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All Journal WARTA Journal of Information Technology and Computer Engineering Plexus Medical Journal
Coana Sukmagautama
Departemen Ilmu Penyakit Dalam Rumah Sakit Universitas Sebelas Maret, Sukoharjo, Indonesia
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Health Professions Medicine & Pharmacology Public Health

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Optimalisasi Palang Merah Remaja dalam Pencegahan Penyakit Tidak Menular di Era COVID-19 Risalina Myrtha; Amelya Augusthina Ayusari; Ratna Kusumawati; Alamanda Murasmita; Coana Sukmagautama; Adigama Priamas; Ainal Fadly
WARTA LPM WARTA LPM, Vol. 24, No. 2, April 2021
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/warta.v24i2.12327

Abstract

Penyakit Tidak Menular (PTM) merupakan penyebab kematian terbesar di dunia yang memberikan beban sosial ekonomi yang berat. PTM merupakan penyakit yang dapat dicegah dengan mengendalikan faktor risiko sejak dini. Generasi muda dapat berkontribusi dalam pencegahan PTM dengan cara membagikan pesan-pesan bermanfaat tersebut ke lingkungan keluarga, sekolah, maupun masyarakat. Kegiatan ini merupakan kegiatan persembahan alumni untuk memberikan pelatihan pencegahan PTM yang dilakukan secara daring. Kegiatan ini diikuti oleh anggota PMR SMA Negeri 1 Surakarta. Organisasi ini merupakan organisasi yang cukup aktif, tetapi selama ini belum pernah mengangkat tema PTM dalam kegiatannya. Pengetahuan anggotanya tentang PTM masih kurang. SMA Negeri 1 Surakarta merupakan salah satu sekolah favorit di Surakarta dan menjadi percontohan dan tolak ukur prestasi bagi sekolah lainnya. Kegiatan ini dibagi 2 sesi yaitu pencegahan dan penatalaksanaan awal PTM dan adaptasi kebiasaan baru pada era tatanan baru. Pelatihan ini diikuti oleh 34 orang anggota PMR SMA Negeri 1 Surakarta. Didapatkan kenaikan signifikan rerata nilai postest (nilai rerata 10) dibandingkan pretest (nilai rerata 6,24+2,26; (p0,001). 68% peserta sangat setuju pelatihan ini menarik, 56% peserta sangat setuju bahwa materi pelatihan ini mudah dipahami, dan 84% peserta sangat setuju materi pelatihan ini relevan dengan kondisi saat ini. Pelatihan ini menambah pengetahuan tentang pencegahan PTM pada anggota PMR. Adanya pandemi COVID-19 menyebabkan adanya kebiasaan baru. Apabila tidak dikelola dengan baik, kondisi ini dapat menyebabkan timbulnya faktor risiko PTM atau memperburuk faktor risiko yang ada. Kami menyarankan dilakukannya skrining dini faktor risiko PTM pada semua siswa.
Increased Mammogram Image Contrast Using Histogram Equalization And Gaussian In The Classification Of Breast Cancer Febri Liantoni; Coana Sukmagautama; Risalina Myrtha
JITCE (Journal of Information Technology and Computer Engineering) Vol 4 No 01 (2020): Journal of Information Technology and Computer Engineering
Publisher : Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (613.675 KB) | DOI: 10.25077/jitce.4.01.40-44.2020

Abstract

Breast cancer is one of the most common diseases among women in several countries. One of the most common methods to diagnose breast cancer is mammography. In this study, we propose a classification study to differentiate benign and malignant breast tumors based on mammogram image. The proposed system includes five major steps, i.e. preprocessing, histogram equalization, convolution, feature extraction, and classification. Image is cropped using region of interest (ROI) at preprocessing stage. In this study, we perform image contrast quality enhancement of the mammogram to view the breast cancer better. Image contrast enhancement uses histogram equalization and Gaussian filter. Gray-Level Co-Occurrence Matrix (GLCM) is used to extract the mammogram features. There are five features used i.e. entropy, correlation, contrast, homogeneity, and variance. The last step is to classify using naïve Bayes classifier (NBC) and k-nearest neighbor (KNN). Based on the hypothesis, the accuracy of NBC method is 90% and the accuracy of KKN method is 87.5%. So, the mammogram image contrast enhancement is well performed.
The Profil Klinis dan Epidemiologi Pasien Covid-19 di Sukoharjo Muhammad Rasyid Ridho; Coana Sukmagautama; Frieska Dyanneza
Plexus Medical Journal Vol. 1 No. 3 (2022): Juni
Publisher : Fakultas Kedokteran, Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/plexus.v1i3.44

Abstract

Introduction: The COVID-19 pandemic is still a very important concern in various parts of the world. The disease that infects the respiratory tract does have similar characteristics to SARS and MERS, but increases sporadically in various regions. Therefore, this study aims to conduct research on clinical profiles of COVID-19 patients at UNS Sukoharjo Hospital. Methods: This research is a descriptive observational study with a cross sectional approach. The population in this study were patients with confirmed COVID-19 at UNS Sukoharjo Hospital for the period December 2020 to May 2021, aged more than 18 years and had no incidents. The data obtained are then sorted based on the criteria and analyzed using descriptive analysis. Results: Based on the results of the study, the number of samples was 469 with the following characteristics: (1) the most age group was 46 – 59 (40.3%); (2) male 53.9% and female 46.1%; (3) the most confirmed jobs are private employees; (4) the most common symptoms were cough (69.9%), shortness of breath (66.5%0, and fever (62.4%);(5) the most common comorbidities were hypertension (29.6%) followed by diabetes mellitus (28.6%); (6 ) Complete blood counts generally have a normal average, while blood sugar, laboratory related to kidney, liver, D-Dimer, and CRP have an average above normal, and ALC below normal, (7) the mortality rate is 22.4%; (8) 98.1% of cases had pathological thorax readings, 81.6% pneumonia, (9) mean length of negative conversion of patients 11.28 days. Conclusion: The clinical and epidemiological profiles of COVID-19 patients at UNS Hospital as a whole have similarities with data in Indonesia as a whole and several other countries. Keywords: Clinical Profile; COVID-19; Epidemiology; UNS Hospital
Co-Authors Adigama Priamas Ainal Fadly Alamanda Murasmita Ayusari, Amelya Augusthina Febri Liantoni Frieska Dyanneza Muhammad Rasyid Ridho Ratna Kusumawati Risalina Myrtha Risalina Myrtha