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All Journal ASERSI : Jurnal Akuntansi Terapan dan Bisnis Priviet Social Sciences Journal Journal of Demography, Etnography, and Social Transformation
Fadhlul Mubarak
UIN Sulthan Thaha Saifuddin Jambi
Humanities Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Environmental Science Law, Crime, Criminology & Criminal Justice Social Sciences

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Analisis Volume Saham Pada Saat Covid-19 Menggunakan Metode Regresi Dengan Teknik Imputasi Adi Setiawan Adi Setiawan; Fadhlul Mubarak
Jurnal Akuntansi Terapan dan Bisnis Vol 2 No 1 (2022): July
Publisher : Politeknik Negeri Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25047/asersi.v2i1.3321

Abstract

PT. Bintang Mitra Semestaraya Tbk is a subsidiary engaged in investment and trading. The company started as an investment company investing in real estate companies in developing basic housing projects, mid-range residential projects and companies developing commercial buildings. This study aims to determine the volume of shares in the company PT. Bintang Mitra Semestaraya Tbk during the Covid-19 pandemic. The stock data is simulated from 2020, 2021 and 2022 in daily form. This research only focuses on discussing the movement of stock values ​​during the Covid-19 pandemic and looking for some data related to Missing Value (missing or incomplete data) in the company's stock data using the imputation method. The correlation between data variables in simulations 1-8 as a whole has a significant correlation with the percentage of truth/trust in this study of 95%. Furthermore, in the regression model, the best model is seen from the parameter data, the smallest RSE is in simulation 6 and the largest RSE is in simulation 3   PT. Bintang Mitra Semestaraya Tbk adalah anak perusahaan yang bergerak di bidang investasi dan perdagangan. Perusahaan tersebut dimulai sebagai perusahaan investasi yang berinvestasi di perusahaan real estat dalam mengembangkan proyek perumahan dasar, proyek perumahan kelas menengah dan perusahaan yang mengembangkan bangunan komersial. Penelitian ini bertujuan untuk mengetahui volume saham pada perusahaan PT. Bintang Mitra Semestaraya Tbk di masa pandemi Covid-19. Data saham tersebut disimulasikan dari tahun 2020, 2021 dan 2022 dalam bentuk harian. Penelitian ini hanya berfokus membahas tentang pergerakan nilai saham selama masa pandemi Covid-19 dan mencari beberapa data terkait Missing Value (data hilang atau tidak lengkap) yang ada pada data saham perusahaan tersebut menggunakan metode imputasi. Korelasi antara variabel data pada simulasi 1-8 secara keseluruhan memiliki korelasi yang signifikan dengan persentase kebenaran/kepercayaan dalam penelitian ini sebesar 95%. Selanjutnya pada model regresi terdapat model terbaik yang dilihat dari data parameter RSE terkecil berada pada simulasi 6 dan RSE terbesar berada pada simulasi 3
Village Potential Statistics (PODES): Visualization of Schools in Jambi Province with Statistical Programming (R) Fadhlul Mubarak; Atilla Aslanargun; Vinny Yuliani Sundara
Journal of Demography, Ethnography and Social Transformation Vol. 2 No. 2 (2022): Journal of Demography, Etnography and Social Transformation
Publisher : Pusat Kajian Demografi, Etnografi dan Transformasi Sosial

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30631/demos.v2i2.1333

Abstract

One of the primary data that can be used in research is village potential statistics (PODES). The data was obtained based on research in a certain period by the Statistics Indonesia (BPS). This study aims to visualize the percentage of schools in each city/district in Jambi Province using R programming based on PODES data in 2014 and 2019. In this study, we not only visualize but also how to build attractive graphics and arrange them starting from windows, graphic size, dimensions, color, horizontal axis, vertical axis, and others. Of course, the graph produced in this study is different from the basic plot found in the R program, although the process carried out is also more complicated. From 2014 to 2019, in general, within a period of 5 years there has been an increase in the number of schools in each city/district in Jambi Province. However, from the university level, the number decreased. In 2014 the number of universities in Jambi City was 32 but in 2019 the number decreased to 24. There are even interesting things in Kerinci and Tebo district. In 2014 there were no universities listed, while in 2019 there were 3. This also affects the percentage of education level in each city/district.
SAR probit regression modeling using the fisher scoring approach: A case study of poverty levels on the island of Sumatra Panji Jiblathar; Germansah Germansah; Fadhlul Mubarak; Ellys Agustina; Nabilla Rida Tri Nisa
Priviet Social Sciences Journal Vol. 6 No. 4 (2026): April 2026
Publisher : Privietlab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55942/pssj.v6i4.1727

Abstract

The probit model is commonly used to study categorical response data. However, failing to account for spatial autocorrelation factors between regions can lead to inconsistent and biased parameter estimation results. This study focuses on examining the parameter estimation of the Spatial Autoregressive (SAR) Probit model through the Maximum Likelihood Estimation (MLE) method using the Fisher Scoring numerical iteration scheme. The model was implemented on poverty data across 131 regencies/cities in the Sumatra region for 2022. Empirical findings indicate that the GRDP growth rate, open unemployment rate, per capita expenditure, and expected years of schooling significantly affect the poverty rate. The results of this model development provide a prediction accuracy of 83.97%. This achievement is superior to that of the RIS Simulator technique, which only yields an accuracy of 74.05%. These results emphasize the advantages of the efficiency and accuracy of the Fisher Scoring approach in representing spatial dependencies in the poverty phenomenon in Sumatra.
Co-Authors Adi Setiawan Adi Setiawan Atilla Aslanargun Ellys Agustina Germansah Germansah Nabilla Rida Tri Nisa Panji Jiblathar Vinny Yuliani Sundara