scholarly journals Implementasi Iterative Dichotomiser 3 (ID3) Untuk Penentuan Kelayakan Pemberian Kredit Pada PT.BPR Ploso Saranaartha Jombang

2021 ◽  
Vol 7 (1) ◽  
pp. 60-69
Author(s):  
Siti Nurul Afiyah ◽  
Wahyu Dini Aula Nabila
Keyword(s):  
Training Dataset ◽  
Root Node ◽  
Record Data

Pada PT. BPR Ploso Saranaartha Jombang terdapat beberapa permasalahan yang kerap muncul mengenai pemberian kredit pada debitur. Saat ini bank tersebut memberikan kredit kepada nasabahnya masih dengan cara seleksi debitur, belum ada prosedur secara sistematis dalam menentukan apakah suatu nasabah tersebut layak diberikan kredit atau tidak. Hal inilah yang mengakibatkan banyaknya kredit macet yang dapat merugikan pihak bank.. Algoritma Iterative Dichotomiser 3 (ID3) merupakan salah satu algoritma yang dapat digunakan untuk menyelesaikan kasus ini. Dalam penyelesaiiannya nanti ID3 akan melakukan proses preprocessing data terlebih dahulu yang bertujuan untuk membuang data-data yang tidak penting guna mendapatkan data yang benar-benar dibutuhkan. Setelah itu ID3 akan membentuk sebuah pohon keputusan berdasarkan rules yang dihasilkan. Setiap root node dalam sebuah pohon keputusan terbentuk berdasarkan nilai gain terbesar dari tiap-tiap input atribut. Dalam perhitungan algoritma ini diperlukan sebuah dataset yang cukup untuk digunakan proses training. Dataset yang digunakan untuk proses training ini berjumlah 300 record data yang terdiri dari 272 data dengan kolektibilitas lancar dan 28 data dengan kolektibilitas macet. Terdapat pula data yang akan digunakan untuk proses testing berjumlah 20 record data nasabah baru yang terdiri dari 8 data dengan kolektibilitas macet dan 12 data dengan kolektibilitas lancar. Dalam uji coba yang telah dilakukan terhadap dataset menghasilkan 10 rules. Setelah dilakukan proses testing atau pengujian terhadap data testing dihasilkan output dengan tingkat keakurasian 88,51%. Artinya dari 300 record data yang telah ditraining dapat meng-cover 19 data dari 20 record data testing.

scholarly journals Prospective Real-World Performance Evaluation of a Machine Learning Algorithm to Predict 30-Day Readmissions in Patients with Heart Failure Using Electronic Medical Record Data (Preprint)

2018 ◽  
Author(s):  
Sujay S Kakarmath ◽  
Neda Derakhshani ◽  
Sara B. Golas ◽  
Jennifer Felsted ◽  
Takuma Shibahara ◽  
...  
Keyword(s):  
Machine Learning ◽  
Heart Failure ◽  
Real World ◽  
Predictive Performance ◽  
Training Dataset ◽  
Brier Score ◽  
Medical Record Data ◽  
Electronic Medical Record Data ◽  
Patients With Heart Failure ◽  
Record Data

BACKGROUND Heart failure (HF) patients have a high readmission rate with approximately 20% of patients being readmitted within 30-days after discharge. Hospital interventions to reduce HF readmissions are resource- and effort-intensive. Widespread availability of electronic medical record data has spurred interest in using machine learning-based techniques for risk stratification of heart failure patients. The predictive performance of machine learning-based predictive models is often evaluated solely using the Area Under the Receiver Operating Characteristic (AUROC) curve. However, the AUROC is independent of prevalence therefore predictive models with the same AUROC can have differential clinical utility. Furthermore, the AUROC does not provide any insight about the presence of overfitting or decay in predictive performance of a model over time, both of which can affect its real-world performance. OBJECTIVE Our primary objective is to assess real-world performance of a 30-day readmission risk prediction model for HF patients, which had an AUROC of 0.71 in the training dataset. METHODS Predictions for risk of 30-day readmissions in HF patients in the Partners Healthcare System were prospectively obtained from the model. We assessed the positive (PPV) and negative predictive value (NPV), in addition to sensitivity, specificity, accuracy, model calibration and Brier score. RESULTS Four hundred twenty index admissions that were not part of the training dataset were included in this prospective evaluation. Readmission rate was 24% (101 30-day readmissions). The AUROC of the predictive model was 0.57. At a discrimination threshold of 0.2 for flagging high-risk index admissions, the sensitivity and specificity of the model were 53.46% and 63.32%, respectively. The PPV and NPV were 31.57% and 81.12%, respectively. The Brier score was 0.19. CONCLUSIONS Our analysis offers important insights about the real-world performance of this predictive model. The NPV suggests that the model’s prediction about patients at low risk for readmission are reliable. This insight can be useful in optimizing resource allocation for patients with heart failure.

EDPS of Clinical Case Record and Scientific Document in the Industry Post-Marketing Surveillance of Drugs

1983 ◽  
Vol 22 (03) ◽  
pp. 135-148 ◽  
Author(s):  
T. Kitaguchi ◽  
T. Nojiri ◽  
S. Suzuki ◽  
T. Fukita ◽  
T. Kawana
Keyword(s):  
Data Base ◽  
Clinical Case ◽  
Drug Information ◽  
Case Record ◽  
Post Marketing Surveillance ◽  
Japanese Character ◽  
Record Data ◽  
Post Marketing ◽  
On Line ◽  
Line Drug

In order to meet the multifarious needs for drug information and to cope with the post-marketing surveillance of drugs adequately, an on-line drug information network, which is composed of two data bases, clinical case record data base and literature data base, has been developed. Primary considerations in designing these systems were input of clean data, accurate input, insuring that no ADRs are overlooked, accumulation of the latest data, saving manpower required for processing, and processing large quantities of data. This system is also designed to input and to output in Japanese character.

PREDIKSI KEDALAMAN BATUBARA MENGGUNAKAN TRIANGGULASI DAN KRIGING

KURVATEK ◽  
2018 ◽  
Vol 2 (1) ◽  
pp. 85-89
Author(s):  
Agung Dwi Sutrisno
Keyword(s):  
Record Data

Salah satu fokus dari Masterplan Percepatan dan Perluasan Pembangunan Ekonomi Indonesia (MP3EI) adalah pengembangan energi batubara. Sebelum batubara dieksploitasi dilakukan eksolorasi terlebih dahulu. Kegiatan eksplorasi meliputi kegiatan pemboran. Dalam pemboran detil penghematan dapat dilakukan apabila prediksi kedalaman batubara dapat diperkirakan dengan baik. Tujuan penelitian ini adalah untuk menguji keakuratan antara metode trianggulasi dengan metode kriging dalam memprediksi kedalaman lapisan batubara pada suatu lokasi menggunakan software surfer. Pendekatan penelitian ini menggunakan metode komparatif. Data lapisan batubara meliputi koordinat dan elevasi serta elevasi dan ketebalan batubara diplot bersamaan dengan peta topografi. Peta kontur batubara dibuat menggunakan metode trianggulasi dan kriging. Keduanya dikomparasikan. Analisis dilakukan dengan cara crosscheck dari kedua metode di atas dengan record data aktual. Nilai dengan selisih tekecil berarti tingkat akurasinya lebih baik. Hasilnya, metode kriging mempunyai selisih prediksi rata-rata 22,2 m, sedangkan metode trianggulasi mempunyai selisih prediksi 2,4 m. Dengan demikian, metode trianggulasi prediksinya lebih baik dibandingkan dengan metode kriging.

Non-Blind Image Deconvolution Based on “Ringing” Removal Using Convolutional Neural Network

2020 ◽  
Vol 2020 (10) ◽  
pp. 181-1-181-7
Author(s):  
Takahiro Kudo ◽  
Takanori Fujisawa ◽  
Takuro Yamaguchi ◽  
Masaaki Ikehara
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Network Architecture ◽  
Large Scale ◽  
Blind Deconvolution ◽  
Training Dataset ◽  
Image Deconvolution ◽  
Classic Problem ◽  
Key Points ◽  
Blind Image

Image deconvolution has been an important issue recently. It has two kinds of approaches: non-blind and blind. Non-blind deconvolution is a classic problem of image deblurring, which assumes that the PSF is known and does not change universally in space. Recently, Convolutional Neural Network (CNN) has been used for non-blind deconvolution. Though CNNs can deal with complex changes for unknown images, some CNN-based conventional methods can only handle small PSFs and does not consider the use of large PSFs in the real world. In this paper we propose a non-blind deconvolution framework based on a CNN that can remove large scale ringing in a deblurred image. Our method has three key points. The first is that our network architecture is able to preserve both large and small features in the image. The second is that the training dataset is created to preserve the details. The third is that we extend the images to minimize the effects of large ringing on the image borders. In our experiments, we used three kinds of large PSFs and were able to observe high-precision results from our method both quantitatively and qualitatively.

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

SOEPRA ◽  
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.

The relationship betweenparityand the incident of perinealruptures on women’s physiological maternity

2019 ◽  
Vol 1 (2) ◽  
Author(s):  
Evi Rosita ◽  
Siti Nurnaningrum
Keyword(s):  
Public Health ◽  
Health Center ◽  
P Value ◽  
Chi Square ◽  
Cross Sectional ◽  
Midwifery Care ◽  
Public Health Center ◽  
Record Data ◽  
The Relationship ◽  
Very High

There are about 2.8 million incident of perineal rupture in maternal physiological labor. In 2050,it is estimated that the incidence of perineal rupture can be 6.3 million if it is not accompanied by a good midwifery care. In 2016, in Trawas, there was (89%) perineal rupture in primiparas and (57%) perineal rupture in multiparas. Perineal rupture incidences due to parity were still very high. This study aims to analyze the relationship between parity and the incidence of perineal rupture . It is quantitative studyusing a cross sectional approach, by using analysis of physiological maternity women  medical record data from January to April 2017 of 130 peoplein Trawas Public Health Center, Mojokerto Regency.The dataanalysis used was Chi - Square , indicated by p value = 0,000 with ɑ = 0,05. It means that the value of p <ɑ, so H1 is accepted. It can be concluded that there is a relationship between parity and the incidence of perineal rupture on physiological maternity women in Trawas Public Health Center,Mojokerto Regency. Midwives can apply collaboration with patients and their families to have physical and psychologicalpreparation with an alternative of hypnobirthing methods.

Moralitas dalam Novel Negeri di Ujung Tanduk Karya Tere Liye

2018 ◽  
Vol 1 (1) ◽  
pp. 154-173
Author(s):  
Muhtadin Muhtadin ◽  
Sugi Murniasih
Keyword(s):  
Research Method ◽  
Self Esteem ◽  
The Novel ◽  
Human Beings ◽  
Human Relationships ◽  
Mutual Help ◽  
Analysis Techniques ◽  
Self Confidence ◽  
Record Data ◽  
Morality Literature

The objective of this research was to describes the morality contained in the novel Affairs at the Negeri di Ujung Tanduk the works Tere Liye. The research method used content analysis. The data in this research is a sentence containing the moral values ​​contained by the novel of the State at Ujung Tanduk Karya Tere Liye. Technique of collecting data using documentation technique and record. Data analysis techniques with steps: data reduction, data tabulation and coding, interpretation, classification, and conclusion. The result of the research shows that morality in Tere Liye Negeri di Ujung Tanduk novel is: first, human relationships with other human beings in the form of self existence, self esteem, self confidence, fear, death, longing, resentment, loneliness, maintaining the sanctity of greed, developing courage, honesty, hard work, patient, resilient, cheerful, steadfast, open, visionary, independent, brave, courageous, optimistic, envy, hypocritical, reflective, responsible, principle, confident, disciplined , and voracious. Second, human relationships with other humans or social and nature in the form of cooperation, acquaintance, hypocrisy, caring, hypocrisy, caring, friendship, smile, mutual help, and betrayal. Third human relationships in the form of God's menthidising and avoiding shirk, piety and pleading with prayers, prayers performed by human beings, as an awareness that everything in this universe belongs to God. Keywords: morality, literature, novel

Automated chronic disease surveillance and visualization using electronic health record data

2011 ◽  
Vol 4 (0) ◽  
Author(s):  
Michael Klompas ◽  
Chaim Kirby ◽  
Jason McVetta ◽  
Paul Oppedisano ◽  
John Brownstein ◽  
...  
Keyword(s):  
Chronic Disease ◽  
Electronic Health Record ◽  
Disease Surveillance ◽  
Health Record ◽  
Electronic Health Record Data ◽  
Record Data ◽  
Electronic Health
Sign in / Sign up

Export Citation Format

Share Document