students (61.5%), particularly those in grades 5 and 6, with 11 years old being the most affected group. The most common clinical manifestations included fever and parotid gland swelling. Notably, none of the students had received the MMR vaccination. The epidemic curve showed a sharp increase in October 2024, followed by a decline in November, with an overall attack rate of 12.5%.Conclusion: Low immunization coverage, overcrowded classrooms, and delays in early detection played a significant role in facilitating transmission within the school. Strengthening vaccination programs, implementing health education, improving hygiene protocols, and ensuring early isolation of suspected cases are recommended to control and prevent further mumps outbreaks in school settings. Keywords: Mumps; epidemiology; imunization; disease prevention; school children
Time series analysis of outpatient visits at RSUD X In Samarinda using the ARIMA model Saputri, Deby Indah; Anggraeni, Ike; Isnuwardana, Ronny
Mulawarman International Conference on Tropical Public Health Vol. 2 No. 2 (2025): The 4th MICTOPH
Publisher : Faculty of Public Health Mulawarman University, Indonesia

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Abstract

Background : Efficient hospital resource planning, including staff allocation and pharmaceutical logistics, heavily relies on accurate patient visit volume forecasting. Daily outpatient visit data at Regional Hospital from January 2023 to February 2025 shows high volatility and a strong weekly pattern (5-day work cycle). Therefore, a forecasting method is needed that can describe the patterns and trends of patient visits based on historical data. Methods commonly used for time series forecasting is ARIMA (Autoregressive Integrated Moving Average). This model is capable of capturing seasonal patterns and trends within the data, making it useful for predicting the number of future visits with a high level of accuracy. Objective : This study aims to identify the most optimal time series forecasting model using internal seasonal SARIMA and external regression SARIMAX analysis. Research Methods/ Implementation Methods : This study design is repeated cross-sectional. Outpatient visit data was divided into training (2023-2024) and testing (January-February 2025) sets for accuracy validation, measured by Root Mean Squared Error (RMSE). Results : In the first stage, the seasonal ARIMA model without explanatory variables, namely ARIMA(0,0,1)(2,1,0)[5], passed the Ljung-Box diagnostic test (p>0.05) but showed low predictive accuracy (RMSE 281.01). The second stage involved using explanatory (exogenous) variables such as Monday, Friday, and Public Holidays. A regression model with ARIMA(0,1,1) errors was identified as the superior model with an RMSE of 194.39. Regression coefficients showed a significant impact from specific days: Monday (+50 visits, 95% CI 32, 68), Friday (-91 visits, 95% CI -73, -109), and Public Holidays (-489 visits, 95% CI -463, -516). ConclusioAlthough the Ljung-Box test resulted in p<0.05, indicating that there are still residuals not fully explained by the model, it still provides important insights for hospital operational planning.n/Lesson Learned :