Analisis harga saham pada PT. BTPN Syariah Tbk dengan metode EMA (exponential moving average) Tahun 2020-2022

This study uses a quantitative research method that aims to apply time series charts to the shares of Bank Syariah Tbk. The right guess is the main information needed by investors in determining the next strategy in investing, one of which is the Exponential Moving Average method. This method is a time series method used to predict the future using historical data. Giving weights involves a period, so the longer the period we use, the less weighting the last value we use.With the abundance of existing data, a system that utilizes past data has been built, in other words, a time series model tries to use the past time series to predict, later the system will be useful to assist investors in predicting estimates of the magnitude of the value in the future so that they can determine the right strategy for investent

The Impact of Islamic Financial Development, GDP, and Population on Environmental Quality in Indonesia

Environmental problems are becoming an issue along with the issue of global warming whose impacts are increasingly being felt. Cases of environmental destruction in Indonesia are increasing, so several directions of government policies have started toward sustainable development goals (SDGs). The situation has challenged Islamic finance, an alternative financial system that is said to be the answer to the current toxic financial system, to prove itself to support the environment quality. This research aims to determine the impact of Islamic financial development, Gross Domestic Product (GDP), and population on the environmental quality in Indonesia using data spanning from 2016 to 2020. The results show that GDP significantly impacts the environmental quality of almost all major islands in Indonesia. Overall, in the territory of Indonesia Islamic financial development had a significantly negative effect at a significant level of 10% on environmental quality

Pemodelan Tingkat Suku Bunga Surat Perbendaharaan Negara 3 Bulan

One of the basic macroeconomic assumptions that is still experiencing difficulties developing an accurate economic model is the 3-month Treasury bill (Surat Perbendaharaan Negara/SPN). This is mainly caused by its irregular data period, based on the average yield won in an auction held at a certain period. This study aims to build 3-month Treasury Bill (SPN) interest rate models by comparing several time-series methods, namely spline smoothing, exponential smoothing, moving average smoothing, and a regression model using s spread with one year Government Bond yield (Surat Utang Negara/SUN). This study shows that the spline smoothing method and regression analysis with one year SUN is the best model. In contrast, spline smoothing is better for short-term projections, and regression with one year SUN is better for medium-term projection

The Economics of The Household

This paper has knowing about applied the economics of the househol

Analisis Volume Saham Pada Saat Covid-19 Menggunakan Metode Regresi Dengan Teknik Imputasi

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

Locf imputation for Astra Agro Lestari Tbk. (Indonesia) and Anadolu Group (Turkey) stock

This study aims to apply time series graphs on stock of Astra Agro Lestari Tbk. and Anadolu Group with last observation carried forward (LOCF) imputation. The imputation was used because the data for the two companies had missing values on several dates. Missing value contained in the company Astra Agro Lestari Tbk. in Indonesia more than Anadolu Group in Turkey because of the difference in the number of holidays. Original data and data with complete dates are combined to form new data where missing values are seen on certain dates. The function used in the R program to form the graph is xts. However, the Date variable has a character class so it needs to be changed to the Date class. The xts function will error if the class is not changed. The modification also causes the horizontal axis of the graph to be replaced by the date. Based on the chart of stock prices and transaction volume of stock of the company Astra Agro Lestari Tbk. and Anadolu Group experienced increases, decreases, and is constant on several dates. Keywords: missing value, R programming, stock prices, transaction volume. MSC2020: 62M10, 91B84, 62-0