Analisis Survival pada Data Pasien Covid 19 di Kabupaten Jember

The confirmed number of positive Covid 19 cases in Indonesia until June 15th, 2020 was 38.227 people with 3.134 dead, case fatality rate 5,9%. Case fatality rate is the percentage of the number of dead people from all confirmed and reported positive cases . Particularly, in Jember Regency, the spreading of Covid 19 is still underway day by day with the increasing of number of patient so that appropriate preventive and treatment should be done precisely. The problem of the paper is the survival analysis of Covid 19 patient by using Kaplan Meier and Log Rank test method. The result of this paper, the result of the analysis using Kaplan Meier Curve method, patients with male sex have a chance of recovering faster compared with female patients and patients with age interval of 40-49 years have a chance of recovering faster than any other age intervals, meanwhile Log rank test did not provide significant results. So the Kaplan Meier Curve method is more appropriate to analyze Covid 19 patient data in Jember compared to the Log rank test

Analisis Faktor Risiko Kematian Ibu di Kabupaten Jember Menggunakan Cox Proportional Hazard

Maternal mortality is the death of a woman who is pregnant, giving birth and childbirth to the pregnancy or its handler. Maternal mortality in East Java Province still quite high with the highest number of deaths in 2021 is Jember Regency. The purpose of this paper is to determine risk factors that cause death in an effort to reduce the number of maternal deaths. Method used for the analysis of risk factors for maternal mortality is survival analysis with the Cox Proportional Hazard model. Survival analysis purpose to assess the relationship of predictor variables to survival time to determine maternal survival. Cox Proportional Hazard model is one of the models in survival analysis that is often used. Selection of the best model for Cox Proportional Hazard is carried out to determine the factors that have a significant effect. The best model is done by selecting the smallest AIC value backwards. Parameter significance test on the best model was carried out simultaneously and partially. Results obtained for maternal mortality factors in Jember Regency are anemia status and parity

PENENTUAN LOKASI STRATEGIS AUTOMATIC TELLER MACHINE PT. BANK SYARIAH INDONESIA TBK MENGGUNAKAN METODE DECISION TREE

ABSTRAK.  Lokasi Automatic Teller Machine Bank Syariah Indonesia Tbk (ATM BSI) dapat dianalisis dengan mengambil beberapa data sesuai dengan faktor pendukung yang akan digunakan. Faktor pendukung yang sesuai dianalisis dengan salah satu metode klasifikasi data mining yaitu Desicion Tree untuk menentukan lokasi strategis ATM BSI yang sudah didirikan. Desicion Tree adalah salah satu metode klasifikasi pada data mining berupa pohon keputusan untuk menyelesaikan permasalahan yang diperoleh dan menghasilkan aturan-aturan yang dapat dijadikan sebuah kesimpulan. Hasil perhitungan dengan metode Desicion Tree diperoleh akurasi sesuai dengan tabel confusion matrix untuk data training 100% dengan nilai AUC 1 dan data testing 100% dengan nilai AUC 1 dengan aturan pohon keputusan berdasarkan variabel jumlah penduduk dan jarak ATM ke SPBU. Hasil akurasi menunjukkan sangat baik dan akurat serta model Desicion Tree mampu memprediksi lokasi strategis dan tidak strategis berdasarkan data lokasi yang digunakan. Kata Kunci:  Lokasi strategis, Automatic Teller Machine (ATM), Metode Desicion Tree

Application of Black Scholes Method in Determining Agricultural Insurance Premium Based On Climate Index Using Historical Burn Analysis Method

Climate index insurance is an insurance that provides reimbursement for losses due to decreased harvest rates or crop failures caused by weather. The use of Historical Burn Analysis (HBA) method in determining climate index based on rainfall resulted in a concept of the agricultural insurance payment in Pasuruan Regency. The application of The Black Scholes method in determining agricultural insurance premiums is obtained when rainfall more than 17 mm the premium is Rp 221,234. If the rainfall are 13 mm ≥ RR < 17 mm, the nominal premium paid by farmers to the insurance party is Rp 147,489. Respondents in the study were farmers who owned rice fields. Instrument quality testing (questionnaire) using validity test and reliability test using the help of SPSS statistical software. It can be concluded that the questionnaire is valid and reliable. Based on the results of the questionnaire, farmers considered that the nominal agricultural insurance premiums are in accordance with farmers' income

FINANCIAL DISTRESS PREDICTION OF FINANCIAL SECTOR SERVICE COMPANIES ON INDONESIAN STOCK EXCHANGE USING COX PROPORTIONAL HAZARD

A company that cannot compete with its competitors is likely to experience financial difficulties or commonly referred to as financial distress. Financial distress is a stage of a decline in the company's financial condition or a situation of financial difficulty that occurred before the company went bankrupt. This study aims to determine the factors that can predict a company experiencing financial distress. The factors suspected in this study include leverage, profitability, company size, free cash flow and sales growth. The method used is the Cox Proportional Hazard model. The research data is data on financial sector service companies listed on the Indonesia Stock Exchange (IDX) for 5 years of observation, namely from 2016 to 2020. Based on the results of the analysis of financial distress predictions using the Cox Proportional Hazard model, it is found that the factors that have a significant effect on predicting companies experiencing financial distress are: financial distress, namely profitability and company size

Analysis of the Death Risk of Covid-19 Patients Using Extended Cox model

Globally, in 2021, there were 170,051,718 COVID-19 cases and 3,540,437 patients who died. The high mortality rate of patients infected with COVID-19 gives an idea to research the analysis of the factors that influence the death of Covid-19 patients. The data used in this study is data on Covid-19 patients obtained from the Mexican Government, with response variables namely time and status and predictor variables, namely patient laboratory results in the form of a history of illness that has been suffered by Covid-19 patients so that they adopt the extended model to evaluate the data. The data in this study are heterogeneous and large in number so that data clustering is carried out into 3 clusters, namely low emergency clusters, medium emergency clusters and high emergency clusters using K-means clustering. Because the study could not find the factors that influence the death of Covid-19 patients, two clusters were chosen, namely the medium emergency cluster and the high emergency cluster. So that the factors that influence the death of Covid-19 patients in the medium emergency cluster are sorted by the highest hazard ratio, namely pneumonia, old age, renal chronic, diabetes, Chronic Obstructive Pulmonary Disease (COPD), immune system, hypertension, cardiovascular, obesity, gender, and asthma. In the high emergency cluster, sorted by the highest hazard ratio is the immune system, renal chronic, cardiovascular, COPD, tobacco, hypertension, obesity, gender, and pneumonia

Perbandingan Metode Naïve Bayes Classifier dengan Metode Random Forest pada Prediksi Rating Review Drama Korea

Korean dramas have very many fans and are spread in various countries. This study aims to determine whether the korean drama is classified as Bagus, Tidak Bagus, or Cukup Bagus and compares two methods, namely the naïve bayes classifier method and the random forest method in predicting korean drama review ratings. This study shows that the naïve bayes classifier and random forest methods are capable of predicting korean drama review ratings. In the prediction review, the random forest method obtained an accuracy value of 89%, while the naïve bayes classifier method obtained an accuracy value of 86%. In rating predictions, the random forest method obtains an accuracy value of 41%, while the naïve bayes classifier method obtains an accuracy value of 40%. The conclusion of this study is that the random forest method is superior and accurate in predicting Korean drama review ratings

Comparison of Online and Offline Learning During The COVID-19 Pandemic using Naïve Bayes Method and C4.5

Learning is a process of interaction between educators and students who meet the elements of learning carried out in an educational environment, so that learning can develop student’s abilities, interests and talents optimally. In today's era learning is done online and inversely with offline. The purpose of this study is to analyze the comparison of percentages and classification results as well as the results of learning evaluations using the Naïve Bayes method and C4.5. This test is carried out with 4 variables and a comparison of the two methods. The results showed that the accuracy of Naïve Bayes was 74.07% and C4.5. of 77.77% so that the comparison results show that the level of accuracy of the C4.5 method is better than Naïve Bayes. The resulting importance variables are time and effectiveness as well as the results of the classification of learning decisions, namely the offline category as many as 16 data on the Naïve Bayes method and 19 data on the Decision Tree algorithm C4.5 method from 27 input testing data

Survival Analysis in Patients with Dengue Hemorrhagic Fever (DHF) Using Cox Proportional Hazard Regression

Indonesia is a tropical country that has two seasons: the rainy season and dry season. In the rainy season frequent flooding or puddles of water that could become mosquito breeding and the spread of various diseases, one of which is the dengue fever. Dengue Hemorrhagic Fever (DHF) is the cause of public health problems with a very rapid deployment and can lead to death within a short time. This causes dengue become one of the attractions to be investigated further. This study discusses the survival analysis and the factors that affect the healing rate of dengue patients using Cox proportional hazard regression based on data from the medical records of hospitalized dengue patients at the Jember Klinik Hospital. The results showed that the factors of age, gender, hemoglobin, trombonist, and hematocrit affect the healing rate of DHF patients

Cox Proportional Hazard Model for Analysis of Farmers Insurance Premium Payment Period

The sub-sector of agriculture plays a significant role in the national economic order. The crop failure rate is one of the unexpected risks caused by natural disasters, including drought, pest attacks, and floods. Agricultural insurance has been used as a pilot project in several areas, such as Gresik and Palembang Regencies. This pilot project has not been carried out in many places and cannot be implemented optimally in Jember. Farmer insurance is a transfer of risk due to farming business losses so that the sustainability of the farming business can be guaranteed. Survival analysis is a statistical method for analyzing data with observed response variables in terms of the time until an event occurs. One survival analysis is to determine the factors that cause an event with a response variable, namely using the Cox Proportional Hazard Model. The results of the significance testing obtained the variable that had a significant influence on the model, namely the growing season variable (X4). Then, a hazard ratio comparison was made for the category of cultivation season variables, and the category with the lowest hazard value was selected, followed by the second category, the months of May until August. (X42), This significantly influenced the policyholder’s time spent paying farmer’s insurance premiums