(IJCSAM) International Journal of Computing Science and Applied Mathematics

Analyzing Factors Contributing to Gender Inequality in Indonesia using the Spatial Geographically Weighted Logistic Ordinal Regression Model

2025-06-02T06:37:48+07:00

Abstract—Gender inequality is a condition of discrimination caused by social systems and structures. The main objective of this research is to identify factors that influence gender inequality in each province in Indonesia and obtain classification accuracy values using Geographically Weighted Ordinal Logistic Regres- sion (GWOLR). The dataset used in this research consists of a response variable, namely the gender inequality index where the
index value is divided into ordinal categories (low, medium, and high) and four predictor variables from the dimensions of health,
education, human empowerment, social-culture, and work. The
results of this study show that the classification accuracy of the
GWOLR model is 85%. The mapping of provinces in Indonesia
based on influential variables forms three groups. The first group
(brown) is influenced by the percentage of women who give
birth with the assistance of health workers (X 1 ) and the female
Human Development Index (HDI) (X3 ). The second group (blue)
is influenced by the ratio of women’s Pure Participation Rate
(APM) (X 2 ) and the percentage of rape crimes against women
(X 4 ). The third group (red) is influenced by the percentage of
women who give birth with the assistance of health workers (X1),
the ratio of women’s Pure Participation Rate (APM) (X2 ), the
percentage of women’s Human Development Index (HDI) ratio
(X 3 ), and the percentage of women’s rape crimes (X4 ).

Combined Model of Markov Switching and Asymmetry of Generalized Seasonal Autoregressive Moving Average Conditional Heteroscedasticity for Early Detection of Financial Crisis in Hong Kong

2025-06-02T07:24:36+07:00

The financial crisis in Hong Kong occurred in 1997 and 2008. To prevent a crisis or reduce the impact of a crisis, action is needed through early detection of the crisis using export indicator. The combination of Markov Switching and Asymmetric Generalized Seasonal Autoregressive Moving Average Conditional Heteroscedasticity (MS-AGSARMACH) models explains the crisis well. The results show that the MSAGSARMACH(2,1,1) model can explain past and future crises well.

On Reverse Super Edge Bimagic Labeling of Gear Graph, Hibiscus Graph and Dove Tail Graph

2025-06-02T07:40:16+07:00

VAR Model Estimation And Application Of IRF And FEVD On Currency Exchange Rates, COVID-19 Cases, And WHO Twitter Information In Southeast Asia

2025-06-02T07:56:02+07:00

This paper examines the impact of the COVID-19 pandemic and World Health Organization (WHO) information dissemination through Twitter on the exchange rates of Southeast Asian countries. The study utilizes a VAR model for analysis, incorporating daily positive cases and the percentage of tweets with positive sentiment as proxies for the pandemic and WHO information, respectively. The VAR models are employed for forecasting and estimating impulse response functions (IRF) and forecast error variance decomposition (FEVD). The forecasting performance is evaluated using mean absolute error (MAE), root-mean-square error (RMSE), and R2 metrics, revealing that only Cambodia possesses a reliable forecasting model. The IRF analysis demonstrates varying effects of the pandemic and WHO information across different countries, while the FEVD results indicate distinct contributions of the pandemic and WHO information in each Southeast Asian country. Additionally, the FEVD analysis reveals that exchange rates are mostly influenced by their own past behavior. Overall, this study provides insights into the economic impact of the COVID-19 pandemic and WHO information on exchange rates in Southeast Asia.

Forecasting of Indonesian Crude Prices using ARIMA and Hybrid TSR-ARIMA

2025-06-02T08:23:02+07:00

Forecasting of Indonesian crude prices (ICP) is crucial for the government and policymakers. It helps them develop appropriate economic policies, budget allocations, and energy strategies. Forecasting methods that can be used are Time Series Regression (TSR) and Autoregressive Integrated Moving Average (ARIMA). This study aims to forecast ICP using ARIMA and hybrid TSR-ARIMA models. The data used in this study is the ICP per month, from January 2017 to November 2022. The data is divided into two groups, the data from January 2017 to December 2020 is used as training data, and the data from January 2021 to November 2022 is used as testing data. The MAPE values for the testing data of the TSR-ARIMA(2,1,0) and ARIMA(2,1,0) models are 8.24% and 17.37% respectively. Based on this, it can be concluded that the TSR-ARIMA(2,1,0) model is better than the ARIMA(2,1,0) model for forecasting ICP.

Marketing Refurbished Products with Carbon-Emission-Constraint Policy and Consumer Behavior: Offline vs. Online Channels

2025-06-03T01:28:40+07:00

Refurbished products, which are repaired or restored to a like-new condition, offer a more sustainable alternative to new products by extending their lifecycle. However, the marketing of refurbished products faces several chal-lenges, including consumer perception, trust, and the impact of carbonemission-constraint policies. This study aims to address these challenges and provide recommendations for effective marketing strategies. We explore the marketing of refurbished products within the context of carbon-emission-constraint policies, specifically comparing offline and online channels. We present two channel models, with the first model, referred to as Model O, fo-cusing on marketing refurbished products through the manufacturer’s own e-commerce channel. The second model, known as Model T, explores the al-ternative approach of outsourcing the marketing activity to a third-party en-tity. Carbon-emissionconstraint policies impose restrictions on businesses’ carbon footprint, affecting their marketing strategies. Businesses must navi-gate these policies while effectively promoting refurbished products to envi-ronmentally conscious consumers. By addressing the challenges faced in marketing refurbished products with carbon-emission-constraint policies, consumer behavior, and comparing offline and online channels, this thesis aims to provide valuable insights for businesses and policymakers to effec-tively promote sustainable consumption and contribute to a more environ-mentally conscious industry.

Truncated Gamma-Truncated Lomax Distribution in Modelling Data Claims

2025-06-03T01:42:41+07:00

One of the methods to analyze the risk of loss on insurance companies based on the historical data on claim payments is modelling the data into severity distribution. This research deals with severity distribution by connecting two distribution Truncated Gamma and Truncated Lomax in modelling claim payments. The Kolmogorov-Smirnov test is used to test the fit of model. The result shows that Truncated Gamma-Truncated Lomax distribution is the best model to analyze the risk of loss based on data claim payments. The AIC value of 1533,915 and the BIC value of 1550,132.

Implementation of Fuzzy-PID Controller on Quadcopter Movement

2025-06-03T01:50:24+07:00

A UAV is an unmanned aerial vehicle, one of which is a Quadcopter. A Quadcopter has a simple structure and small size. Therefore, high maneuverability allows the Quadcopter to take off, fly, and land in narrow areas. The speed of the four motor-driven propellers affects the quadcopter’s motion. The problem that often occurs in Quadcopters lies in the lifting force. Where the speed of the four motors must be the same so that the lift force can make the Quadcopter reach the desired height. The study aims to control the angular velocity and speed of the Quadcopter on the z-axis. The Quadcopter motion system model is a non-linear system because environmental disturbances give the system very high uncertainty. The system is given a control design in the form of Fuzzy-PID (Fuzzy Proportional Integral Derivative) with the desired set point or speed is 1. Simulation is carried out by comparing the system without disturbance and with disturbance to see how the speed of the Fuzzy-PID stabilizes the system. The simulation results show that even though the system is disturbed, the fuzzy-PID control can guide it toward the desired set point.

Design of Monkeypox Virus Spread Control in Humans Using Pontryagin Minimum Principle

2025-06-03T02:03:32+07:00

Monkeypox is a contagious disease caused by a virus. In Africa, monkeypox results in death in 1 out of 10 infected individuals. The Food and Drug Administration in the United States recommends vaccination as a preventive measure against monkeypox virus. If infected, the World Health Organization (WHO) advises quarantine to prevent further transmission to others. This research develops a mathematical model known as SIR (Susceptible-Infected-Recovered) for the spread of monkeypox virus, incorporating vaccination and quarantine as control measures. The SIR model utilized is based on an existing model and follows the conditions of monkeypox spread in Nigeria, represented as a system of nonlinear differential equations. Optimal control is determined using the Pontryagin Minimum Principle and simulated using the fourth-order forward-backward sweep Runge-Kutta method to assess the level of monkeypox infection before and after implementing control measures. Based on the simulation results, it is concluded that the application of control measures can reduce the population of infected monkeys by 70% and infected humans by 59%.

Optimal Control of the Spread of Dengue Fever by Controlling the Vectors Growth Affected by Climate Change and Treatment

2025-06-03T02:08:43+07:00

Dengue Hemorrhagic Fever (DHF) is an infectious disease caused by the dengue virus and is spread through the bite of an adult female Aedes aegypti mosquito, as a vector (disease-carrying animal), to humans. This disease is still a major health problem in tropical and subtropical regions. Indonesia is reported as the 2nd highest country among 30 other endemic countries. Warm temperatures during the rainy season are ideal conditions for mosquitoes to lay eggs optimally, increasing egg maturity, and shortening the virus incubation period. This has an impact on increasing the number of mosquitoes and the risk of disease transmission. In this study, control of DHF was carried out by controlling the growth of vectors in the egg and adult phases of mosquitoes, which were influenced by rainfall and air temperature, as well as the treatment of infected humans. Before carrying out the control, stability analysis around the equilibrium point is first conducted. Next, the numerical solution is obtained using the Runge-Kutta method of order 4 with the help of MATLAB software. The results of the analysis show that, based on the optimal control effect in the form of mosquito egg death (k1), adult mosquito death (k2), and human treatment (k3), in the cities of Pekanbaru and Solok, there is not much difference between the two. However, there is a slight difference in the increase in the human population that is susceptible to disease.

Electrodiogram Signal Classification by Using XGBoost in Different Discrete Wavelet Transform

2025-06-03T02:14:53+07:00

Electrocardiogram (ECG) is electrical signal from heart. ECG can use for Detection or tracking the hearth health. The one of method can use is machine learning. Machine learning is Algorithm which can learning from data and is used for classifying and predicting. Machine Learning can use for signal classification, in this case is for ECG classification. In signal processing, wavelet transform is common method for analyzing signal. Wavelet transform has many familly. The aim from this research is to find the best wavelet transform in the classification of Electrocardiogram (ECG) signals on XGBoost. The Discrete Wavelet Transform which is used for the research is daubechies, coiflets, symlets, biorthogonal, reverse biorthogonal, haar. Finally, the best wavelet transform in the classification is biorthogonal (3.1) with F1 score 1.0.

Development of Drowsiness Detection System for Drivers using Haar Cascade Classifier and Convolutional Neural Network

2025-06-03T02:29:27+07:00

The use of the Convolutional Neural Network (CNN) method to recognize an object in an image that is not too complex from the background and fore-ground shows very good results. However, in the case of images with various and very complex objects, the CNN method produces a large number of fea-ture maps, sometimes even unnecessary regions of interest (ROI) are includ-ed as material for model training which results in a lot of noise. This results in high computational costs and inconsistencies in the prediction results. Therefore, a pre-processing stage is needed, such as determining the area of interest (ROI) on the object of interest and the optimal architecture of CNN. This study applies the Haar Cascade Classifier method to determine the ROI of the object of interest in the image and CNN with the modified vgg-16 model architecture to detect drowsiness in drivers based on facial images. Test results based on the method used show optimal performance on exper-iments at various epochs with the highest accuracy was achieved 96.72%.

Analysis of Human Development Index in West Nusa Tenggara Province with Spatial Panel Model

2025-06-03T02:36:58+07:00

The purpose of this article is to examine the factors that influence the human development index (HDI) in West Nusa Tenggara using a spatial panel model. This research is crucial because it can analyze correlations between regions and is more efficient, informative, and effective in HDI modeling. The data structure is panel data, where observation units are the cities and regencies in West Nusa Tenggara Province for 2010 to 2022. A human development index serves as the dependent variable. The independent variables were per capita expenditure, average length of school, length of school expectations, and life expectancy. The Rook contiguity and the customized matrix (transportation routes) are used to examine geographical impacts. The results of the analysis indicate: 1) there are spatial linkages between districts and cities in West Nusa Tenggara; 2) the SAR Fixed Effect model is the most appropriate spatial model to model the human development index; 3) the human development index can be improved simultaneously by factors such as life expectancy, expected length of schooling, average length of schooling, and per capita expenditure; and 4) life expectancy is the main factor affecting the human development index.

Optimal control using pontryagin’s maximum principle: Tuberculosis spread case

2025-06-03T02:41:25+07:00

Tuberculosis is one of the deadliest infectious diseases in the world. In 2020, 9.9 million people were infected and 1.5 million died. East Java province ranks third with 43,268 tuberculosis cases. This research aims to determine the results of the tuberculosis disease model and simulation without and with the use of optimal control. The mathematical model SEIR is a model that can analyze the spread of the disease tuberculosis. In this research, a variable treatment compartment to the SEIR model. It used 4 antibiotics in the intensive phase and added Isoniazid and Rifampicin in the advanced phase as the optimal control parameters. Optimal control uses Pontriagin’s maximum principle as the derivative to modify the SEIR model and is described by a Runge-Kutta order 4 scheme. It shows both the useful parameters in the optimal control with a maximum value of 1 and plots where the effect of optimal control exists further constrained the people infected with Tuberculosis.

Simulation of a Mathematical Model of Proteins Interaction on GLUT4 Translocation

2025-06-03T02:47:19+07:00

Glucose is the energy source of cells. Glucose absorption into muscle cells is regulated by Insulin by involving the interaction of several proteins in a specific system. The system works for the translocation of GLUT4 to the cell membrane. GLUT4 is a transporter protein owned by every muscle cell, as an entry gate for glucose and an Insulin partner in maintaining homeostasis of blood glucose levels. After the Insulin activation occurs in the Insulin Receptor Substrate (IRS), it is followed by the activation of several proteins to regulate GLUT4 translocation, namely IRS, phosphatidylinositol 3-kinase (P13K), 3-phosphoinositide-dependent protein kinase-1 (PDK1/2) and serine/threonine-protein kinase (AKT). This study describes these processes in a mathematical model as a system of ordinary differential equations. The specific process modeled is the Insulin signal pathway that regulates GLUT4 translocation, which can be accessed on Kegg.jp. Moreover, string.db.org analysis results are used as a reference to prove the type of protein interaction. The formulated model is directed to coherently explain the flux changes of each protein involved in the system and stimulate easily. The simulation provides an overview of the protein dynamics in the system over time. Finally, the mathematical models and simulations will complement the basic understanding of the effect of glucose absorption on the translocation of GLUT4.

An Inventory Model for Deteriorated Item with Time- and Inventory-dependent Demand and Backorder

2025-06-03T02:53:08+07:00

The paper focuses on developing an inventory model for deteriorated item when demand is time- and inventorydependent. Deteriorated items can usually be found in items such as vegetables, fruit, milk, chemical product, pharmaceutical and it needs special attention in managing this kind of inventory. We model the inventory control for these items by a mathematical model involving time- and inventory-dependent demand and considering the backorder policy in handling shortages. The developed model aims to find the optimal time between replenishment and when inventory drops to zero, which minimizes the total inventory cost. The total inventory cost consists of the purchase cost, the order cost, the holding cost, and the shortage cost. Sensitivity analysis is performed to analyse the effect of changing the parameters’ values to the time between replenishment, when inventory drops to zero, the order quantity, and the total inventory cost. The finding shows that changing the parameters’ values of deterioration rate, demand, unit holding cost, unit holding cost and unit shortage cost will have an impact on the time between replenishment, time when inventory drops to zero, order quantity, and inventory cost.

Empowering New Capital Zones: East Kalimantan’s Economic District Outlooks Using Location Quotient and Cluster Analysis

2025-06-03T02:59:40+07:00

This research focuses on investigating the economy of the new capital buffer zone by identifying and clustering its leading sectors in GRDP (Gross Regional Domestic Product) of East Kalimantan. The identification of a region’s leading sector through LQ (Location Quotient) index has proven to be effective. In addition, k-means clustering and Self-Organizing Maps (SOM) are adopted to provide comprehensive insights. The results show that LQ index quickly identifies the main sectors in each district of East Kalimantan. In addition, the kmeans clustering has better performance than SOM based on the Silhouette coefficient. This meticulous analysis confirms the existence of two distinct clusters, one including eight members and the other consisting of only two. Anticipating future research endeavours, the exploration of various approaches for constructing clusters, encompassing both hierarchical and non-hierarchical approaches, provides the potential to enhance the performance of clusters. By investigating this structure, a more comprehensive comprehension of the economic framework of East Kalimantan can be achieved, as well as its potential role as a buffer for the capital region.