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Management of Facilities and Infrastructure of Physical Education in State Junior High School Jajang, Jajang; Purwanto, Sugeng; Nanda, Fitri Agung; Novriansyah, Novriansyah
Journal of Education Reseach and Evaluation Vol 5 No 2 (2021): May
Publisher : LPPM Undiksha

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (256.49 KB) | DOI: 10.23887/jere.v5i2.33683

Abstract

Management of infrastructure and facilities is important in physical education, considering that infrastructure is a medium to support the success of learning. This study aims to determine how the management of physical education facilities and infrastructure in State Junior High Schools. This research is a type of qualitative research using a case study research design. Data obtained through interviews, observation, and documentation. The research data were obtained from six sources consisting of the principal, physical education teachers, and facilities and infrastructure staff. Data analysis used Miles and Huberman analysis. The results of research on the availability and management of facilities and infrastructure revealed that there were several physical education facilities and infrastructure that were feasible but had their availability. The removal of physical education facilities and infrastructure activities that have not been carried out properly has resulted in many damaged facilities and infrastructure piled up in the warehouse. The inventory process has been carried out well. This can be seen from the process of registering goods or facilities and infrastructure which are recorded alphabetically by the names of items that have been spent, the inventory process is carried out routinely and regularly. The process of maintaining physical education facilities and infrastructure is carried out by teachers and students.
Comparing of Car-Bym, Generalized Poisson, and Negative Binomial Models on Tuberculosis Data in Banyumas Districs: Pembandingan Model Car-Bym, Generalized Poisson, dan Binomial Negatif pada Data Tuberkolosis di Kabupaten Banyumas Jajang Jajang; Budi Pratikno; Mashuri Mashuri
Indonesian Journal of Statistics and Applications Vol 5 No 1 (2021)
Publisher : Departemen Statistika, IPB University dengan Forum Perguruan Tinggi Statistika (FORSTAT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/ijsa.v5i1p130-140

Abstract

In 2019 the number of people with TB (Tuberculosis) in Banyumas, Central Java, is high (1,910 people have been detected with TB). The number of people infected Tuberculosis (TB) in Banyumas is the count data and it is also the area data. In modeling, the parameter estimation and characteristic of the data need to be considered. Here, we studied comparing Generalized Poisson (GP), negative binomial (NB), and Poisson and CAR.BYM model for TB cases in Banyumas. Here, we use two methods for parameter estimation, maximum likelihood estimation (MLE) and Bayes. The MLE is used for GP and NB models, whereas Bayes is used for Poisson and CAR-BYM. The results showed that Poisson model detected overdispersion where deviance value is 67.38 for 22 degrees of freedom. Therefore, ratio of deviance to degrees of freedom is 3.06 (>1). This indicates that there was overdispersion. The folowing GP, NB, Poisson-Bayes and CAR-BYM are used to modeling TB data in Banyumas and we compare their RMSE. With refer to RMES criteria, we found that CAR-BYM is the best model for modeling TB in Banyumas because its RMSE is smallest.
PENCARIAN RUTE OPTIMAL TRAVELING SALESMAN PROBLEM DENGAN ALGORITMA ANT COLONY OPTIMIZATION (ACO) Nuraliya, Aliffia Yasya; Nurshiami, Siti Rahmah; Jajang, Jajang
Jurnal Ilmiah Matematika dan Pendidikan Matematika Vol 17 No 1 (2025): Jurnal Ilmiah Matematika dan Pendidikan Matematika (JMP)
Publisher : Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jmp.2025.17.1.15866

Abstract

The implementation of product distribution requires transportation to deliver products effectively across various locations. Challenges encountered during this process include varying distribution sites, travel distances, time taken for product delivery, transportation costs, and other related factors. To address these challenges, selecting an efficient travel route is crucial. The Traveling Salesman Problem (TSP) serves as a practical application of graph theory in tackling such distribution issues. The Ant Colony Optimization (ACO) algorithm emerges as a viable solution for route optimization, particularly in addressing TSP challenges to derive optimal routes. Results derived from the TSP calculations utilizing ACO, executed through the Matlab R2018a application, employed parameters of
The Nexus of Environmental Performance and Economic Growth: A Panel Analysis from Organization of Islamic Cooperation Countries Khafidh, Muhammad; Jajang, Jajang; Junejo, Safiullah
Muslim Business and Economics Review Vol. 4 No. 1 (2025)
Publisher : Universitas Islam Internasional Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56529/mber.v4i1.432

Abstract

The climate is changing and the earth is getting hotter. Cutting down rainforests, burning fossil fuels, and farming livestock all contribute to greenhouse gas emissions. Human economy and the natural world are closely connected. This study evaluates the relationship between environmental performance and economic growth using panel data for Asian member states of the Organization of Islamic Cooperation (OIC) for the years 2020 to 2022. Data on Environmental Performance Index and Gross Domestic Product growth were collected from the Yale Center for Environmental Law & Policy and the World Bank. Panel data regression was used by selecting the best parameter estimates from three panel data regression models: Common Effect Model (CEM), Fixed Effect Model (FEM), and Random Effect Model (REM). The study findings are anticipated to enhance nations' consciousness regarding environmental concerns and to enhance their focus on ecologically sustainable economic growth and development trajectories.
ORDINAL LOGISTIC REGRESSION MODEL AND CLASSIFICATION TREE ON ORDINAL RESPONSE DATA Jajang, Jajang; Nurhayati, Nunung; Mufida, Suci Jena
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 16 No 1 (2022): BAREKENG: Jurnal Ilmu Matematika dan Terapan
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (809.781 KB) | DOI: 10.30598/barekengvol16iss1pp075-082

Abstract

Logistic regression (LR) is a model that associates the relationship between category-type response variables with quantitative or quantitative and qualitative predictor variables. The prediction of the LR model is in the form of probability. This research studied logistic regression (LR) models and Classification Trees in the case of ordinal response variable types. The data used in this research from The Central Statistics Agency (BPS). The research variables used are Human Development Index (HDI), gross enrollment rate for high school, percentage of poor people, open unemployment, and percentage of married age <17 years and some of the related predictor variables in Central Java Province in 2018. The HDI data is categorized into three levels, namely very high, high, and moderate. The results of the ordinal LR model show that there are three factors that influence the HDI, they are the gross enrollment rate for high school (GER), the percentage of the poor, and the proportion of women who married at the age of less than 17 years. Comparison of the accuracy LR model and Classification Tree in classification analysis shows that if the training data used is 60%-70% the LR model is better than Classification Tree, while the training data used is more than 70% and less than 86% then the Classification Tree model is better than LR.
Biplot Analysis Methods for Selecting the Consumer's Preferences of Primary Needs in Java Island Indonesia Jajang, Jajang; Supriyanto, Supriyanto; Maryani, Sri; Bawono, Icuk Rangga; Novandari, Weni; Gunawan, Diah Setyorini; Naufalin, Rifda
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 8, No 3 (2024): July
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v8i3.22264

Abstract

The effect of COVID-19 pandemic in February 2020 had changingchanged human consumption pattern. Most people especially for lower and middle communitycommunities, they only be able to fulfils the primary needs. The COVID-19 pandemic had been made some companies done a work termination. Therefore, people is required to sort out and choose needs that are on a priority scale. This article used biplot methods to analyze behavior of the consumers consumer's primary needs during the COVID-19 pandemic. Respondents number of this research are 100 respondents from 4 districts in Java Island who filled out the questioner. In some references, biplot analysis methods focus on agriculture field such as determining the best genotypes and habitats of plants. Rarely of them cosider in economic point of view for example in consumers’ preferences. As we known that biplot analysis is a valuable technique for identifying environtmental condition. It is superior to other statistical methodologies because of its superior predictive accuracy. This method represent a grapics of multivariate data that plot information between the observation and variables in cartesian coordinates. Therefore, the goal of this study examines the consumers' preferences in the Java Island, Indonesia, using biplot analysis to assess preferences of primary needs such rice, cooking oil and margarine in four districts, Bekasi, Madiun, Tasikmalaya, Banyumas, in Java Island were conducted. Regarding to the result of principal component analysis, it shows that consumers have same priority to choose the brand of the cooking oil. It was shown from score of PC1 and PC2 values. The result provide helpful information about the consumer preferences of primary needs during COVID-19 from four districts in Java Island.  
MODEL SURVIVAL SEMIPARAMETRIK DAN PARAMETRIK UNTUK DATA DEMAM BERDARAH DENGUE (DBD) DI RSUD KABUPATEN CIAMIS TAHUN 2020 Jajang, Jajang; Ashfahani, Raden Ninditya Ghina; Tripena Br.Sb, Agustini; Nurhayati, Nunung
JST (Jurnal Sains dan Teknologi) Vol. 11 No. 2 (2022)
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (339.142 KB) | DOI: 10.23887/jstundiksha.v11i2.43493

Abstract

Data survival merupakan bagian dari time-to-event data.  Data survival adalah data longitudinal dimana subjek dipantau dan diikuti dari awal permulaan hingga hingga subjek tersebut mengalami peristiwa yang diinginkan. Demam Berdarah Dengue (DBD) merupakan penyakit infeksi yang disebabkan oleh virus dengue, yang ditularkan dari nyamuk Aedes Spp.  Penanganan pasien DBD dengan karakteristik yang dimilikinya perlu dikaji agar untuk mendapatkan informasi dan mengambil langkah yang tepat. Salah satu upaya dari sisi pemodelan adalah dengan menganalisis daya taha (survival) pasien DBD.  Penelitian ini bertujuan untuk menganalisis performa model survival parametrik dan semiparametric pada kasus DBD. Metode estimasi Breslow, Efron, dan Exact merupakan pilhan estimasi parameter karena dapat menangani kasus waktu kejadiann kembar (ties). Pemilihan performa model erbaik didasarkan pada Akaike Information Criteria (AIC). Hasil analisis menunjukkan bahwa model terbaik yang diperoleh adalah model semiparametrik Cox PH dengan metode estimasi Exact. Berdasarkan model ini ditemukan bahwa pasien dengan karakteristik berusia lebih muda, kadar hematokrit rendah, kadar hemoglobin tinggi, kadar leukosit rendah , dan suhu badan rendah memiliki laju kesembuhan yang lebih besar dibandingkan dengan pasien dengan karakteristik sebaliknya.