Evaluation of Active Affiliates to the SIS Multidimensional Analysis in R Shiny

This article presents a study that uses multiple linear regression analysis to examine the factors influencing the number of people affiliated with different insurance plans within the Comprehensive Health Insurance (SIS) system in Peru.The study highlights the importance of multiple linear regression analysis in understanding the factors that affect SIS Comprehensive Health Insurance affiliates. It also showcases the value of utilizing interactive tools like RShiny to enhance data analysis, providing a dynamic and participatory experience for researchers and users interested in the subject.To facilitate the analysis and visualization of SIS-related data, the researchers developed an interactive application using RShiny. This tool allows for the easy loading, visualization, and analysis of data in a user-friendly and practical manner. By providing an interactive platform, users can effectively explore and understand the factors that impact SIS affiliates.The results of the analysis indicate that the selected variables have a significant positive influence on the total number of affiliates. This suggests that the specific insurance plan examined in this study has a favorable effect on the enrollment of individuals in SIS. Additionally, the data shows a linear trend, supporting the use of a linear regression model to describe this relationship. Active affiliates,Comprehensive health insurance SIS,Data Visualization,Multiple Linear Regression Analysis,RShin

Algoritmos de aprendizaje automático no supervisado para la extracción de palabras clave en trabajos de investigación de pregrado

La información que administra la Universidad Nacional del Altiplano de Puno, en los últimos años se ha visto incrementada sobre todo trabajos de investigación realizados por estudiantes y egresados de pregrado, para los que se usan técnicas empíricas para la selección de palabras clave, existiendo a la fecha métodos técnicos que ayuden en este proceso, en tanto el uso de tecnologías de información y comunicación han tomado relevancia e importancia en la administración y seguimiento de trabajos de investigación como la Plataforma de Investigación Integrada a la Labor Académica con Responsabilidad (PILAR), donde registra información de los proyectos de investigación como (Título, Resumen, Palabras Clave), en sus diferentes modalidades. En el presente trabajo de investigación se ha analizado 7430 registros de proyectos de investigación, a los cuales se realizaron predicciones con cada uno de los 09 modelos de aprendizaje automático no supervisado implementados. Los resultados nos muestran que el modelo TF-IDF, es el más eficiente en tiempo y en precisión de extracción de palabras clave, obteniendo un 72 % de precisión y en un tiempo de extracción entre [0.4786 ,SD 0.0501], por cada documento procesado por este modelo.Tesi

CATASTROAGRI -- Interactive data analysis and visualization application with a future projection for catastrophic agricultural insurance

CATASTROAGRI is an application developed to load, analyze and interactively visualize relevant data on catastrophic agricultural insurance. It also focuses on the analysis of an ARIMA (0,1,1) (0,1,1) model to identify and estimate patterns in the agricultural data of the Puno Region, it presents a decreasing trend because there is a significant relationship between successive values of the time series, We can also state that it is not stationary because the mean and variance do not remain constant over time and the series has periods, and it is observed that the cases are decreasing and increasing over the years, especially the amount to indemnify due to the behavior of the climate in the highlands. The results of the analysis show that agricultural insurance plays an important role in protecting farmers against losses caused by adverse climatic events. The importance of concentrating resources and indemnities on the most affected crops and in the provinces with the highest agricultural production is emphasized. The results of the users' evaluation showed a high level of satisfaction, as well as ease of use.Comment: In the process of sending magazine

Peru Mining: Analysis and Forecast of Mining Production in Peru Using Time Series and Data Science Techniques

Peruvian mining plays a crucial role in the country's economy, being one of the main producers and exporters of minerals worldwide. In this project, an application was developed in RStudio that utilizes statistical analysis and time series modeling techniques to understand and forecast mineral extraction in different departments of Peru. The application includes an interactive map that allows users to explore Peruvian geography and obtain detailed statistics by clicking on each department. Additionally, bar charts, pie charts, and frequency polygons were implemented to visualize and analyze the data. Using the ARIMA model, predictions were made on the future extraction of minerals, enabling informed decision-making in planning and resource management within the mining sector. The application provides an interactive and accessible tool to explore the Peruvian mining industry, comprehend trends, and make accurate forecasts. These predictions for 2027 in total annual production are as follows: Copper = 2,694,957 MT, Gold = 72,817.47 kg Fine, Zinc = 1,369,649 MT, Silver = 3,083,036 MT, Lead = 255,443 MT, Iron = 15,776,609 MT, Tin = 29,542 MT, Molybdenum = 35,044.66 MT, and Cadmium = 724 MT. These predictions, based on historical data, provide valuable information for strategic decision-making and contribute to the sustainable development of the mining industry in Peru

Multiple Correspondence and Proportional Analysis of Vaccination Rate Among Healthcare Personnel of MINSA

DataProAnalytica is a powerful application for analyzing vaccination data in health care professionals. Through visualizations and multiple correspondence analysis, it uncovers meaningful relationships between variables and categories. The results provide valuable information for improving vaccination strategies. While there are limitations, the potential of DataProAnalytica to improve accuracy and functionality makes it a promising tool for future research and decision making in any other research topic

DataXploreFines: Generalized Data for Informed Decision, Making, An Interactive Shiny Application for Data Analysis and Visualization

This article presents DataXploreFines, an innovative Shiny application that revolutionizes data exploration, analysis, and visualization. The application offers functionalities for data loading, management, summarization, basic graphs, advanced analysis, and contact. Users can upload their datasets in popular formats like CSV or Excel, explore the data structure, perform manipulations, and obtain statistical summaries. DataXploreFines provides a wide range of interactive visualizations, including histograms, scatter plots, bar charts, and line graphs, enabling users to identify patterns and trends. Additionally, the application offers statistical tools such as time series analysis using ARIMA and SARIMA models, forecasting, and Ljung-Box statistic. Its user-friendly interface empowers individuals from various domains, including beginners in statistics, to make informed decisions

Prediction of breast cancer with 98% accuracy

Abstract Cancer is a tumor that affects people worldwide, with a higher incidence in females but not excluding males. It ranks among the top five deadliest types of cancer, particularly prevalent in less developed countries with deficient healthcare programs. Finding the best algorithm for effective breast cancer prediction with minimal error is crucial. In this scientific article, we employed the SMOTE method in conjunction with the R package Shiny to enhance the algorithms and improve prediction accuracy. We classified the tumor types as benign and malignant (B/M). Various algorithms were analyzed using a Kaggle dataset, and our study identified the superior algorithm as logistic regression. We evaluated algorithm performance using confusion matrices to visualize results and the ROC Curve to obtain a comprehensive measure of performance. Additionally, we calculated precision by dividing the number of correct predictions by the total predictions Keywords Breast cancer, Smote, Benign, Malignant

Autoconfianza y su relación con el rendimiento, procedencia, logros y edad en jugadoras de voleibol peruanas en categoría de formación

The objective of the present research was to determine the relation between the self-confidence and the performance, place of origin, achievements and age of Peruvian volleyball players players in training category.  This is a non-experimental, correlational, cross-sectional study. A total of 86 volleyball players, between 12 and 16 years old (age M=15.59-TD=0.74) were studied.  The sports confidence inventory was applied to these volleyball players (reproducibility of .992). The results show that there is a statistically significant positive correlation between lack of confidence and performance (r = .310; p < .01), lack of confidence and provenance (r = .280; p < .01); confidence and age (r = .244; p < .05); overconfidence and achievements (r = .235; p < .05); level of self-confidence and age (r = .236; p < .05). On the other hand, there is a negative correlation, also statistically significant, between confidence and provenance (r = -.342; p < .01); overconfidence and yield (r = -.399; p < .01); self-confidence level and provenance (r = -.387; p < .01). It is concluded that self-confidence is to a large extent associated with sports performance, the geographical region from which they come and the age of the volleyball players, except with the sports achievements obtained in training category.El objetivo de este estudio fue determinar la relación de la autoconfianza con el rendimiento, procedencia, logros y edad en voleibolistas peruanas en categoría de formación. El estudio es de naturaleza no experimental, transeccional correlacional. Se estudió a 86 voleibolistas, de edades entre 12 y 16 años (M=15.59-DT=0.74), a quienes se les aplicó el inventario de confianza deportiva (reproductividad de .992). Los resultados demuestran que existe una correlación positiva, estadísticamente significativa, entre falta de confianza y rendimiento (r = .310; p < .01), falta de confianza y procedencia (r = .280; p < .01); confianza y edad (r = .244; p < .05); exceso de confianza y logros (r = .235; p < .05); nivel de autoconfianza y edad (r = .236; p < .05). Por otro, que existe una correlación negativa, también estadísticamente significativa, entre confianza y procedencia (r = -.342; p < .01); exceso de confianza y rendimiento (r = -.399; p < .01); nivel de autoconfianza y procedencia (r = -.387; p < .01). Se concluye que la autoconfianza en gran medida se asocia con el rendimiento deportivo, región geográfica de donde provienen y edad que presentan las voleibolistas, excepto con los logros deportivos obtenidos en categoría de formación. &nbsp

Validación de un instrumento de medición de actividad física y propuesta de percentiles para su valoración en jóvenes universitarios

Introduction: The aim of this study was: a) to validate the questionnaire that measures FA by means of confirmatory analysis; b) to analyze reliability by means of stability measures; and c) develop percentiles by age and sex range.Material and methods: A cross-sectional descriptive study was carried out in 1,937 in university students (1,064 men and 873 women) from the city of Puno, Peru. The weight and height were measured and the Body Mass Index (BMI) was calculated by sex . An 11-question questionnaire was used that measures Physical Activity. It was validated by Factorial Confirmatory Analysis (AFC) and reliability was verified by test re-test. Percentiles were generated by age and sex range for AF patterns by the LMS method.Results: For the AFC, saturations were observed between 0.41 and 0.96, Eigen values greater than 1.0, and the variance explanation was 63.9% (Varimax and Kaiser-Meier-Olkin, KMO = 0.872 Sphericity of X2 = 4999.5, p <0.0000). Reliability by re-test showed a Technical Measurement Error (TEM) of 2.48 to 3.68% and an intra-class correlation coefficient (ICC) between 0.65 for men and 0.654 for women and for both sexes CCI = 0.92.Conclusion: The questionnaire of 11 questions that measures FA is valid and reliable for university students in a high altitude region of Peru. In addition, the proposed percentiles serve to identify and classify AF levels according to age and sex range.Introducción: El objetivo del presente trabajo fue: a) validar el cuestionario que mide actividad física mediante análisis confirmatorio; b) analizar la fiabilidad por medio de medidas de estabilidad; y c) desarrollar percentiles por rango de edad y sexo.Material y métodos: Se efectuó un estudio de tipo descriptivo de corte transversal en 1.937 jóvenes universitarios (1.064 hombres y 873 mujeres) de la ciudad de Puno, Perú. Se midió el peso y estatura y se calculó el índice de Masa Corporal (IMC) por sexo. Se aplicó un cuestionario de 11 preguntas que mide actividad física. Se validó por Análisis Factorial Confirmatorio (AFC) y se verificó la confiabilidad por test re-test. Se generó percentiles por rango de edad y sexo para los patrones de actividad física por el método LMS.Resultados: Para el AFC se observó saturaciones entre 0,41 a 0,96, valores propios superiores a 1,0, el porcentaje de explicación de la varianza fue de 63,9% (Varimax y Kaiser-Meier-Olkin, KMO= 0,872. Esfericidad de X2= 4999,5, p<0,0000). La fiabilidad por test re-test mostró un Error Técnico de Medida (ETM) de 2,48 a 3,68% y un coeficiente de correlación intra-clase (CCI) entre 0,65 para hombres y 0,654 para mujeres y para ambos sexos CCI= 0,92.Conclusión: El cuestionario de 11 preguntas que mide actividad física es válido y confiable para jóvenes universitarios de una región de elevada altitud del Perú. Además, los percentiles propuestos sirven para identificar y clasificar los niveles de actividad física según rango de edad y sexo

PENSAMIENTO CRÍTICO EN LA INVESTIGACIÓN CIENTÍFICA Y ACADÉMICA COLECCIÓN CIENTÍFICA EDUCACIÓN, EMPRESA Y SOCIEDAD

PENSAMIENTO CRÍTICO EN LA INVESTIGACIÓN CIENTÍFICA Y ACADÉMICA COLECCIÓN CIENTÍFICA EDUCACIÓN, EMPRESA Y SOCIEDAD Primera Edición 2023 Vol. 21 Editorial EIDEC Sello Editorial EIDEC (978-958-53018) NIT 900583173-1 ISBN: 978-628-95884-1-5 Formato: Digital PDF (Portable Document Format) DOI: https://doi.org/10.34893/e1150-3660-8721-s Publicación: Colombia Fecha Publicación: 13/09/2023 Coordinación Editorial Escuela Internacional de Negocios y Desarrollo Empresarial de Colombia – EIDEC Centro de Investigación Científica, Empresarial y Tecnológica de Colombia – CEINCET Red de Investigación en Educación, Empresa y Sociedad – REDIEES Revisión y pares evaluadores Centro de Investigación Científica, Empresarial y Tecnológica de Colombia – CEINCET Red de Investigación en Educación, Empresa y Sociedad – REDIEE