Claim Missing Document
Check
Articles

Found 4 Documents
Search
Journal : International Journal of Applied Mathematics, Sciences, and Technology for National Defense

Mathematical modeling of basal body temperature influence on menstrual cycle, length of sleep, and stress levels as detection of fertile period (ovulation) in women Rahayu, Tiara; Hasudungan, Ardiman; Afiya, Rahmatul; Farradila M, Vinka; Rachmawati, Ro'fah Nur
International Journal of Applied Mathematics, Sciences, and Technology for National Defense Vol 1, No 3 (2023): International Journal of Applied Mathematics, Sciences, and Technology for Natio
Publisher : FOUNDAE

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58524/app.sci.def.v1i3.234

Abstract

Basal body temperature is the temperature when the body reaches the resting phase or does not perform any activity. Basal body temperature is influenced by factors such as the quality of a person's length of sleep, stress, and menstrual cycle patterns. The benefit of checking and monitoring basal body temperature for a woman is to determine when a woman starts to enter the ovulation period, making it easier for couples who want a target pregnancy. The measurement method was carried out in the morning right after waking up using a thermometer flanked in the armpit area by applying three repetitions of measurements within a period of two months with the number of sample participants of 10 cadet students of military biology study program with an age range of 19-21 years. This type of research is carried out observationally and analytically using longitudinal data. The analysis used in this study was by conducting a statistical mathematical model trial by analyzing the p-value. The results showed that in the paired test there was a significant influence of the relationship of basal body temperature on the menstrual cycle at the time before menstruation and when menstruation. The researcher's suggestion is to conduct further research with larger participants of samples and the presence of sample variations in observations because not all biologists do significant research with the statistical method.
Modeling fuel consumption in various external vehicle conditions for military vehicle using mixed linear models Saputra, Muhammad Nuraliffudin; Arif, Samsul; Wijanarko, Fakhri; Panse, Vishal R; Lubis, Agnes Sprakezia; Rachmawati, Ro'fah Nur
International Journal of Applied Mathematics, Sciences, and Technology for National Defense Vol 1, No 2 (2023): International Journal of Applied Mathematics, Sciences, and Technology for Natio
Publisher : FOUNDAE

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58524/app.sci.def.v1i2.183

Abstract

With the crisis in fuel consumption, it is necessary to save fuel consumption by selecting fuel that is quite efficient. The aim of the research is to examine the fuel consumption patterns of vehicles in an area that experiences various weathers so as to determine the level of efficiency of fuel use. both from the factor of fuel type, distance, speed, temperature, to the weather. testing was carried out using the linear model technique, the Linear Mixed effect model, and the Anova mathematical model. The results of the analysis if the different types of fuel have a very large significant effect in influencing the fuel consumption of a vehicle. With all the approaches analyzed from the linear mix model, analysis of variance and linear mix random effect model, the results show that other independent variables such as average speed, distance traveled and ambient temperature do not have much effect on fuel consumption. Based on modeling results that has been done, it can be identified if fuel consumption is strongly influenced by the type of fuel used by the vehicle. Meanwhile, other variables such as vehicle mileage, average speed, and ambient temperature at the time of data collection did not show any significant effect on fuel consumption.
Mixed linear model for investigating food security during the covid-19 pandemic: Panel data for rice consumption in indonesia Aisyah, Mutiara Aghnyn; Putri, Devita Amalia; Chandra, Yoshua; Syazali, Muhamad; Machmud, Amir; Rachmawati, Ro'fah Nur
International Journal of Applied Mathematics, Sciences, and Technology for National Defense Vol 1, No 1 (2023): International Journal of Applied Mathematics, Sciences, and Technology for Natio
Publisher : FOUNDAE

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58524/app.sci.def.v1i1.174

Abstract

The Covid-19 pandemic has affected human life behavior, starting from health, the economy to living habits, one of them is the rice consumption. This study aims to find out whether the Covid-19 pandemic can affect people's rice consumption, and what are the factors that can affect people's rice consumption before and during the pandemic. The independent factors studied in this study were harvested area, productivity, rice production, crime rate, and the ratio of household gas use, with rice consumption as the dependent variable. The data used is panel data for 2019 and 2020, from 34 provinces in Indonesia, which is one of the five countries with the highest rice consumption in the world. By using mixed linear models, the research results show that in general Covid-19 pandemic has not had a significant effect on rice consumption in Indonesia. Other facts also show that social factors, namely the crime rate during a pandemic, did not have a significant effect on rice consumption.However, this is different from economic factors such as productivity and harvested area which have a significant positive effect on rice consumption in Indonesia.
Modeling suspected malaria cases in Papua province with second order Besag-York-Mollie 2 spatial regression Azzahra, Kirana; Rachmawati, Ro'fah Nur; Syazali, Muhamad
International Journal of Applied Mathematics, Sciences, and Technology for National Defense Vol 2, No 2 (2024): International Journal of Applied Mathematics, Sciences, and Technology for Natio
Publisher : FOUNDAE

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58524/app.sci.def.v2i2.433

Abstract

The number of malaria cases in Indonesia has increased in recent years. The highest malaria cases in Indonesia are in the eastern region, namely Papua Province, where in 2021 there were 86,022 cases. This study aims to model suspected malaria cases in Papua using the Integrated Nested Laplace Approximation (INLA) approach. Modelling is carried out with two different orders to see the difference in determining the best results. The results showed that second-order spatial modelling provides better results than first order modelling because the RMSE value is smaller than the first-order model. Based on these results, it is concluded that the INLA approach with second-order spatial modelling is effective for analysing and predicting suspected malaria cases in Papua. Therefore, these results can be used as a reference in developing malaria control strategies in the region.