Pengaruh Inflasi Dan Produk Domestik Bruto (PDB) Terhadap Tingkat Suku Bunga Riil Dengan Menggunakan Pendekatan Taylor Rule

Penelitian ini berfokus kepada kebijakan moneter khususnya analisis kebijakan moneter dengan menggunakan pendekatan "Taylor Rule" Penelitian ini bertujuan untuk mengetahui pengaruh Inflasi Dan Produk Domestik Bruto (PDB) Terhadap Tingkat Suku Bunga Riil Dengan Menggunakan Pendekatan Taylor Rule. Hasil penelitian ini menunjukkan bahwa bahwa Variabel Bebas (Inflasi dan Output) berpengaruh negative slope terhadap Variabel Terikat (Tingkat Suku Bunga Riil), hal ini berarti setiap kenaikan nominal pada variable Inflasi dan Output maka akan menyebabkan tingkat suku bunga riil akan turun. Hasil penelitian ini menjelaskan bahwa Variable bebas mampu untuk menjelaskan variable terikat sebesar 0,240 atau 24%, dan terdapat 76% variabel lain yang dapat juga menjelaskan variabel terikat tetapi tidak dimasukkan kedalam uji model pada penelitian ini. Untuk uji hipotesis, variable bebas tidak berpengaruh secara signifikan terhadap variable terikat

Evaluasi dan Perancangan Model Bisnis pada PT X di Surabaya dengan Pendekatan Business Model Canvas

Banyaknya pembangunan gedung-gedung baru, jasa substitusi dan lesunya perekonomian menyebabkan bisnis persewaan kantor di Surabaya lesu. Penelitian ini dilakukan dengan menggunakan metode kualitatif dengan menggunakan metode case study melalui wawancara terhadap pihak internal Perusahaan x dan pihak eksternal. Teknik pengambilan sampel yaitu purposive sampling. Metode analisis yang digunakan adalah triangulasi sumber Aspek yang menjadi perhatian yaitu Sembilan elemen business model canvas, selanjutnya dilakukan analisis SWOT pada masing-masing elemen tersebut serta membahas blue ocean strategy untuk Perusahaan XHasil dari penelitian ini ialah susunan business model canvas baru yang dapat dikembangkan oleh Perusahaan

Customer Segmentation Menggunakan Fuzzy C-means Clustering Pada E-commerce Henz Collection

Online shop "Henz Collection" is an onlineshop that sells products such as clothes, bags, and shoes. The main problem faced by the online shop are not yet have a website that specialized in selling the products that it sells itself and difficult to know which customers have loyalty to this shop online. Ecommerce application is built using Fuzzy C-Means. Fuzzy C-Means clustering is a technique in which the existence of each data point is determined by the degree of membership (partition). Value centroid k-means clustering taken from random numbers, so that when the centroid determination will be modified so that the clustering results have not changed, so that the customer data can be grouped consistently and data on the cluster have been no changes during the period that would diklaster not changed. The purpose of the application design e-commerce based website is to look at the criteria for customers who are entitled to a rebate / discount. Based on test results and data modules can be concluded that the application is running as expected. Discounting seen from the experimental formation of clusters that provide the best global value silhouette. Cluster in the period 2014 to have the degree of similarity of 60% of customer data and in the period 2015 to have the degree of similarity of 80% of customer data contained in these clusters with the data of the owner onlineshop discount

Characteristics and outcomes of an international cohort of 600 000 hospitalized patients with COVID-19

Background: We describe demographic features, treatments and clinical outcomes in the International Severe Acute Respiratory and emerging Infection Consortium (ISARIC) COVID-19 cohort, one of the world’s largest international, standardized data sets concerning hospitalized patients. Methods: The data set analysed includes COVID-19 patients hospitalized between January 2020 and January 2022 in 52 countries. We investigated how symptoms on admission, co-morbidities, risk factors and treatments varied by age, sex and other characteristics. We used Cox regression models to investigate associations between demographics, symptoms, co-morbidities and other factors with risk of death, admission to an intensive care unit (ICU) and invasive mechanical ventilation (IMV). Results: Data were available for 689 572 patients with laboratory-confirmed (91.1%) or clinically diagnosed (8.9%) SARS-CoV-2 infection from 52 countries. Age [adjusted hazard ratio per 10 years 1.49 (95% CI 1.48, 1.49)] and male sex [1.23 (1.21, 1.24)] were associated with a higher risk of death. Rates of admission to an ICU and use of IMV increased with age up to age 60 years then dropped. Symptoms, co-morbidities and treatments varied by age and had varied associations with clinical outcomes. The case-fatality ratio varied by country partly due to differences in the clinical characteristics of recruited patients and was on average 21.5%. Conclusions: Age was the strongest determinant of risk of death, with a ~30-fold difference between the oldest and youngest groups; each of the co-morbidities included was associated with up to an almost 2-fold increase in risk. Smoking and obesity were also associated with a higher risk of death. The size of our international database and the standardized data collection method make this study a comprehensive international description of COVID-19 clinical features. Our findings may inform strategies that involve prioritization of patients hospitalized with COVID-19 who have a higher risk of death