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All Journal Pena Medika : Jurnal Kesehatan Journal of Big Data Analytic and Artificial Intelligence
Tri Martuti
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Computer Science & IT Health Professions Medicine & Pharmacology Nursing Public Health Veterinary

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Asuhan Keperawatan Bersihan Jalan Napas Tidak Efektif Pada Pasien Ny. S Dengan Tb Paru Di Ruang Dahlia RSUD Prof. Dr. Margono Soekarjo Purwokerto Desta Anggoro Saputri; Tri Sumarni; Tri Martuti
Pena Medika Jurnal Kesehatan Vol 13, No 1 (2023): PENA MEDIKA JURNAL KESEHATAN
Publisher : Universitas Pekalongan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31941/pmjk.v13i1.3044

Abstract

Tuberculosis (TB) is an infectious disease caused by Mycobacterium Tuberculosis. The method in this case study is descriptive with the subject of one Pulmonary Tuberculosis patient. The pharmacological actions that have been given are Acetulcysteine tab 3x200 mg given IV to relieve phlegm, non-pharmacological measures that are carried out, namely effective coughing and chest physiotherapy which are given every morning for three days. Conclusion: effective cough and chest physiotherapy in clearing blocked airways in Pulmonary Tuberculosis patients. Therefore, it is hoped that nurses can provide effective coughing and chest physiotherapy as non-pharmacological measures to help overcome ineffective airway clearance in patients with pulmonary tuberculosis.
Application of K-Means Clustering for Student Class Division System Tri Martuti; Eviana Tjatur Putri; Gusmana, Roman
Journal of Big Data Analytic and Artificial Intelligence Vol 6 No 2 (2023): JBIDAI Desember 2023
Publisher : STMIK PPKIA Tarakanita Rahmawati

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.71302/jbidai.v6i2.35

Abstract

SMP Negeri 2 Malinau Utara is a junior high school in Desa Putat, Malinau Utara, Malinau, Kalimantan Utara and has 127 students. Currently, the class division process is inefficient and random. On the other hand, the clustering process' class division must be able to provide each class a balanced number of students. This study proposes the grades of Indonesian and English languages, Mathematics, and Natural Sciences for the clustering. K-means is applied to evenly group students based on predetermined value criteria to achieve the expected class formation. K-Means Clustering is an algorithm in data analysis to group a set of data into several groups based on their similar characteristics. In the clustering process, the distance between the data and the Centroid was calculated using the Euclidean Distance. Initial centroid determination and data distance calculation with the initial centroid were performed until the centroid member remains unchanged. The initial centroid was determined using a combination of 1,081 times obtained from 47 data combinations for two clusters. This research has been successfully applied to classify students using the K-Means Clustering method and select a balanced number of students between one class and another. Next, combine some students in each cluster with other clusters, so that each class has different levels of learning ability. With the combination of two clusters in one class, it is expected that students can help each other during the learning process.
Co-Authors Desta Anggoro Saputri Eviana Tjatur Putri Gusmana, Roman Tri Sumarni