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All Journal PROSIDING SEMINAR NASIONAL Jurnal Statistika Universitas Muhammadiyah Semarang Jurnal Matematika dan Statistika serta Aplikasinya (Jurnal MSA)
Muhammad Saifudin Nur
Unknown Affiliation
Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Environmental Science Mathematics Medicine & Pharmacology

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SPATIAL AUTOCORRELATION UNTUK DETEKSI DATA KEWILAYAHAN PRODUK DOMESTIK REGIONAL BRUTO PROVINSI JAWA TENGAH Muhammad Saifudin Nur; Abdul Karim
PROSIDING SEMINAR NASIONAL & INTERNASIONAL 2017: Prosiding Seminar Nasional Pendidikan, Sains dan Teknologi
Publisher : Universitas Muhammadiyah Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (642.219 KB)

Abstract

Spatial Autocorrelationl is one of the method that can determined spatial characteristic in data variables. Sparial Autocorrelation is able to define whether there is spatial characteristic ineach variables at regression models. The purpose of this study is to map and Detecting the Spatial Autocorrelation  for Gross Regional Domestic Product (GDRP) data in Central Java province with appropriate spatial weighting. The data used is the GDRP data and the factors that affect the GDRPie labor, human capital, roads infrastructure in 2015. Based on the results, the spatial efect on GDRP data is significanly occurs. Keywords : Spatial Autocorrelation, Ordinary Least Square, GDRP
MODEL TERBAIK ARIMA DAN WINTER PADA PERAMALAN DATA SAHAM BANK Moh. Yamin Darsyah; Muhammad Saifudin Nur
Jurnal Statistika Universitas Muhammadiyah Semarang Vol 4, No 1 (2016): Jurnal Statistika Universitas Muhammadiyah Semarang
Publisher : Department Statistics, Faculty Mathematics and Natural Science, UNIMUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (830.286 KB) | DOI: 10.26714/jsunimus.4.1.2016.%p

Abstract

Peramalan harga saham adalah hal yang sangat penting bagi pelaku saham pasar utama untuk membuat keputusan serta transaksi. Salah satu sektor yang sangat berpengaruh pada harga saham indonesia (IHSG) adalah sektor perbankan. Sektor perbankan diketahui menjadi penyumbang terbanyak emiten saham terbaik di indonesia. Salah satu metode peramaln yang dapat digunakan adalah ARIMA (autoregressive/integrated/moving average), model ini meliputi dua hal yaitu analisis pola deret dan seleksi model. Model winter adalah model peramalan yang menitik beratkan pada data yang megandung pola trend serta musiman, sedangkan dalam ARIMA mengharuskan kestasioneran data. Kedua model dibuat dalam data 3 besar bank di Indonesia yaitu Bank Rakyat Indonesia (BBRI), Bank Mandiri (BMRI), dan Bank Central Asia (BBCA) pada 109 hari pada periode 1 desember 2015 hingga 13 mei 2016. Hasil permalan menunjukkan bahwa model yang sesuai bagi BBRI adalah ARIMA(1,1,2), BMRI adalah Winter multiplikatif (0.2,0.2.0,2), dan BBCA tidak sesuai dengan kedua model peramalan.Kata Kunci : ARIMA, Winter, BBRI, BMRI, BBCA
Autocorrelation Spatial Infrastruktur Transportasi di Jawa Tengah Abdul Karim; Muhammad Saifudin Nur; Akhmad Faturohman
PROSIDING SEMINAR NASIONAL & INTERNASIONAL 2017: Prosiding Seminar Nasional Publikasi Hasil-Hasil Penelitian dan Pengabdian Masyarakat
Publisher : Universitas Muhammadiyah Semarang

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Abstract

This paper describes the spatial dependence of road transport infrastructure in Central Java using Moran's global approach. The results show that road transport infrastructure in Central Java has a spatial dependence on alpha five percent. In addition, the value of Moran's index is positive which indicates that each adjacent area has a positive spatial dependence.Keywords: spatial autocorrelation, Moran's I, Spatial Dependency, Transportation Infrastructure.
Pemodelan Spatial Autoregressive (SAR) untuk Persentase Kemiskinan di Jawab Barat Tahun 2021 Muhammad Saifudin Nur; Prizka Rismawati Arum; Fenny Amalia Adani; Cintadea Amanda Dwi Aryani; Aqsal Maulana
Jurnal MSA (Matematika dan Statistika serta Aplikasinya) Vol 12 No 1 (2024): VOLUME 12 NO 1 TAHUN 2024
Publisher : Universitas Islam Negeri Alauddin Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/msa.v12i1.39449

Abstract

Spatial Autoregressive Model (SAR) is a spatial regression model that has a spatial effect on the dependent variable. Spatial data refers to data that contains geographic information or regional location. Spatial analysis process consisting of visualization, exploration and modeling. This study uses the response variable (y), namely poverty, and 5 predictor variables, namely AMH (x1), open response rate (x2), GRDP (x3), participation rate (APS) (x4), and life expectancy (x5). A significant factor influencing West Java's poverty is GRDP (x3). The best model for the data in this study is the SAR because the R square value in the spatial regression is greater than the classical regression of 62%. There is no significant independent variable in the classical regression model but after modeling using SAR there is one significant variable which means it gives added value to the SAR regression model as the best model.
Co-Authors Akhmad Faturohman Aqsal Maulana Cintadea Amanda Dwi Aryani Fenny Amalia Adani Karim, Abdul Moh. Yamin Darsyah Prizka Rismawati Arum