Claim Missing Document
Check
Articles

Found 8 Documents
Search

Pembelajaran Matematika Melalui Metode Bermain Erawaty, Nur; Thoha, Syamsuddin; B., Hasmawati; Kasbawati, Kasbawati; Aris, Naimah; Sirajang, Nasrah; Sahriman, Sitti; Anwar, Andi M.; Aidawayati, Aidawayati; Jusmawati, Jusmawati; Saputra, Edy
JATI EMAS (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat) Vol 3 No 2 (2019): JATI EMAS (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat)
Publisher : Dewan Pimpinan Daerah (DPD) Forum Dosen Indonesia JATIM

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (381.788 KB) | DOI: 10.36339/je.v3i2.201

Abstract

The achievement of Mathematics contestants from the City of Makassar is very concerning. In March 2018 elementary school mathematics competition was held. Of the 186 participants from Makassar, there were only 56 students who got scores above zero. Only about 30%. Other students get zero or less than zero (negative). There was a decrease in interest and achievement in Mathematics in elementary school students in Makassar. The solution offered was training for Mathematics Elementary School teachers by emphasizing learning method with playing. This is intended so that children have enjoyed Mathematics from the beginning so that in the future the interest in learning Mathematics will be even greater.
Peningkatan Kualitas Pembelajaran Matematika Bagi Guru SMA Melalui Media Google Classroom dan Geogebra Aris, Naimah; Erawaty, Nur; Massalesse, Jusmawati; Sirajang, Nasrah; Wahda, Wahda; Kasbawati, Kasbawati; Thamrin, Sri Astuti; Sahriman, Sitti; Ramadhan, Muh. Nur Bahri; Jaya, A. Kresna
JATI EMAS (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat) Vol 3 No 2 (2019): JATI EMAS (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat)
Publisher : Dewan Pimpinan Daerah (DPD) Forum Dosen Indonesia JATIM

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (347.483 KB) | DOI: 10.36339/je.v3i2.253

Abstract

The involvement of teachers in Bone Regency in using information and communication technology (ICT) to prepare teaching materials is very little or even never said, even though computer facilities and infrastructure are available in the computing lab. This activity aims to provide knowledge to Mathematics teachers about online learning Google Classroom and Geogebra. The use of Google Classroom will make learning more effective for teachers and students because learning is no longer limited by space and time, student can explore learning resources easily and utilize information technology properly. Likewise, Geogebra training is expected to overcome the difficulties of teachers in visualizing concept charts in mathematics dynamically. The target audience for community service is mathematics teachers who are members of the Mathematics MGMP in Bone Regency.
Implementasi Algoritma Centroid Linkage dan K-Medoids dalam Mengelompokkan Kabupaten/Kota di Sulawesi Selatan Berdasarkan Indikator Pendidikan Raja, Nur Alfianingsih; Tinungki, Georgina Maria; Sirajang, Nasrah
ESTIMASI: Journal of Statistics and Its Application Vol. 5, No. 1, Januari, 2024 : Estimasi
Publisher : Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/ejsa.v5i1.13605

Abstract

Cluster analysis is a multivariate analysis technique that aims to cluster the observational data or variables into clusters in such a way that each cluster is homogeneous according to the factors used for clustering. This study used the Centroid linkage algorithm that was useful for forming groups based on the distance between centroids and the K-Medoids algorithm that was based on the use of the most centered object (medoid) to group districts/cities and obtained comparison results based on the education indicator data in South Sulawesi. The implementation of the Centroid Linkage Algorithm and K-Medoids on the education indicator data in South Sulawesi in 2018, showed that the grouping of districts/cities in South Sulawesi produced 2 clusters with cluster 1 of 21 districts/cities, and cluster 2 of 3. To determine the best method, it was seen from the value of the Standard Deviation ratio in the cluster 〖(S〗_W) and Standard Deviation between Clusters 〖(S〗_B) showed the same standard deviation ratio (S) in the Centroid Linkage algorithm and K-Medoids that was equal to 104,967.
Analisis Regresi Data Panel Dengan Model Efek Umum, Model Efek Tetap Dan Model Efek Acak (Studi Kasus: Inflasi Dan Indeks Pembangunan Manusia) ada, Nuralyatussa’; Herdiani, Erna Tri; Sirajang, Nasrah
ESTIMASI: Journal of Statistics and Its Application Vol. 5, No. 2, Juli, 2024 : Estimasi
Publisher : Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/ejsa.v5i2.33279

Abstract

Panel data regression analysis is a method for modeling the influence of independent variables on dependent variables, on a combination of cross-section and time-series data. This research aims to estimate a panel data regression model with a generalized effects model using the least squares method, estimate a fixed effects model with the Least Square Dummy Variable and estimate a random effects model with Generalized Least Square on inflation and human development index data. The results obtained show that the factors that have a significant influence at the 5% level on the inflation rate in 2014-2019 are the dollar exchange rate with a coefficient of determination of the general effects model of 61.06%, then the HDI level in South Sulawesi in 2011-2017 is significantly influenced by factors such as average length of schooling and life expectancy with a coefficient of determination of the fixed effects model of 89.73%, and the HDI level in South Sulawesi in 2016-2019 is significantly influenced by the factors of life expectancy, per capita expenditure and poverty with a coefficient of determination of the random effects model amounting to 63.07%.
Estimasi Model Regresi Spline Kubik Tersegmen dengan Metode Penalized Least Square Islamiyati, Anna; Anisa, Anisa; Raupong, Raupong; Massalesse, Jusmawati; Sirajang, Nasrah; Sahriman, Sitti; Wahyuni, Alfiana
Al-Khwarizmi : Jurnal Pendidikan Matematika dan Ilmu Pengetahuan Alam Vol. 10 No. 2 (2022): Al-Khwarizmi : Jurnal Pendidikan Matematika dan Ilmu Pengetahuan Alam had Accr
Publisher : Prodi Pendidikan Matematika FTIK IAIN Palopo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24256/jpmipa.v10i2.3197

Abstract

Abstract:Nonparametric regression is used for data whose data pattern is non-parametric. One of the estimators that can be developed is a segmented cubic spline which is able to show several segmentation changes in the data. This article examines the estimation of segmented cubic spline nonparametric regression models using the Penalized Least Square estimation criteria. The method involves knot points and smoothing parameters simultaneously. In addition, the model is used to analyze data on BPJS claims based on patient age. The results show that the optimal model is at two-knot points, namely 26 and 52 with a smoothing parameter of 0.89. There are three segmentation changes from the cubic data, which consist of young people up to 26 years old, 26-52 years old, and 52 years and over. Abstrak:Regresi nonparametrik digunakan untuk data yang pola datanya bentuk non parametrik. Salah satu estimator yang dapat dikembangkan adalah spline kubik tersegmen yang mampu menunjukkan beberapa segmentasi perubahan pada data. Artikel ini mengkaji estimasi model regresi nonparametrik spline kubik tersegmen melalui kriteria estimasi menggunakan Penalized Least Square. Metode tersebut melibatkan titik knot dan parameter penghalus secara bersamaan. Selain itu, model digunakan untuk menganalisis data klaim BPJS berdasarkan usia pasien. Hasil menunjukkan bahwa model optimal pada dua titik knot yaitu 26 dan 52 dengan parameter penghalus sebesar 0,89. Terdapat tiga segmentasi perubahan data secara kubik, yaitu usia muda hingga 26 tahun, usia 26-52 tahun, dan usia 52 tahun ke atas. 
Estimasi Parameter Model Three-Factor Completely Randomized Design dengan Metode Robust MM Nurkamalia, Nurkamalia; Kalondeng, Anisa; Sirajang, Nasrah
ESTIMASI: Journal of Statistics and Its Application Vol. 6, No. 1, Januari, 2025 : Estimasi
Publisher : Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/ejsa.v6i1.18323

Abstract

When conducting experiments, it is often found that there are errors in the observed responses. It can cause data outliers to appear whose existence results in making conclusions inaccurate. Therefore, outliers need to be overcome by applying the robust regression method. The robust method used is the robust MM because it has a high level of efficiency and breakdown point. The Robust MM method is useful for obtaining parameter estimates in a three-factor Completely Randomized Design (CRD) which is applied to the data on average abdominal fat of broiler chickens experiencing outliers in four observations. The results showed that the presence of outliers caused no effect of differences in age of chicken and the interaction between age of chicken and feeding fermented kiambang on the average abdominal fat of broiler chickens. However, after the data was replaced with estimated data obtained from the Robust MM method to overcome outliers, it showed that there was an effect of age of chicken and the interaction between age of chicken and feeding of fermented kiambang on the average abdominal fat of broiler chickens.
Pemodelan Regresi Seemingly Unrelated Menggunakan Metode Maximum Likelihood pada Data Panel Hikmah, Nurul; Raupong, Raupong; Sirajang, Nasrah
ESTIMASI: Journal of Statistics and Its Application Vol. 6, No. 2, Juli, 2025 : Estimasi
Publisher : Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/ejsa.v6i2.34463

Abstract

This study aims to model and predict the Human Development Index (HDI) values in South Sulawesi Province for the period 2014–2022 using a multiple linear regression approach with the Maximum Likelihood Estimation (MLE) method. Multiple linear regression analysis often encounters multicollinearity issues among independent variables; therefore, Principal Component Analysis (PCA) is employed as a dimensionality reduction technique to eliminate correlations among explanatory variables. In addition, due to the potential correlation of residuals among equations in a multivariate model, the Seemingly Unrelated Regression (SUR) approach is used, which is also estimated using the MLE method. The data utilized in this study is panel data, which offers advantages in obtaining more comprehensive and accurate information regarding the relationships between the analyzed variables. The estimation results of the SUR model indicate that variables such as Life Expectancy (UHH), Mean Years of Schooling (RLS), Expected Years of Schooling (HLS), and Adjusted Per Capita Expenditure have a significant influence on HDI across all districts/cities in South Sulawesi. One of the estimated equations from the SUR model is y22t=81.44+0.670KU122 which illustrates the relationship between the principal component and HDI in a specific region.
THE USE OF PENALIZED WEIGHTED LEAST SQUARE TO OVERCOME CORRELATIONS BETWEEN TWO RESPONSES Islamiyati, Anna; Anisa, Anisa; Zakir, Muhammad; Sirajang, Nasrah; Sari, Ummi; Affan, Fajar; Usrah, Muhammad Jayzul
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 16 No 4 (2022): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (711.447 KB) | DOI: 10.30598/barekengvol16iss4pp1497-1504

Abstract

The non-parametric regression model can consider two correlated responses. However, for these conditions, we cannot use the usual estimation process because there are violations of assumptions. To solve this problem, we use a penalized weighted least square involving knots, smoothing parameters, and weighting in the estimation criteria simultaneously. The estimation process involves a weighted criteria matrix in the estimation criteria. Estimation results show that the estimated two-response non-parametric regression function with penalized spline is a linear estimation class in y response observation and depends on the knot point and smoothing parameter. Furthermore, the use of the model on toddler growth data shows some changes in the pattern of weight and height gain. The pattern segmentation that experienced a gradual increase was age 7-43 months for weight and age 6-54 months for height