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All Journal Journal of Applied Intelligent System Journal of Economics, Accounting, Tax and Management (Jecatama)
Ayu Hendrati Rahayu
Politeknik TEDC Bandung
Humanities Economics, Econometrics & Finance Social Sciences

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Classification of X-Ray Images of Normal, Pneumonia, and Covid-19 Lungs Using the Fuzzy C-Means (FCM) Algorithm Dini Rohmayani; Ayu Hendrati Rahayu
Journal of Applied Intelligent System Vol 7, No 1 (2022): Journal of Applied Intelligent System
Publisher : Universitas Dian Nuswantoro and IndoCEISS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/jais.v7i1.5512

Abstract

Lung disease has a very serious impact on the respiratory system and can be dangerous if not treated immediately. At this time, lung diseases that are often encountered by the public include pneumonia and 2019 coronavirus. Many people mistake the disorder that occurs to him because the symptoms of Covid-19 and pneumonia are very similar. Thus, it is very important to know the difference between the two diseases so that early treatment can be carried out. Based on the problems that have been described, the author will propose a study entitled "Classification of X-ray Images of Normal Lungs, Pneumonia, and Covid-19 Using the Fuzzy C-Means (FCM) Algorithm". The aim of this study is to assist in classifying normal, pneumonia, and Covid-19 lungs. The reason for choosing this algorithm is that this algorithm has advantages in grouping cluster centers which are more optimal than other methods.
Naive Bayes Performance in Analysis of Public Opinion Sentiment Against COVID-19 Ayu Hendrati Rahayu; Ari Sudrajat
Journal of Applied Intelligent System Vol 7, No 3 (2022): Journal of Applied Intelligent System
Publisher : Universitas Dian Nuswantoro and IndoCEISS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/jais.v7i3.7134

Abstract

The huge impact caused by the COVID-19 pandemic has made many people express their opinions on Twitter social media. There are various responses given by the community that are negative and positive. The dataset comes from kaggle with more than 750 tweets of data. Classification designed by the Naive Bayes method. Implementation through preprocessing, case folding, tokenizing, stopword removal, TF-IDF, and cross validation has been able to produce quite high accuracy. After classification, validation will be carried out with Cross Fold Validation. The best value is on cv5 where accuracy = 0.847, precision = 0.855, recall = 0.83, and f1 score = 0.842.
ANALISIS PERBEDAAN TARIF RIIL RUMAH SAKIT DENGAN TARIF INA-CBG’s PASIEN RAWAT INAP PADA KASUS PERCUTANEOUS CORONARY INTERVENTION (PCI) GUNA MENUNJANG EFISIENSI BIAYA RUMAH SAKIT BANDUNG Ayu Hendrati Rahayu; Nadia Meythalia Setiawan
Journal of Economics, Accounting, Tax, and Management (JECATAMA) Vol 1 No 1 (2022): JECATAMA
Publisher : Journal of Economics, Accounting, Tax, and Management (JECATAMA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (384.936 KB)

Abstract

Berdasarkan studi pendahuluan yang dilakukan peneliti di Instalasi Rekam Medis RSAU dr. M. Salamun Bandung, ditemukan perbedaan tarif rill rumah sakit dan tarif INA-CBG’s pada pasien kardiologi tindakan Percutaneous Coronary Intervention (PCI) yang dilihat dari software INA-CBG’s pada bulan Juli sampai dengan bulan Desember tahun 2019 memiliki perbedaan tarif yang sangat siginifikan dan dapat menyebabkan kerugian pada pihak rumah sakit. Tujuan dari penelitian ini adalah untuk mengetahui bagaimana upaya yang dilakukan oleh rumah sakit terhadap perbedaan tarif rill rumah sakit dan INA-CBG’s agar biaya rumah sakit efisien.Metode penelitian yang digunakan adalah metode penelitian deskriptif dengan pendekatan kuantitatif dan teknik pengumpulan data dengan cara observasi, wawancara, studi kepustakaan dan teknik dokumentasi. Hasil penelitian dari 65 pasien rawat inap kardiologi dengan tindakan Percutaneous Coronary Intervention (PCI) yang diteliti peneliti menemukan tarif rill rumah sakit lebih tinggi dari tarif INA-CBG’s dengan tarif tertinggi rumah sakit sebesar Rp. 147.475.394,- sedangkan tarif tertinggi INA-CBG’s sebesar Rp. 50.437.500,- dan hal ini menunjukan bahwa selisih antara tarif rill rumah sakit dengan tarif INA-CBG’s tidak sedikit dan menyebabkan kerugian yang lumayan besar bagi rumah sakit, faktor yang menyebabkan terjadinya perbedaan tarif rill rumah sakit adalah penjaminan BJS yang kurang sedangkan biaya tindakan Percutaneous Coronary Intervention (PCI) sangat tinggi, maka rumah sakit harus melakukan upaya pengendalian biaya dengan menerapkan standarisasi pelayanan agar biaya rumah sakit menjadi lebih efisien dan tidak terjadinya tarif rill rumah sakit yang lebih tinggi dibandingkan INA-CBG’s. Saran yang diberikan sebaiknya upaya pengendalian biaya dengan menerapkan standarisasi pelayanan dan dilakukan sosialisasi agar terlaksana lebih maksimal.
Co-Authors Ari Sudrajat Dini Rohmayani Nadia Meythalia Setiawan