Article Per Year (5 Year)
p-Index From 2020 - 2025
0.817
P-Index
This Author published in this journals
All Journal Jurnal Informatika Journal of Medical Science; Jurnal Ilmu Medis Rumah Sakit Umum Daerah dr. Zainoel Abidin, Banda Aceh Jurnal KALANDRA
Rosni
Unknown Affiliation
Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Civil Engineering, Building, Construction & Architecture Computer Science & IT Dentistry Economics, Econometrics & Finance Education Health Professions Immunology & microbiology Medicine & Pharmacology Nursing Public Health

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
Efektivitas Terapi Non-Farmakologis Terhadap Nyeri Tindakan Invasif Pada Neonatus Di Rumah Sakit Umum Daerah dr. Zainoel Abidin Sri Intan Rahayuningsih; Rosni; Ramlah; Nova Fajri
Journal of Medical Science Vol 2 No 1 (2021): Journal of Medical Science
Publisher : LITBANG RSUDZA

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (368.309 KB) | DOI: 10.55572/jms.v2i1.40

Abstract

Prosedur tindakan invasif merupakan salah satu prosedur yang sering dilakukan di rumah sakit khususnya di ruang NICU dan menimbulkan nyeri pada neonatus. Beberapa manajemen nyeri non-farmakologi untuk menurunkan nyeri adalah dengan pemberian pacifier, ASI, dan bedung. Namun metode tersebut masih perlu diukur keefektifannya dalam manajemen menurunkan nyeri. Tujuan dari penelitian ini adalah untuk mengidentifikasi efektivitas terapi non-farmakologis terhadap nyeri tindakan invasif pada neonatus di Rumah Sakit Umum Daerah dr. Zainoel Abidin Banda (RSUDZA) Aceh. Penelitian ini menggunakan desain randomized control trial (RCT). Populasi dalam penelitian ini adalah seluruh neonatus risiko tinggi yang tidak mendapatkan obat sedasi di ruang NICU level IIA dan IIB RSUDZA. Jumlah sampel sebanyak 19 orang dan menggunakan teknik randomisasi alokasi yang terdiri dari empat kelompok yaitu kelompok kontrol, kelompok intervensi 1 (pemberian pacifier), kelompok intervensi 2 (pemberian pacifier dan bedung), dan kelompok intervensi 3 (pemberian ASI dan bedung). Skala nyeri pada sampel dinilai menggunakan intrumen neonatal infant pain scale (NIPS). Analisis statistik menggunakan uji normalitas, uji homogenitas, uji anova dan uji Post Hoc Bonferroni. Hasil penelitian ini menunjukkan bahwa data normal, homogen dan diperoleh p valu e0,364 yang berarti tidak ada perbedaan tingkat nyeri antar semua kelompok penelitian. Namun secara klinis, kelompok intervensi pemberian pacifier dan bedung memiliki skala nyeri terendah (2,25) dan memiliki perbedaan rerata 2,6 poin dengan kelompok kontrol. Diharapkan seluruh perawat di NICU dapat melakukan pengkajian nyeri pada neonatus terutama saat tindakan invasif agar dapat memberikan manajemen nyeri yang tepat.
Pelatihan Pemanfaatan Looker Studio dalam Analisis Data dan Dashboard Statistik bagi Peningkatan Kompetensi Siswa SMKS Nurul Huda Pringsewu Rosni; Mahrani, Dwi; Fitriawati , Andi; Sofia, Ayu; Yulita, Tiara; Irawan, Agus; Mt, Ma’rufah Hayati; Mahkya, Dani Al; Nasrullah; Simanjuntak, Erica Grace; Irfan, Miftahul; Madonna, Nora; Alfian, Muhammad Nuril; Siregar, Abian Avisena; Lestari, Yushinta Cahya
KALANDRA Jurnal Pengabdian Kepada Masyarakat Vol 4 No 6 (2025): November
Publisher : Yayasan Kajian Riset Dan Pengembangan Radisi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55266/jurnalkalandra.v4i6.605

Abstract

This Community Service (PkM) program aims to enhance students’ competencies in data analysis and statistical dashboard management through the utilization of the Looker Studio application. The training was conducted at SMKS Nurul Huda Pringsewu, involving students as participants. The training methods included lectures, demonstrations, and hands-on practice in processing data and presenting it in the form of interactive dashboards. The results of the program showed that students were able to understand the basic concepts of data exploration, the purpose of data visualization, and the use of key features in Looker Studio. In addition, students’ skills in selecting appropriate chart types according to analytical needs improved significantly. Based on the satisfaction survey, most participants rated the activity as very satisfactory (63%) and satisfactory (16%), although a small proportion expressed dissatisfaction (16%) or were not satisfied (5%). Overall, this PkM activity successfully contributed to improving students’ data literacy and digital skills, which are expected to support them in facing both academic challenges and the demands of a data-driven workforce
Klasterisasi Penyakit pada Data Klaim Rujukan Tingkat Lanjut BPJS Kesehatan Menggunakan Algoritma Density-Based Spatial Clustering of Application with Noise Rivai, Muklas; Huda, Misbahul; Rosni; Dewi, Karina Sylfia
Jurnal Informatika Vol 25 No 2 (2025): Jurnal Informatika
Publisher : Institut Informatika Dan Bisnis Darmajaya

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Over time and with the advancement of technology, an increasing number of disease-claim submissions have been received by Badan Penyelenggara Jaminan Sosial (BPJS) for Health, causing data accumulation to the point that the dataset can now be categorized as Big Data. One of the challenges of Big Data is that it cannot be processed using conventional methods, thus requiring specialized approaches such as data clustering. The purpose of this study is to determine the optimal number of clusters and to analyze the characteristics of the cluster groups. The type of data used is secondary data obtained from the BPJS Health database. The data used consists of claim data from Fasilitas Kesehatan Rujukan Tingkat Lanjutan (FKRTL) under BPJS Health from January 2019 to December 2020. The variables used include childbirth, accidents, catastrophic diseases, and other diseases. The stages of the clustering process include data normalization, parameter determination, application of the Density-Based Spatial Clustering of Application with Noise (DBSCAN) algorithm, and evaluation of cluster results using the silhouette index. The results of the clustering analysis on FKRTL claim data based on the International Statistical Classification of Diseases and Related Health Problems, 10th Revision (ICD-10), show that there are three clusters and one noise cluster, with an average silhouette index of 0.6595942, indicating that the model has a medium structure. Cluster 1 consists of two members with dominant claim categories being accidents and other diseases, cluster 2 consists of 27 members with childbirth as the dominant claim category, cluster 3 consists of four members with catastrophic diseases and other diseases as the dominant claim categories, and the noise cluster consists of one member with childbirth as the dominant claim category.
Co-Authors Agus Irawan Alfian, Muhammad Nuril Arnita Dani Al Mahkya Daulay, Putri Agustin Dewi, Karina Sylfia Dwi Mahrani Fitriawati , Andi Irfan, Miftahul Lestari, Yushinta Cahya Madonna, Nora Misbahul Huda Mt, Ma’rufah Hayati Nasrullah Nita, Arnita Nova Fajri Rahmadi, M Taufik Ramlah Rivai, Muklas Simanjuntak, Erica Grace Siregar, Abian Avisena Sofia, Ayu Sri Intan Rahayuningsih Suciani, Ayu Yulita, Tiara Z, Soedirman