cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Aang Nuryaman
Contact Email
aang.nuryaman@fmipa.unila.ac.id
Phone
+6285324460093
Journal Mail Official
siger.matematika@fmipa.unila.ac.id
Editorial Address
Jurusan Matematika FMIPA Universitas Lampung Jl. Soemantri Brojonegoro No 1 Gedong Meneng Rajabasa Bandar Lampung
Location
Kota bandar lampung,
Lampung
INDONESIA
Jurnal Siger Matematika
Published by Universitas Lampung
ISSN : 27215849     EISSN : 27216853     DOI : https://doi.org/10.23960/JSM
Core Subject : Education,
Mathematics
Jurnal Siger Matematika is a broad scope journal that publishes original research articles as well as review articles on all aspects of both pure and applied mathematics. publised by Departement Mathematics, Faculty of Mathematics and Natural Sciences, University of Lampung. This journal covers all topics of Mathematical sciences which includes: Analysis Geometry Algebra Combinatorics Operation Research Statistics Applied Mathematics Computational Mathematics
Arjuna Subject : Matematika - Matematika (Lain-Lain)
Articles 5 Documents
 1 
Search results for , issue "Vol 2, No 1 (2021): Jurnal Siger Matematika" : 5 Documents clear
Perbandingan Metode Bootstrap, Jacknife Jiang Dan Area Specific Jacknife Pada Pendugaan Mean Square Error Model Beta-Bernoulli Yesi Santika; Widiarti Widiarti; Fitriani Fitriani; Mustofa Usman
Jurnal Siger Matematika Vol 2, No 1 (2021): Jurnal Siger Matematika
Publisher : FMIPA Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (487.04 KB) | DOI: 10.23960/jsm.v2i1.2756

Abstract

Small area estimation is defined as a statistical technique for estimating the parameters of a subpopulation with a small sample size. One method of estimating small area parameters is the Empirical Bayes (EB) method.  The accuracy of the Empirical Bayes (EB) estimator can be measured by evaluating the Mean Squared Error (MSE). In this study, 3 methods to determine MSE in the EB estimator of the Beta-Bernoulli model will be compared, namely the Bootstrap, Jackknife Jiang and Area-specific Jackknife methods.  The study is carried out theoretically and empirically through simulation with R-studio software version 1.2.5033. The simulation results in a number of areas and pairs of prior distribution parameter values, namely Beta, show the effect of sample size and parameter value pairs on the Mean Square Error (MSE) value. The larger the number of areas and the smaller the initial ????, the smaller the MSE value.  The area-specific Jackknife method produces the smallest MSE in the number of areas 100 and the Beta parameter value 0.1.
Peramalan Data Runtun Waktu menggunakan Model Hybrid Time Series Regression – Autoregressive Integrated Moving Average Melisa Arumsari; Andrea Tri Rian Dani
Jurnal Siger Matematika Vol 2, No 1 (2021): Jurnal Siger Matematika
Publisher : FMIPA Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (498.378 KB) | DOI: 10.23960/jsm.v2i1.2736

Abstract

Peramalan merupakan metode yang digunakan untuk memperkirakan atau memprediksi suatu nilai di masa yang akan datang dengan menggunakan data dari masa lampau. Semakin berkembangnya metode dalam analisis data runtun waktu, dikembangkan metode yang bersifat hybrid dimana dilakukan kombinasi beberapa model dengan tujuan untuk menghasilkan peramalan yang lebih akurat. Tujuan dari penelitian  ini adalah untuk mengetahui apakah metode hybrid TSR-ARIMA memiliki tingkat akurasi lebih tinggi dibandingkan dengan metode TSR secara individu sehingga diperoleh hasil peramalan yang lebih akurat. Data pada penelitian ini adalah data bulanan jumlah penumpang maskapai penerbangan Amerika Serikat periode Januari Tahun 1949 hingga Desember Tahun 1960. Berdasarkan hasil analisis, metode hybrid TSR-ARIMA menghasilkan MAPE sebesar 3,061% dan metode TSR menghasilkan MAPE sebesar 7,902%.
PERBAIKAN CITRA MENGGUNAKAN METODE CONTRAST STRETCHING Supiyanto Supiyanto; Titik Suparwati
Jurnal Siger Matematika Vol 2, No 1 (2021): Jurnal Siger Matematika
Publisher : FMIPA Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (512.95 KB) | DOI: 10.23960/jsm.v2i1.2743

Abstract

Contrasting images that are not good because they are too bright or too dark cannot provide good information. Therefore, a method is needed to improve the image quality, so that the information in the image can be conveyed properly. Contrast stretching is one of the methods for improving image quality. With this method is expected to produce a new image that is better. The purpose of this research is to apply contrast stretching method to an application or software that can be used to improve image quality. Data used in this study in the form of grayscale image data and RGB imagery (true color), with the format . BMP or .JPG, while the application development uses the Matlab programming language.The results of the study, contrast stretching method can be used to repair image that affects bad or poor image quality such as too bright / dark image, less sharp image, blurry, and so on. Contrast stretching method can also be used to improve image enhancement by leveling the histogram that was collected in an area, so that the information contained in the image is more clearly visible compared to the original image.
Penerapan Model Geographically Dan Temporally Weighted Regression Pada Kecelakaan Lalu Lintas Naomi Nessyana Debataraja; Dadan Kusnandar; Riani Mahalalita; Nurfitri Imro’ah
Jurnal Siger Matematika Vol 2, No 1 (2021): Jurnal Siger Matematika
Publisher : FMIPA Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (741.391 KB) | DOI: 10.23960/jsm.v2i1.2751

Abstract

Geographically and temporally weighted regression (GTWR) is a model that is used to deal with instability in data both spatially and temporally and to produce local parameters. In this paper, The GTWR model is used to analyze the factors that are thought to significantly influence the number of traffic accidents in Mempawah Regency.  The data used in this study came from 8 districts with the variables used were the number of traffic accidents, the number of population (gender ratio, length of damaged road conditions, and percentage of adolescence. The parameter estimation of the GTWR model was obtained using the weighted least square (WLS) method. The optimal bandwidth selection uses the Cross-Validation (CV) method and the weighting used is the Fixed bisquare function. The results of the analysis show that using the GTWR model, it was found that only the population size variable significantly affected the number of traffic accidents in all locations in Mempawah Regency from 2015 to 2018. The GTWR model was known to be better than the multiple regression model because it produced smaller AIC and RSS values and a larger R-square value.
Analisis Hubungan Antara Kelembaban Relatif Dengan Beberapa Variabel Iklim Dengan Pendekatan Korelasi Pearson di Samudera Hindia Miftahuddin Miftahuddin; Ananda Pratama Sitanggang; Ichsan Setiawan
Jurnal Siger Matematika Vol 2, No 1 (2021): Jurnal Siger Matematika
Publisher : FMIPA Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (458.567 KB) | DOI: 10.23960/jsm.v2i1.2753

Abstract

Relative humidity is a parameter that can affect global climate change, including in Indonesia region. Aceh province is located on the island of Sumatra and is located around the Malacca Strait in the northern and eastern parts of Aceh, while it is located around the Indian Ocean for the western and southern parts of Aceh. Thus, due to its geographic position Aceh Province has a considerable impact on climate change. Changes in relative humidity will cause changes in climate variables through natural cycles. There are several climate variables including air temperature, rainfall, sea surface temperature, wind speed, solar radiation, and dynamic altitude. In this study, the correlation method is used which aims to see the closeness of the relationship between each climate variable from in the Indian Ocean. Regarding climate variables having quantitative data, the Pearson Correlation method is used in this study. The results showed that the relationship between the variables air temperature and sea surface temperature had the highest relationship with a positive correlation value of 0.769. The lowest relationship is the variable rainfall and wind speed with a negative weak correlation value of -0.01. In correlation research, it shows that a gap in the dataset reduces the value of the positive correlation magnitude. The correlation value with gap tends to have a lower correlation coefficient value than the gapless correlation value in the dataset for positive correlation. Meanwhile, negative correlation applies the opposite. The existence of gaps can affect the distribution pattern, shape and slope of the data distribution so that it affects the correlation magnitude and direction (positive or negative).

Page 1 of 1 | Total Record : 5

 1 

Filter by Year

2021 2021


Reset
Filter By Issues
All Issue Vol 4, No 2 (2023): Jurnal Siger Matematika Vol 4, No 1 (2023): Jurnal Siger Matematika Vol 3, No 1 (2022): Volume 3 No 1 Vol 3, No 2 (2022): Jurnal Siger Matematika Vol 2, No 2 (2021): Jurnal Siger Matematika Vol 2, No 1 (2021): Jurnal Siger Matematika Vol 1, No 2 (2020) Vol 1, No 1 (2020): Jurnal Siger Matematika