Performance analysis of AES-Blowfish hybrid algorithm for security of patient medical record data

Patient histories who use the services of Badan Penyelenggara Jaminan Sosial (BPJS) Kesehatan are stored in medical record data. Each medical record data contains important information that is very valuable and can be processed to explore new knowledge using a data mining approach. This study aims to help Prof. Dr. Tabrani hospital in classifying patient data who use BPJS Kesehatan, so that the pattern of disease spread is known based on class of service. The data used is patient medical record data in 2019 from October to December, the data will be processed using the K-Means Clustering algorithm with a total of 3 clusters. In cluster 0 (H0) there are 3 patients who are dominated by A09.9 disease (Diarrhea / Dysentery) in Class 2 and Class 3, for cluster 1 (H1) there are 5 patients with more diverse types of disease, while for cluster 2 (H2) there are 5 patients who are predominantly K30 disease (Dyspepsia) in Class 1.

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Accuracy Implementation of Medical Record Management Information System with Waterfall Design System and ISO 9126

Asian Journal of Research in Computer Science ◽

10.9734/ajrcos/2020/v6i230156 ◽

2020 ◽

pp. 36-45

Author(s):

Wahyu Wijaya Widiyanto ◽

Sri Wulandari

Keyword(s):

Information System ◽

Medical Record ◽

Management Information System ◽

Record Management ◽

Management Information ◽

Medical Record Data ◽

Patient Medical Record ◽

Average Value ◽

Record Data ◽

Iso 9126

Aims: Based on the observations of researchers, some health facilities still use manual processes / have not been documented by the information system resulting in slow service, this study aims to improve health services with a medical record information system. Methodology: The method used in this study is an analysis of information systems with the waterfall method and accuracy testing with ISO 9126. Results: The results of this medical record management information system run well based on black-box testing and white box results obtained both from an average value of 82 based on the ISO 9126 scale conversion table. Conclusion: Based on the results of the average value obtained from the validation test carried out on 3 expert examiners, it can be concluded that the application for the validation system for the validation and distribution of this letter has met the ISO 9126 standard with an average good interpretation of a total value of 82, and according to be able to simplify the process of Patient Medical Record Data Management without neglecting the safety aspects of the validation and distribution process, minimizing data loss, simplifying the reporting process and facilitating the processing of patient medical record data.

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Peningkatan Akurasi Klasifikasi Algoritma C 4.5 Menggunakan Teknik Bagging pada Diagnosis Penyakit Jantung

Jurnal Teknologi Informasi dan Ilmu Komputer ◽

10.25126/jtiik.2020752379 ◽

2020 ◽

Vol 7 (5) ◽

pp. 1035 ◽

Cited By ~ 1

Author(s):

Erwin Prasetyo ◽

Budi Prasetiyo

Keyword(s):

Machine Learning ◽

Data Mining ◽

Heart Disease ◽

Medical Record ◽

Medical Field ◽

Medical Record Data ◽

Patient Medical Record ◽

C4.5 Algorithm ◽

Record Data ◽

Increase In Accuracy

Perkembangan teknologi yang begitu pesat menjadikan kebutuhan akan suatu informasi semakin meningkat, sehingga keakuratan suatu informasi menjadi suatu hal yang sangat penting, Terutama keakuratan informasi yang dibutuhkan dalam memprediksi penyakit dalam bidang medis. Dalam proses pengumpulan suatu informasi dibutuhkan metode tertentu, sehingga informasi yang telah diproses menjadi sebuah pengetahuan menggunakan suatu metode tertentu disebut dengan penambangan data atau istilah lainnya adalah data mining. Umumnya data mining digunakan untuk memprediksi suatu penyakit yang bersumber dari data rekam medis pasien, khususnya penyakit jantung. Data penyakit jantung diambil dari dataset UCI Machine Learning Repository. Tujuan dari penulis melakukan penelitian ini yaitu untuk mengetahui penerapan teknik bagging pada algoritma C4.5, mengetahui hasil akurasi dalam algoritma C4.5, dan membandingkan tingkat akurasi dari penerapan teknik bagging pada algoritma C4.5. Dataset yang diklasifikasikan dengan algoritma C4.5 memperoleh akurasi sebesar 72,98%. Hasil akurasi ini dapat ditingkatkan dengan menerapkan teknik bagging menghasilkan akurasi sebesar 81,84%, sehingga terjadi peningkatan akurasi sebesar 8,86% dari penerapan teknik bagging pada Algoritma C4.5. AbstractThe quick development of technology makes the need for information increase, so that the accuracy of the information becomes a very important thing, especially the accuracy of the information needed in predicting diseases in the medical field. In the process of gathering information certain methods are needed, so information that has been processed into knowledge using a certain method is called data mining or other terms is data mining. Data mining is generally used to predict a disease originating from patient medical record data, especially heart disease. Heart disease data is taken from the UCI Machine Learning Repository dataset. The purpose of the authors conducting this research is to determine the application of bagging techniques on the C4.5 algorithm, determine the accuracy of the results in the C4.5 algorithm, and compare the level of accuracy of the application of bagging techniques on the C4.5 algorithm. The dataset classified by the C4.5 algorithm obtained an accuracy of 72.98%. The results of this accuracy can be improved by applying bagging techniques resulting in an accuracy of 81.84%, resulting in an increase in accuracy of 8.86% from the application of bagging techniques in the C4.5 Algorithm.

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Klasterisasi Data Rekam Medis Pasien Menggunakan Metode K-Means Clustering di Rumah Sakit Anwar Medika Balong Bendo Sidoarjo

Matrik Jurnal Manajemen Teknik Informatika dan Rekayasa Komputer ◽

10.30812/matrik.v19i1.529 ◽

2019 ◽

Vol 19 (1) ◽

pp. 186-195

Author(s):

Amir Ali

Keyword(s):

Medical Record ◽

Disease Spread ◽

Medical Record Data ◽

Patient Medical Record ◽

Female Patients ◽

New Information ◽

Record Data ◽

Information Management Systems ◽

Male Patients ◽

Patient Service

The use of information management systems that are owned by hospitals is still limited to being used only for the operation of daily patient service transactions and making reports only. The use of SIMRS is not optimal, it should pile the data stored in the database server can be used to generate new information if we dig deeper with the IT approach. This study uses data mining techniques with K-Means clustering method to cluster the patient's medical record data. The results of this study produce column 4 clusters consisting of districts, diagnoses of diseases, age and sex.The results of this study produce column 4 clusters consisting of districts, diagnoses of diseases, age and sex. Cluster 1 produced many patients consisting of 79(15%) female patients, Cluster 2 produced many patients consisting of 214(50%) male patients. Likewise Cluster 3 produced 89(17%) female patients. people and cluster 4 produced many patients consisting of 152(28%) female patients.The grouping of patient medical record data produces new information about the pattern of grouping of disease spread in each district based on the patient's medical record data from Anwar Medika Hospital as much as 534 data with a completion time of 0.06 seconds

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FAKTOR-FAKTOR YANG MEMPENGARUHI KETERLAMBATAN PENGEMBALIAN BERKAS REKAM MEDIS RAWAT JALAN DI UPT RUMAH SAKIT KHUSUS PARU TAHUN 2019

Jurnal Ilmiah Perekam dan Informasi Kesehatan Imelda (JIPIKI) ◽

10.52943/jipiki.v5i1.364 ◽

2020 ◽

Vol 5 (1) ◽

pp. 108-113

Author(s):

Ali Sabela Hasibuan

Keyword(s):

Service Delivery ◽

Medical Record ◽

Medical Records ◽

Sampling Technique ◽

Medical Record Data ◽

Patient Medical Record ◽

Descriptive Research ◽

Record Data ◽

Quantitative Descriptive ◽

Time Required

ABSTRAK Unit rekam medis merupakan bagian yang penting dalam suatu rumah sakit, karena rekam medis memuat kegiatan mulai dari penerimaan pasien, pencatatan, pengelolaan data rekam medis pasien, penyimpanan dan pengembalian berkas rekam medis.Selain itu, unit rekam medis harus mampu melayani permintaan informasi yang berkaitan dengan data rekam medis dengan cepat, tepat dan akurat pada waktu yang dibutuhkan.Salah satu faktor yang berpengaruh dalam kecepatan pemberian pelayanan kepada pasien adalah ketepatan waktu pengembalian berkas rekam medis ke unit rekam medis.Tujuan umum dari peneliti ini adalah untuk mengetahui faktor keterlambatan pengembalian berkas rekam medis rawat inap di UPT Rumah Sakit Khusus Paru Medan.Jenis penelitian ini menggunakan metode penelitian deskriptif kuantitatif.Populasi dalam penelitian petugas yang berkaitan dengan pengisian rekam medis diRS Khusus Paru yang berjumlah 15 orang, dengan teknik pengambilan sampel adalah total sampling yaitu berjumlah 15 orang.Berdasarkan hasil penelitian yang telah dilakukan peneliti bahwa faktor yang paling mempengaruhi keterlambatan adalah menjalankan prosedur yang telah ditetapkan dan ketidaklengkapan dalam pengisian dokumen rekam medis baik dalam identitas pasien dan ketepatan dalam pengisian diagnosis juga mempengaruhi keterlambatan dalam pengembalian berkas rekam medis dan menjalankan prosedur yang telah ditetapkan di rumah sakit pengembalian berkas rekam medis paling lama 1x24 jam, apabila pengembalian berkas rekam medis mengalami keterlambatan maka akan sangat berpengaruh terhadap assembling,analisis,coding,indixing,filling dan laporan. Kata Kunci : Pengembalian Rekam Medis. ABSTRACT Medical record unit is an important part in a hospital, because medical records contain activities ranging from receiving patients, recording, managing patient medical record data, storing and returning medical record files. In addition, medical record units must be able to service requests for information relating with medical record data quickly, precisely and accurately at the time required. One of the factors that influence the speed of service delivery to patients is the timeliness of returning medical record files to the medical record unit. inpatient medical record at UPT Medan Special Lung Hospital. This type of research uses quantitative descriptive research methods. Population in the study of officers relating to filling medical records in the Special Lung RSR totaling 15 people, with the sampling technique is the total sampling which amounted to 15 people . Brilliant The results of research that have been conducted by researchers that the factors that most influence the delay are carrying out established procedures and incompleteness in filling medical record documents both in the patient's identity and accuracy in filling out the diagnosis also affect the delay in returning the medical record file and carry out the procedures specified in the hospital returns the medical record file for a maximum of 1x24 hours, if the return of the medical record file is delayed it will greatly affect the assembling, analysis, coding, indixing, filling and reporting. Keywords: Returning Medical Records.

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Influential Factors in The Law Enforcement Process of Sexual Violence Cases in Children in The City of Semarang

SOEPRA ◽

10.24167/shk.v6i2.2912 ◽

2020 ◽

Vol 6 (2) ◽

pp. 4

Author(s):

Liya Suwarni

Keyword(s):

Law Enforcement ◽

Sexual Violence ◽

Medical Record ◽

Child Protection ◽

Influential Factors ◽

Medical Record Data ◽

Violence Against Children ◽

Record Data ◽

The Law ◽

The City

Background. Cases of sexual violence increase every year, victims ranging from adolescents, children to toddlers. Based on data from the Indonesian Child Protection Commission, abuse and violence against children in Indonesia in 2013 were 23 cases, in 2014 there were 53 cases, in 2015 there were 133 cases, 2017 reached 1,337 cases, and as of July 2018 there were 424 cases. Purpose. Knowing the factors that influence the law enforcement process of sexy violence cases in Semarang City. Method This study uses descriptive analytical methods for cases of violence against children, based on medical record data in hospitals, documents in Mapolrestabes, the District Attorney's Office and the Semarang City Court for the period of January 2015 to December 2018. Results. Based on research results obtained 213 experimental cases section from medical record data in hospitals in the city of Semarang. Most cases of child abuse occurred in 2018 with 72 cases. Most victims are 12-14 years old age group, female. Most types of cases are cases of intercourse. The majority of violations are persons known as victims, perpetrators not working, and most of the places of occurrence are in the defendant's house. At the time of prosecution and trial, the number of cases was significantly reduced to only 8 cases. Factors related to this include lack of evidence, difficulty in obtaining information from victims, convoluted statements of coverage, lack of election, and obtaining diversion rates. Conclusion Cases of sexual violence have increased from year to year. The process of law enforcement on this problem still has many difficulties in each manufacturing process which is still difficult to overcome.

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