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All Journal Eksakta : Berkala Ilmiah Bidang MIPA Pelita Eksakta Journal of Mathematics UNP
Fadhilah Fitri
Universitas Negeri Padang
Agriculture, Biological Sciences & Forestry Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Energy Engineering Environmental Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Other

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Application Of Mathematical Literacy In Mathematics Learning For Elementary School Fadhilah Fitri; Dina Fitria; Fridgo Tasman; Defri Ahmad; Suherman Suherman
Pelita Eksakta Vol 2 No 2 (2019): Pelita Eksakta Vol. 2 No. 2
Publisher : Fakultas MIPA Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/pelitaeksakta/vol2-iss2/75

Abstract

Mathematical literacy requires individuals to solve a problem and also apply mathematics in everyday problems, which results in the ability to interpret solutions to those problems. In PISA it is known that Indonesia's mathematics literacy score is among the lowest, as well as in Guguk District Lima Puluh Kota Regency. One way to overcome this is to start introducing literacy to students early on. The introduction of literacy must be instilled in students since they are still in elementary school. Based on this, a training program and workshop was held regarding the application of mathematical literacy in mathematics learning in elementary schools in Guguak District with elementary school mathematics teacher partners who are members of the KKG SD Gugus III Kecamatan Guguak Kabupaten Lima Puluh Kota.
Infant Mortality Case: An Application of Negative Binomial Regression in order to Overcome Overdispersion in Poisson Regression Fadhilah Fitri; Fitri Mudia Sari; Nurul Fiskia Gamayanti; Iut Tri Utami
EKSAKTA: Berkala Ilmiah Bidang MIPA Vol. 22 No. 3 (2021): Eksakta : Berkala Ilmiah Bidang MIPA (E-ISSN : 2549-7464)
Publisher : Faculty of Mathematics and Natural Sciences (FMIPA), Universitas Negeri Padang, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (898.543 KB) | DOI: 10.24036/eksakta/vol22-iss3/272

Abstract

Infant mortality is an indicator to determine the degree of public health. Infant mortality is death that occurs in the period from birth to before the age of one. The high rate of infant mortality indicates that the quality of public health services is not optimal. The number of infant deaths is an example of count data that follows a Poisson distribution, so it can be analyzed using Poisson Regression. The assumption that must be met when using this method is the equidispersion or variance of the response variable is equal to mean. However, this condition rarely occurs because usually the counted data has a greater variance than the mean or it is called overdispersion. One way to solve this problem is to use the Negative Binomial Regression method. The data used in this study is the case of infant mortality in the city of Padang. First, we model the data using Poisson Regression, then we check the assumption, if there is overdispersion, we handle it by modeling the data with Negative Binomial Regression. The results showed that the equidispersion assumption could not be met so that the data was modeled with Negative Binomial Regression.
Peramalan Kurs Rupiah Terhadap Dolar Amerika Menggunakan Jaringan Saraf Tiruan Rifani Rizki Amelia; Fadhilah Fitri
Journal of Mathematics UNP Vol 7, No 3 (2022): Journal Of Mathematics UNP
Publisher : UNIVERSITAS NEGERI PADANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (395.723 KB) | DOI: 10.24036/unpjomath.v7i3.12564

Abstract

The Indonesian rupiah (IDR) exchange rate is used to gauge Indonesia's economic stability. Maintaining the IDR exchange rate's stability is critical since it has a direct impact on Indonesia's national monetary situation, particularly during the Covid-19 pandemic. Forecasting is one way to assess government policy in terms of lowering the exchange rate. The goal of this study is to use the backpropagation artificial neural network model to model and predict the IDR exchange rate. This study uses daily data on the US Dollar (USD) to Indonesian Rupiah (IDR) exchange rate from March 2020 to December 2021. The best BPNN model is BP (2,5,1) with 2 neurons in the input layer, 5 neurons in the hidden layer, and 1 neuron in the output layer. The accuracy of prediction of this model is very good with an RMSE value is 33,66 and MAPE value is 0,1796%.
Co-Authors Defri Ahmad Dina Fitria Fitri Mudia Sari Fridgo Tasman Iut Triutami Nurul Fiskia Gamayanti Rifani Rizki Amelia Suherman Suherman