An efficient numerical method for estimating the average free boundary velocity in an inhomogeneous Hele-Shaw problem

We develop a numerical method to estimate the average speed of the free boundary in a Hele-Shaw problem with periodic coefficients in both space and time. We test the accuracy of the method and present a few examples. We show numerical evidence of flat parts (facets) on the free boundary in the homogenization limit.Comment: 18 page

Enhancing Accuracy on Chronic-Kidney Disease Detection Using Machine Learning with Technique of Resampling and Missing Value Treatment

Chronic kidney disease is one of the deadliest diseases in the world. It is important to identify chronic kidney disease at an early stage, so that treatment and prevention can be carried out early. This study used linear interpolation method to treat the missing values, resampling using SMOTE method, and several feature selection methods, such as Pearson’s correlation coefficient and Principal component analysis. For the classification methods, Support Vector Machine and Logistic Regression were used to build prediction models for chronic kidney disease based on dataset on UCI Machine Learning. To measure the performance of the model, several test scenarios were tested out so it can be compared to the previous research on the detection of chronic kidney disease, which is used as a benchmark for this study. The best result from the experiment is obtained from the scenario of resampling using SMOTE and feature selection using Principal Component Analysis with averaged accuracy, precision, and f1-score respectively are 98,8%, 100%, dan 98,77%

Land-Use Planning for Farming Area in West Java to Divide Allocation of Vegetables Commodity Using Genetic Algorithm Approach

This research has created a model to determine the optimum allocation of land-use planning for farming in West Java by considering the two main components, i.e., production and cost. The method is essential in farming, especially in the COVID-19 situation, as it determines clearly which procedure needs to be involved for land-use farming optimization. The problem of land allocation lies in finding the optimum solution from the multi-objective functions. In this study, the method used to cope with the land-use design problem was the Genetic Algorithm (GA) and its expansion called Nondominated Sorting Genetic Algorithm (NSGA). The research results indicated that the best total fitness in GA and NSGA is relatively the same. It was shown that both NSGA and GA could make a planning scheme optimal for the farming commodities in West Java. Based on the maximum optimum value from the best fitness value of NSGA, around 37.35% of the farmland in West Java, it is the best fit for the big red chili commodity. The city where the land used for extensive red chili farming is found to have the maximum optimum value is Garut, with 98.73% of its total farm area.This research has created a model to determine the optimum allocation of land-use planning for farming in West Java by considering the two main components, i.e., production and cost. The method is essential in farming, especially in the COVID-19 situation, as it determines clearly which procedure needs to be involved for land-use farming optimization. The problem of land allocation lies in finding the optimum solution from the multi-objective functions. In this study, the method used to cope with the land-use design problem was the Genetic Algorithm (GA) and its expansion called Nondominated Sorting Genetic Algorithm (NSGA). The research results indicated that the best total fitness in GA and NSGA is relatively the same. It was shown that both NSGA and GA could make a planning scheme optimal for the farming commodities in West Java. Based on the maximum optimum value from the best fitness value of NSGA, around 37.35% of the farmland in West Java, it is the best fit for the big red chili commodity. The city where the land used for extensive red chili farming is found to have the maximum optimum value is Garut, with 98.73% of its total farm area

ANALISIS DETERMINAN TERLAMBATNYA DETEKSI DINI PENDERITA KUSTA DI KECAMATAN JENGGAWAH JEMBER 2008 (Determinan Analysis Late Early Detections Of Leprosy's Patient At Jenggawah) Jember 2008)

ABSTRACT Leprosy is infectious disease which causes disability that can be prevented by early detection and also regularity treatment and care. Proportion of disability grade 2 at Jenggawah subdistric is 38,3% at 2008. The purpose of this research is to analyze influence factor to late of early detection. This was an analytic observational research in case-control approach with the comparison by 1:2. Case sample was taken from the 14 newly patients of leprosy with disability of grade 2. Control sample was taken from the 28 newly patients of leprosy with disability of grade 0 and 1. Dependent variable was late of early detection. Independent variables were health services factors while role of Puskesmas, circumstance geography of Puskesmas, and distant of Puskesmas, health worker factor, patient factors while education and knowledge of leprosy, and stigma of leprosy at community. The sample was taken by using a simple random sampling technique with lottery. The statistical analysis used a simple logistic regression with =0,05. The research showed that the risk factors of the late of early detection were role of Puskesmas (CI 95%= 2,109-39,847 and OR=9,167), health worker factor (CI 95%=1,117-18,132 and OR=4,500), knowledge of leprosy (CI 95%=2,003-58,224 and OR=10,800), and stigma of leprosy at community (CI 95%=1,599-27,243 and OR=6,600). Circumstance geography of Puskesmas, distant of Puskesmas, and education were not the influence factors. According to the results of this research, known that require to increase health workerâs performance by providing health workerâs motivation, incentive, and improvement the ability with countinously training and increase counselling about leprosy according to the socio cultural of the community with entangle religion figure and use Madura language. Keyword : leprosy, disability of leprosy, late early detectio

An efficient numerical method for estimating the average free boundary velocity in an inhomogeneous Hele-Shaw problem

We develop a numerical method to estimate the average speed of the free boundaryin a Hele-Shaw problem with periodic coefficients in both space and time. We test the accuracyof the method and present a few examples. We show numerical evidence of flat parts (facets)on the free boundary in the homogenization limit

A Numerical Scheme for the Hele-Shaw Problem in Oscillating Media

13301甲第4815号博士（理学）金沢大学博士論文本文Full 以下に掲載予定：The Sciences Report of Kanazawa University 62 2018. The Institute of Science and Engineering, Kanazawa University. 共著者：Irma Palup

A Numerical Scheme for the Hele-Shaw Problem in Oscillating Media

13301甲第4815号博士（理学）金沢大学博士論文要旨Abstract 以下に掲載予定：The Sciences Report of Kanazawa University 62 2018. The Institute of Science and Engineering, Kanazawa University. 共著者：Irma Palup

Prediction of the peak Covid-19 pandemic in Indonesia using SIR model

Penelitian ini menyajikan penggunaan model Susceptible, Infected, and Removed (SIR) untuk memprediksi kondisi penularan Covid-19 di Indonesia. Data resmi pemerintah yang terdiri dari kasus positif, meninggal, dan sembuh digunakan sebagai data aktual untuk menginterpolasi model, melalui metode pencocokan data dengan minimum mean squared error (MSE). Salah satu metode pencarian Quasi-Newton yaitu algoritme Broyden, Fletcher, Goldfarb, and Shanno (BFGS) digunakan untuk menentukan nilai optimal koefisien interaksi pada model dengan nilai MSE minimum. Berdasarkan data per 18 Juli 2020, model memprediksi bahwa puncak penambahan kasus positif infeksi akan terjadi pada bulan Oktober dengan jumlah mendekati 14% persen total populasi dan galat MSE 18,42, relatif terhadap periode data aktual. Tingkat penyebaran diestimasi dengan nilai 2,035 dimana lebih kecil 29 % dibandingkan dengan tingkat penyebaran relatif dari data aktual.This research implements the Susceptible, Infected, and Removed (SIR) model to predict the Covid-19 outbreak in Indonesia. The government official data, consisting of infected, dead, and recovered, are used as actual data to interpolate the model through matching data with minimum mean squared error (MSE). The study uses one of the Quasi-Newton search methods, the Broyden, Fletcher, Goldfarb, and Shanno (BFGS) algorithm, to determine the interaction coefficient's optimal value in the model with the minimum MSE value. Based on data as of July 18, 2020, it predicts that the peak of the infected number will be in October 2020 with around 14 % of the total population infected, and the MSE of 18.42 is relative to the period of the actual data. Meanwhile, the basic reproduction rate is calculated to be 2.035 from the model, where it is underestimated by about 29 % compared to the relative basic reproduction rate from the provided actual data

The impact of financial inclusion on national development and national financial system stability

This study seeks to understand the relationship between financial inclusion, national development, and the stability of the national financial system in Indonesia. The data collected in this study is a secondary data that includes the data of the number of commercial bank accounts, number of commercial banking service offices, number of general credits, average income, population welfare, goods and services production, and number of credits of 34 provinces throughout Indonesia, from 2015 until 2019. A dynamic statistic panel Model of the Generalized approach of Moments (GMM) is used for data analysis. The results of this research showed that financial inclusion has a significant negative influence on national development, but it can increase the national financial stability system. This is possible due to the diversity of demography, economic condition, and geographical condition in each province of Indonesia