Article Per Year (5 Year)
p-Index From 2020 - 2025
4.529
P-Index
This Author published in this journals
All Journal SAINSMAT Jurnal Sains dan Teknologi Journal The Winners Syntax Literate: Jurnal Ilmiah Indonesia BAREKENG: Jurnal Ilmu Matematika dan Terapan JTAM (Jurnal Teori dan Aplikasi Matematika) Journal of Educational Research and Evaluation Performance Jurnal Ilmiah Matematika dan Pendidikan Matematika (JMP) Jurnal MSDA (Manajemen Sumber Daya Aparatur) Majalah Ilmiah Matematika dan Statistika (MIMS) Journal of Comprehensive Science SAINSMAT: Jurnal Ilmiah Ilmu Pengetahuan Alam Muslim Business and Economic Review Darma Sabha Cendekia Jurnal Akuntansi dan Keuangan Islam (JAKIs) Indonesian Journal of Statistics and Its Applications
Jajang Jajang
Program Studi Matematika, Universitas Jenderal Soedirman
Religion Humanities Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Physics Public Health Social Sciences Transportation Other

Published : 37 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 37 Documents
Search

 1   2   3   4 
PEMODELAN INDEKS PEMBANGUNAN MANUSIA DI PROVINSI JAWA TENGAH TAHUN 2017 MENGGUNAKAN ANALISIS REGRESI SPASIAL Alwi, Wahyuni; Jajang, Jajang; Nurhayati, Nunung
Jurnal Ilmiah Matematika dan Pendidikan Matematika Vol 11 No 1 (2019): JMP Edisi Juni 2019
Publisher : Jurusan Matematika FMIPA Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This research discussed about model of Human Development Index (HDI) in Central Java with spatial regression analysis. and identify  variables that give significant influence. First, analyze the influence factors based on result of p-value from t test in multiple linear regression models. Then, made spatial weight matrix with queen continguity method. After that, estimate spatial regression models, namely spatial autoregressive (SAR), Spatial error models (SEM), and spatial autoregive moving average (SARMA) and  choose the best model based on minimum AIC value. The results showed that SAR was the best spatial regression model and the significant variables was the gross enrollment rates at senior high schools, the health workers, and the district minimum wages. All of them that give positive influences. The variable that give biggest influence for HDI was the health workers.
KAJIAN METODE ORDINARY LEAST SQUARE DAN ROBUST ESTIMASI M PADA MODEL REGRESI LINIER SEDERHANA YANG MEMUAT OUTLIER Aflakhah, Zahrotul; Jajang, Jajang; Tripena Br. Sb., Agustini
Jurnal Ilmiah Matematika dan Pendidikan Matematika Vol 11 No 1 (2019): JMP Edisi Juni 2019
Publisher : Jurusan Matematika FMIPA Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This research discusses about the Ordinary Least Squares (OLS) method and robust M-estimation method; compare between the Tukey bisquare and Huber weighting from simple linier regression models that contain outliers. Data are generated through simulation with the percentages of outliers and sample sizes. Each data will be formed into a simple linier regression model, then the percentage of outliers, RSE and MAD values are calculated. The results show that RSE and MAD values produced by a simple linear regression model with the OLS method are influenced by the percentage of outliers. However, the regression model of robust M-estimation with sample size 30, 60, 90, 120, and 150 results an unstable RSE values with the change of the percentage of outlier and the MAD values that are not affected by the percentage of outliers and sample size. The robust M-estimation method with Tukey Bisquare weighting is as good as the Huber weighting.
Spatial EBLUP dalam Pendugaan Area Kecil Nusrang, Muhammad; Annas, Suwardi; Asfar, Asfar; Hastuty, Hastuty; Jajang, Jajang
Sainsmat : Jurnal Ilmiah Ilmu Pengetahuan Alam Vol 6, No 1 (2017): Maret
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1248.062 KB) | DOI: 10.35580/sainsmat6164562017

Abstract

Empirical Best Linear Unbiased Prediction (EBLUP) merupakan salah satu metode dalam pendugaan area kecil. Asumsi yang digunakan dalam EBLUP adalah bahwa pengaruh acak galat area saling bebas. Namun dalam beberapa kasus, asumsi ini sering dilanggar. Penyebabnya adalah keragaman suatu area  dipengaruhi area sekitarnya, sehingga pengaruh spasial dapat dimasukkan ke  dalam pengaruh acak. Akibat pelanggaran ini menyebabkan penduga EBLUP menjadi bias dan memiliki ragam yang besar. Solusi untuk mengatasi hal tersebut adalah dengan memasukkan informasi pengaruh spasial ke dalam model. Pendugaan area kecil yang memperhatikan pengaruh acak spasial area dikenal dengan istilah penduga Spatial Empirical Best Linear Unbiased Prediction (SEBLUP). Penduga SEBLUP memberikan pendugaan yang lebih baik dibandingkan dengan penduga EBLUP dengan membandingkan nilai ARRMSE dari masing-masing metode pendugaan.
Optimalisasi Fungsi Kepala Desa Dalam Pelayanan Publik di Era Revolusi Industri 4.0 Aridhayandi, M. Rendi; Fari, Achmad Rifqi Nurghi; Habiburrachman, Usamah; Jajang, Jajang
Jurnal MSDA (Manajemen Sumber Daya Aparatur) Vol 8 No 1 (2020): Juni
Publisher : Institut Pemerintahan Dalam Negeri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33701/jmsda.v8i1.1176

Abstract

Revolusi Industri 4.0 ditandai dengan munculnya IoT (Internet of Things) dan IoP (Internet of People) maka kepentingan interkoneksitas dalam segala hal termasuk dalam pelayanan publik sangat dibutuhkan. Masyarakat yang telah melakukan kontrak sosial dengan pemimpin yang telah dipilih secara demokrasi (pemilihan langsung), namun dalam pemilu tersebut masih sangat jarang persyaratan pemilihan Kepala Desa yang mewajibkan penguasaan informasi teknologi, sehingga korelasi antara Revolusi Industri 4.0 tersebut tidak optimal dalam pelaksanaan pelayanan publik yang berhubungan dengan kewenangan Kepala Desa. Perubahan paradigma akan keterhubungan masyarakat diera Revolusi Industri 4.0 ini sendiri telah memberikan kesempatan bagi Kepala Desa untuk melayani masyarakat secara lebih efisien, cepat dan murah, maka dari itu metode atau pendekatan yang digunakan dalam penelitian ini berbentuk Yuridis Empiris yaitu suatu kajian berdasarkan data di lapangan melalui aspek-aspek yuridisnya. Temuan dalam penelitian ini yaitu masih belum optimalnya pelayanan publik oleh Kepala Desa diera Revolusi Industri 4.0 yaitu dengan studi kasus di Desa Ciherang dan di Desa Bobojong. Selanjutnya identifikasi masalah penelitian ini adalah 1. Apa faktor penyebab Kepala Desa tidak optimal dalam pelayanan publik diera Revolusi Industri 4.0 ?, 2. Bagaimana upaya yang dapat dilakukan untuk optimalisasi pelayanan publik oleh Kepala Desa diera Revolusi Industri 4.0 ?
Management of Facilities and Infrastructure Physical Education SMPN North Bengkulu District Jajang, Jajang; Purwanto, Sugeng; Nanda, Fitri Agung; Novriansyah, Novriansyah
Journal of Education Research and Evaluation Vol 5, No 2 (2021)
Publisher : LPPM Undiksha

Show Abstract | Download Original | Original Source | Check in Google Scholar | 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 in North Bengkulu District. 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. This research was conducted at SMPN 02 and 04 North Bengkulu. 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.
ANALISIS SURVIVAL DENGAN COX PROPORTIONAL HAZARD PADA KASUS DEMAM TIFOID Baisaku, Nurul Azizah; Jajang, Jajang; Nurhayati, Nunung
Majalah Ilmiah Matematika dan Statistika Vol 22 No 1 (2022): Majalah Ilmiah Matematika dan Statistika
Publisher : Jurusan Matematika FMIPA Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/mims.v22i1.29325

Abstract

A common problem found in survival data is the presence of censored data. The length of hospitalization of Typhoid fever patients until declared cured is one of example of this data. Here, we use Cox regression model to analysis this data. Partial likelihood is one of the methods of estimating parameters for Cox regression model. In many cases of censored data, two objects (patients) have the same length of hospitalization (ties). Therefore, to estimate the parameters of the model must use the right method. Here we used partial likelihood Breslow, Efron, and Exact methods. The study was motivated by how the three methods performed for Cox regression model. The data used for the implementation of these methods is length of hospitalization of Typhoid fever patients at Mekar Sari Hospital-Bekasi in 2020. Based on AIC criteria, we found that exact method is the best model (minimum AIC) for parameter estimation of Cox regression model. Referring to the Cox regression model by using a significance level of 10%, there are five predictor variables that affects the length of patient hospitalization. The five variables are age, vomiting, dirty tongue, hemoglobin, and leukocyte.Keywords: Typhoid fever, Cox regression, Breslow method, Efron method, exact method.MSC2020: 62N02, 62N03
OPTIMISASI FUNGSI RASTRIGIN MENGGUNAKAN FLOWER POLLINATION ALGORITHM Taufik Hidayat; Wuryatmo Ahmad Sidik; jajang Jajang
Jurnal Ilmiah Matematika dan Pendidikan Matematika Vol 14 No 1 (2022): Jurnal Ilmiah Matematika dan Pendidikan Matematika
Publisher : Jurusan Matematika FMIPA Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jmp.2022.14.1.5819

Abstract

The Rastrigin function is a multimodal function. It is difficult to find a global minimum of the function because it has many local minimums. So, we need an effective and efficient algorithm to find a solution to the global minimum of the function without being trapped by the local minimum. The flower pollination algorithm is a metaheuristic algorithm, it is expected to be capable of solving multimodal function optimization problems. In this study flower pollination algorithm is used to find the global minimum of the Rastrigin function of two variables with MATLAB. The Rastrigin function of two variables is used as objective function for the flower pollination algorithm. The parameters are divided into three configurations based on the difference amount of pollen gamets, the probability switch, and the search domain, with two different iterations 300 and 1500. In order, to get the best results each configuration is running for 10 times. The best results from the flower pollination algorithm are obtained from the first configuration and 1500 iterations
APLIKASI BAHASA C++ DAN PHP UNTUK MENENTUKAN UKURAN SAMPEL PADA METODE STRATIFIED RANDOM SAMPLING Khanifudin khanifudin; Jajang Jajang; Bambang Hendriya Guswanto
Jurnal Ilmiah Matematika dan Pendidikan Matematika Vol 11 No 2 (2019): Jurnal Ilmiah Matematika dan Pendidikan Matematika
Publisher : Jurusan Matematika FMIPA Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jmp.2019.11.2.2267

Abstract

The accuracy of survey results depends on sample size. So far, in determining the sample size of the stratified random sampling method, researchers still use manual calculations. Because of that, this research aims to create a sample size determination program of the stratified random sampling method using C++ and PHP programming languages. This research begins with the study of literacy, creating flowcharts and pseudocode algorithms, writing program syntax, and implementing data on the number of civil servants in each UPK in Banyumas Regency. By entering a 95% confidence level, the error limit that can be tolerated is 5, and the strata cost of each is 1, the minimum sample size is 60 with the 1st and 2nd strata sample sizes is 45 and 15. The program is expected to help researchers to determine sample size more easily. So far, the program also minimizes errors in calculations because a warning will appear when an error occurs.
PEMODELAN INDEKS PEMBANGUNAN MANUSIA DI PROVINSI JAWA TENGAH TAHUN 2017 MENGGUNAKAN ANALISIS REGRESI SPASIAL Wahyuni Alwi; Jajang Jajang; Nunung Nurhayati
Jurnal Ilmiah Matematika dan Pendidikan Matematika Vol 11 No 1 (2019): Jurnal Ilmiah Matematika dan Pendidikan Matematika
Publisher : Jurusan Matematika FMIPA Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jmp.2020.12.1.1936

Abstract

This research discussed about model of Human Development Index (HDI) in Central Java with spatial regression analysis. and identify variables that give significant influence. First, analyze the influence factors based on result of p-value from t test in multiple linear regression models. Then, made spatial weight matrix with queen continguity method. After that, estimate spatial regression models, namely spatial autoregressive (SAR), Spatial error models (SEM), and spatial autoregive moving average (SARMA) and choose the best model based on minimum AIC value. The results showed that SAR was the best spatial regression model and the significant variables was the gross enrollment rates at senior high schools, the health workers, and the district minimum wages. All of them that give positive influences. The variable that give biggest influence for HDI was the health workers. Full Article
KAJIAN METODE ORDINARY LEAST SQUARE DAN ROBUST ESTIMASI M PADA MODEL REGRESI LINIER SEDERHANA YANG MEMUAT OUTLIER Zahrotul Aflakhah; Jajang Jajang; Agustini Tripena Br. Sb.
Jurnal Ilmiah Matematika dan Pendidikan Matematika Vol 11 No 1 (2019): Jurnal Ilmiah Matematika dan Pendidikan Matematika
Publisher : Jurusan Matematika FMIPA Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jmp.2020.12.1.1934

Abstract

This research discusses about the Ordinary Least Squares (OLS) method and robust M-estimation method; compare between the Tukey bisquare and Huber weighting from simple linier regression models that contain outliers. Data are generated through simulation with the percentages of outliers and sample sizes. Each data will be formed into a simple linier regression model, then the percentage of outliers, RSE and MAD values are calculated. The results show that RSE and MAD values produced by a simple linear regression model with the OLS method are influenced by the percentage of outliers. However, the regression model of robust M-estimation with sample size 30, 60, 90, 120, and 150 results an unstable RSE values with the change of the percentage of outlier and the MAD values that are not affected by the percentage of outliers and sample size. The robust M-estimation method with Tukey Bisquare weighting is as good as the Huber weighting. Full Article
Co-Authors Aflakhah, Zahrotul Agung Prabowo Agus Sugandha Agustini Tripena Br. Sb. Alwi, Wahyuni Andina, Resta Dwi Annisa, Yusrina Ratna Apriliana, Yhenis Apriyani, Mella Asfar Asfar, Asfar Ashari, Helmi Farid Ashfahani, Raden Ninditya Ghina Baisaku, Nurul Azizah Br. Sb., Agustini Tripena Budi Pratikno Dewi, Kanya Anggun Setya Kusuma Diah Setyorini Gunawan Diah Setyorini Gunawan DIMAS EKA PUTRA Fari, Achmad Rifqi Nurghi Guswanto, Bambang Hendriya Habiburrachman, Usamah Hastuty Musa Icuk Rangga Bawono Icuk Rangga Bawono, Icuk Rangga Ijudin, Ijudin Junejo, Safiullah Khanifudin khanifudin khanifudin, Khanifudin Kristy, Kristy M. Rendi Aridhayandi Maryani, Sri Mashuri Mashuri Mufida, Suci Jena Muhammad Khafidh Nanda, Fitri Agung Novriansyah Novriansyah, Novriansyah Nunung Nurhayati Nuraliya, Aliffia Yasya Nurjuman, Iman Nusrang, Muhammad Rifda Naufalin Sb., Agustini Tripena Br. Sidik, Wuryatmo Ahmad Siti Rahmah Nurshiami Siti Rahmah Nurshiami, Siti Rahmah Sri Anggraeni, Ulan Sri Maryani Sugeng Purwanto Sulasih Sulasih Supriyanto Supriyanto Supriyanto Supriyanto Suwardi Annas Suwardi Annas Sylvia Meilani, Sylvia Taufik Hidayat Taufik Hidayat Tripena Br. Sb., Agustini Tripena Br.Sb, Agustini Triyani Triyani Wahyuni Alwi Weni Novandari Weni Novandari Wuryatmo Ahmad Sidik Zahrotul Aflakhah