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This research aims to analyze the influence of Regional Original Income (PAD), Special Allocation Funds (DAK), and General Allocation Funds (DAU) on the allocation of capital expenditure budgets on the island of Java. Capital expenditure is an important component in regional budgets that contributes directly to infrastructure development and improving public services. This study uses panel data from districts/cities on Java Island during the 2015-2020 period. The analytical method used is panel data regression with a fixed effects model (FEM) approach to identify the influence of independent variables on the dependent variable. The research results show that PAD has a positive and significant influence on capital expenditure. This indicates that regions with higher PAD tend to allocate more budget for capital expenditure. Meanwhile, DAK also has a positive and significant effect on capital expenditure, which shows that funds specifically allocated by the central government have succeeded in increasing investment in fixed assets in the regions. On the other hand, DAU was found to have a negative but insignificant effect on capital expenditure, indicating that general funds received from the central government did not directly encourage an increase in capital expenditure. This research provides important implications for regional policy makers in increasing PAD and utilizing transfer funds from the central government more effectively to accelerate the development of infrastructure and public services. Apart from that, the results of this research can also be a reference for further research in the field of regional finance and public budget management.  

The Indonesian capital market is experiencing significant growth, encouraging investors to consider shares as the main investment option. Fundamental analysis is important in assessing company performance, especially in the property and real estate sectors which are important for the Indonesian economy. This research aims to analyze the influence of fundamental factors such as Return On Assets (ROA), Return On Equity (ROE), Debt to Equity Ratio (DER), and Book Value (BV) on the share prices of property and real estate companies listed on the Indonesia Stock Exchange (BEI) for the 2021-2023 period. Using a panel data regression model with a random effects approach, the results show that BV has a partially significant positive effect on stock prices, while ROA, ROE and DER have a partially significant negative effect. These findings provide insight for investors in identifying key factors that influence share prices, so that they can help in making better investment decisions in the property and real estate sector.

This research aims to determine the effect of leverage, company size and retention ratio on company value in banking companies listed on the Indonesian Stock Exchange during the 2020-2023 period. The population taken and used in this research is annual data from 45 companies for four (4) periods totaling 180 data. This research uses the Eviews 12 analysis tool. Applying the Multiple Regression Analysis research method with the data type in the form of panel data with a Fixed Effect Model. The results of this company value research show that leverage and company size have a significant effect on company value, while the retention ratio has an insignificant effect on company value.

The main objective of the company is to maximise the value of the company. But a company can fail to increase company value, if it is not careful in applying the factors that affect company value. The purpose of this study was to determine the effect of dividend policy, institutional ownership, managerial ownership and audit committee on firm value proxied by TobinQ. The sample of this study is state-owned companies listed on the IDX for the period 2015-2021 with a total of 24 companies using purposive sampling method. Using the classic assumption test analysis method and hypothesis testing and multiple analysis, the analytical tool used is multiple linear regression panel data with the best model, namely the fixed effect model. The results showed that the t test for dividend policy was 2.375568 and the t table was 1.697 where t count> t table and a significant probability number of 0.025 <0.05 which means that dividend policy has a positive and significant effect on firm value. While institutional ownership, managerial ownership and audit committee have no significant effect on firm value. The F test results explain that the selected model is suitable for use in research. Then the results of the regression coefficient test (R²) indicate that the predictive ability of the 4 independent variables is 82.98%, while the remaining 17.02% is influenced by other factors outside the model which is not significant.

This study aims to analyze and obtain evidence regarding the effect of leverage, company size, and probility on corporate value in manufacturing companies listed on the Indonesia Stock Exhange for the 2017-2019 period. In this study, there are 3 independent vaiables tested, namely Debt to Equity (DER), Indikator Size (LN), and Return On Asset (ROA). And there is 1 dependent variable, namely Price to Book Value (PBV). The numbers of sample used are 21 manufacturing companies sub sector consumer goods onthes Indonesia Stock Exchange (IDX), the sampling technique used was purpose sampling. The analysis method used is the panel data regression analysis method using the Fixed Effect Model.the research result prove that leverage has no effect on corporate value, company size has negatif effect on corporate value, and probility has a positif effect on corporate value.

This research aims to analyze the influence of company growth, funding decisions and dividend policy on company value. This research was conducted by analyzing the financial reports of companies in the transportation and logistics sector listed on the Indonesia Stock Exchange (BEI) during the period 2018 to 2022. The sample used in this research was 9 technology sector companies listed on the Indonesia Stock Exchange during the period 2018 to 2022 using purposive sampling techniques. The data used in this research is secondary data in the form of financial reports from each company that has been used as a research sample. The variables used in this research are Company Growth (X1) as the first independent variable, Funding Decisions (X2) as the second independent variable, and Dividend Policy (X3) as the third independent variable and Company Value (Y) as the dependent variable. The panel data regression method was used as the research methodology in this study. Analysis of research results using EViews 12 Student Version Lite software. The research results show that the best model is the Fixed Effect Model (FEM). The results of this study show that partial company growth has no effect and is not significant on company value, partial funding decisions have a significant effect on company value, partial dividend policy has no effect and is not significant on company value, and simultaneously company growth and funding decisions and Dividend Policy influences Company Value.

The rapid growth of Internet of Things (IoT) and edge computing technologies has introduced new security challenges due to the distributed, heterogeneous, and dynamic nature of these environments. Conventional static security mechanisms, such as rulebased authentication and fixed trust models, are often inadequate for addressing evolving threats and abnormal behaviors in largescale IoT systems. To overcome these limitations, this study proposes a machine learningbased trust evaluation framework for enhancing security in distributed IoT environments. The proposed approach dynamically assesses the trustworthiness of IoT nodes by analyzing behavioral and interactionbased features collected at the edge layer. Machine learning models are trained to classify nodes into trusted and malicious categories and continuously update trust values in response to changing network conditions. Based on the predicted trust levels, adaptive security decisions are enforced to allow or restrict node participation in data sharing and computation processes. A quantitative experimental evaluation is conducted using simulated distributed IoT scenarios that include both normal and malicious behaviors. The performance of the proposed framework is evaluated using standard metrics such as accuracy, precision, recall, F1score, and detection effectiveness, and is compared against conventional static trust and rulebased security mechanisms. The results demonstrate that the proposed machine learningbased trust evaluation approach achieves significantly higher detection accuracy and robustness while maintaining low computational overhead. Overall, the findings confirm that integrating machine learning into trust management provides an effective and scalable solution for securing distributed IoT systems under dynamic and adversarial conditions.

The purpose of this study was to identify and analyze the impact of audit opinion and audit delay partially on the quality of financial statements, with profitability variables as moderating. This research was conducted at Islamic commercial banks registered with the financial services authority during the period 2018-2022. This type of research uses a quantitative approach, the research population involves a total of 11 Islamic commercial banks. The sample in the study was selected using purposive sampling method, which resulted in 11 samples with observations for 5 years. Hypothesis testing in this study used a panel data regression model with the Fixed Effect Model (FEM) approach and for testing the moderation variable using the MRA (Moderated Regression Analysis) model. The results of this study indicate that the partial results of audit opinion have a positive and significant effect on the quality of financial statements, while audit delay has a negative and significant effect on the quality of financial statements, while profitability is unable to moderate the effect of audit opinion on the quality of financial statements. Meanwhile, profitability is not able to moderate the effect of audit delay on the quality of financial statements.  

This study aims to analyze the effect of local taxes and regional levies on city/regency local revenue (PAD) in North Sumatra province for the 2016-2021 period. The research method used is panel data regression method. This type of research uses quantitative methods and the data used is secondary data, namely data on local taxes, regional levies and PAD. The chosen research method is the fixed effect model. From the simultaneous test results, it was found that local taxes and regional levies have a significant effect on regional original income with a significance value of 0.000. From the results obtained, it is hoped that the city/regency governments in North Sumatra Province can make better use of the available sources of development financing funds to increase the amount of Local Own Revenue, especially those sourced from Regional Taxes and Regional Levies.

The banking capital structure by manage appropriately for smooth operations. This study purposes to: analyze the effect of Profitability, Growth Bank, Bank size on the capital structure of Sharia banks in Indonesia. Assess the size effect of Profitability, Bank size, Growth Bank on the capital structure of Sharia banks in Indonesia. The research method used descriptive and verification. Data is obtain from the published Sharia Bank annual financial statement.Sample of this study is 33 Sharia Banks in Indonesia. Data analysis techniques used panel using the program Eviews 9 fixed effect models. The results showed the profitability and Bank Size are negative effect on the structure of Sharia Bank Capital in Indonesia. Growth Bank have no effect on the structure of Islāmic Bank Capital in Indonesia

Analysis of panel data regression is a regression method to determine the relationship between the independent variable and the dependent variable using combined data, namely between cross-section data and time-series data.Analysis of panel data regression can apply to the processing of rice production estimates for an area including the province of North Sumatera. North Sumatera is one of the provinces in Indonesia, at the very of the population focuses on the agricultural sector as the main livelihood in rice being the primary production. Based on data on the development of rice production at the Agriculture Office of North Sumatra Province, the level of rice production in 2019 for North Sumatra Province reached 4,693,563 Ton/Year.Throught Panel Data Regression Analysis with the three approach methods is Common Effect Model (CEM), Fixed Effect Model (FEM) and Random Effect Model (REM) , the best approach method is obtained, namely the Fixed Effect Model (FEM) with the best estimation model is . The coefficient of determination  of 0.950890, which means that the independent variable affects the dependent variable by 95.08% on rice production.Based on the estimation model, the development of rice production in the next 3 years, namely 2020, 2021 and 2022, has changes of around 39.88% (decrease), 10.68% (increase), 9.89% (increase).

Poverty is a complex problem that is still difficult to solve in almost all regions of Indonesia. Poverty is a measure of negative social conditions arising from increasing poverty. West Java is one of the areas that has a relatively high poverty rate and is increasing every year. It uses a panel data model with an estimated fixed effect model for 9 cities from 2017 to 2021. The purpose of this research is to analyze how and how much unemployment and HDI affect the poverty in West Java province. The data used is secondary data obtained from the Central Statistics Agency (BPS) which is processed. The results state that partially and simultaneously the unemployment variable and the human development index do not affect poverty.

The aim of this study is to analyze and measure the factors affecting Indonesia's economic growth rate by focusing on a number of factors, such as the human development index and inflation. The study use eviews10 software with its fixed effect model (fem) to see its enormous value of determinations and correlation between non-monetary variables and variables. The data studied came from the statistical central body in Indonesia, as well as several literature studies ranging from 2017 to 2021. From research and theoretical studies itis concluded that in 2017-2021 there is no effect between the human development index and inflation and economic growth in Indonesia.  

This study aims to analyze the effect of education level and population growth on economic growth in Indonesia for the 2017-2021 period. Economic growth is a process of changing economic conditions that occur in a country on an ongoing basis towards a condition that is considered better for a certain period of time. This research is a quantitative study, the data was processed using panel data analysis consisting of cross sectional data from six provinces and time series data for 2017-2021. The best regression model in this research data is the FEM (Fixed Effect Model) regression model. The results of this study show that simultaneously the variables of Education Level and Population Growth have no effect and are not significant on Economic Growth in Indonesia for the 2017-2021 period. And partially the variables of Education Level and Population Growth have no effect and are not significant on Economic Growth in Indonesia for the 2017-2021 period.

Terdapat fenomena penelitian ini yaitu : Diluncurkan bank pakan untuk meningkatkan kualitas dan produksi ternak, Impor gandum menjadi opsi alternatif yang diberikan pemerintah untuk menghadapi risiko kenaikan harga pakan, Memastikan dua perusahaan (PT Japfa Comfeed dan PT Charoen Pokphand (CP) Indonesia) menyerap jagung dari petani dan stoknya tercukupi saat panen raya, diharapkan harga jagung tidak anjlok dan berada pada titik keseimbangannya seperti biasanya, dan Pakan ternak diprediksi mengalami kenaikan pada periode kuartal akhir dan menariknya saham JPFA dan MAIN. Dari fenomena diatas, maka peneliti tertarik untuk mendalami aset lancar, total aset, utang lancar, persediaan dari perusahaan pakan ternak yang terdaftar di Bursa Efek Indonesia. Rumusan masalah observasi ini ialah bagaimana pengaruh Current Aset, Quick Aset, terhadap ukuran perusahaan studi  empiris pada perusahaan sector industri dasar kimia sub sector pakan ternak yang terdaftar di Bursa Efek Indonesia secara parsial maupun simultan. Observasi ini bertujuan untuk mengetahui, mengetest juga menganalisa pengaruh current aset, quick aset dan ukuran perusahaan apakah saling berpengaruh, atau sejalan dengan fenomena tersebut secara parsial ataupun simultan. Jenis penelitian ini ialah kuantitatif. Dalam observasi ini menghasilkan sampel uji sebanyak 5 perusahaan pakan ternak, peneliti melanggunakan data selama 3tahun dari tahun 2019-2021 sehingga menghasilkan data observasi selama periode penelitian 2019-2021 sebanyak 45 data. Dan diolah menggunakan aplikasi Eviews 12, dalam aplikasi eviews terdapat tiga (3) metode yaitu Common Effect (CE), Fixed Effect (FE), dan Random Effect (RE). Aplikasi Eviews melakukan beberapa test seperti: Chow Test, Hausman Test, Lagrange Multiplier Test, Uji Multikolinearitas, Uji Autokolerasi, Uji Heteroskedastisitas, Uji Normalitas, Panel Least Squares. Variabel Quick Ratio dalam model penelitian ini secara parsial memiliki berpengaruh terhadap variabel ukuran perusahaan dengan nilai Probabilitas 0.02 (< 0.05) sedangkan variabel Current Ratio dalam model penelitian ini secara parsial tidak memiliki pengaruh terhadap variabel ukuran perusahaan dengan nilai Probabilitas 0.10 (> 0.05). Variabel Quick Ratio, Current Ratio secara simultan memiliki pengaruh terhadap ukuran perusahaan  dengan nilai Prob(F-statistic) < 0,05  sebesar 0.00. Kelayakan variabel Quick Ratio, Current Ratio  terhadap ukuran perusahaan  sebesar 31,73%, sedangkan sisanya dipengaruhi oleh variabel lain, berupa utang jangka panjang, asset tetap, modal, penjualan, bunga, pajak, harga saham, dsb.

To be successful in the financial world, you must know how the public disclosure of business information affects stock prices. Specifically for Pakistan, this research will help us better understand the relationship between corporate governance, disclosure quality, and equity cost The Sys-GMM model has been employed by 167 non-financial enterprises listed on the Pakistan Stock Exchange since 2017. (PSX). Research shows it was in use between 2018 and 2020. The Sys-GMM technique for estimating may be used to account for endogeneity in corporate governance problems. We discovered that GMM projections failed to account for endogeneity, resulting in inaccurate conclusions, using pooled OLS and fixed-effect estimates. According to the research, the cost of equality and financial transparency are mutually incompatible. All of these factors contribute to the PSE's stock price decline, including board size, concentrated ownership, and CEO duality. The research es-tablishes a relationship between independent audit committees and high-quality audits and reduced equity expenses. Independent directors and competent auditors command a premium on the PSX. The duration of the approval process for financial statements has no bearing on the board's independence. Due to the scarcity of information disclosed in annual reports, investors anticipate a higher rate of return. The conclu-sions of the research may be beneficial to Pakistan's corporate govern-ance authorities and investors.

This study aims to analyze the influence of internal and external factors on bank credit. The data was obtained from banks listed on the Indonesian Stock Exchange in the 2017-2020 period. Samples were taken based on the purposive sampling technique. This research uses the data pool regression analysis. Then the selection of the best estimate based on the Chow test to select the Pooled Least Square (PLS) estimate with the Fixed Effect Model (FEM). Then the Hausman test was carried out to select the FEM estimate with the Random Effect Model (REM). The test results found that FEM was the best for further analysis. From the FEM output, it is concluded that Third Party Finance (TPF) and Loan to Deposit Ratio (LDR) have a positive effect on bank credit. Meanwhile, Non Perfoming Loan (NPL) and Capital Adequacy Ratio(CAR) do not affect bank credit. Then Economic Growth affects bank credit negatively. The Market Interest Rate has a positive effect on bank credit. The three state-owned banks have a higher ability to provide credit than the other banks in the sample of this study.

ABSTRACT With the rapid development of technology, the role of information systems is very important. One of the organizations that feel the benefits of an information system is government agencies. The process of deleting fixed assets is still using Microsoft Excel so its performance is still not effective. The problem that arises is when recording assets that will be deleted but the physical condition of the assets does not exist and another problem is that there are still many unrecorded assets for deletion so that employees have to look for asset data and become ineffective. This problem can be solved by designing an information system for the disposal of fixed assets using the waterfall and web-based model, the PHP programming language and MySQL as the database. The method used is the UML (Unified Modelling System) system modelling, namely Activity Diagrams and Use Case Diagram. The design of this information system aims to assist BPKAD employees in handling the asset write-off process and producing the required reports.   Abstrak Dengan adanya perkembangan teknologi yang pesat, peran sistem informasi menjadi sangat penting. Salah satu organisasi yang merasakan manfaat adanya sistem informasi yaitu instansi pemerintahan. Proses penghapusan pada aset tetap masih menggunakan Microsoft Excel sehingga kinerjanya masih belum efektif. Masalah yang muncul yaitu ketika pencatatan aset yang akan dilakukan penghapusan tetapi kondisi fisik asetnya tidak ada dan masalah lainnya yaitu masih banyak aset yang tidak tercatat untuk dilakukan penghapusan sehingga para pegawai harus mencari data aset tersebut dan menjadi tidak efektif. Masalah tersebut dapat diatasai dengan merancang sistem informasi penghapusan aset tetap dengan menggunakan model waterfall dan berbasis web, bahasa pemograman PHP dan MySQL sebagai databasenya. Metode yang digunakan  yaitu permodelan sistem UML (Unified Modelling Sistem) yaitu  Activity Diagram dan Use Case Diagram. Perancangan sistem informasi ini bertujuan untuk membantu pegawai BPKAD dalam menangani proses penghapusan aset dan menghasilkan laporan yang dibutuhkan.

This study aims to determine the effect of liquidity, operating cash flow, leverage, fixed asset intensity, and firm size to the selection fixed asset revaluation model in manufactured companies.  This research was done in Indonesia Stock Exchange (IDX) year 2013-2017.The sample in this research is taken by using purposive sampling method of 501 companies. The data usedare secondary data in the form of company's financial statements analyzed using logistic regression.The results of this study indicate that the liquidity, leverage, and operation cash flow have not effect to the selection of  fixed asset revaluation model. While fixed assets intensity and firm size have positive significant effect to the selection of  fixed asset revaluation model.  Keywords:             Fixed assets revaluation, liquidity, leverage, fixed assets intensity, operating cash flow, and firm size.

This research was conducted to examine the effect of Capital Adequacy Ratio (CAR), Loan to Deposit Ratio (LDR),Net Interest Margin (NIM), Non Performing Loans (NPL) to the Profitability of Foreign Exchange Banks. This research was set 5 years from the period 2013-2017. The population of this research used35 Foreign Exchange Banks listed on the Bank Indonesia. The facts used comes from the annual financial statements of 35 Foreign Exchange Banks. Data analysis using panel data regression analysis. To choose estimation of Fixed Effect Model (FEM) and Random Effect Model (REM) using Hausman Test technique. The results of data analysis using the help of E-Views software, based on the Hausman Test, are recommended to use Random Effect Model (REM). The results of data analysis show that 1) Capital Adequacy Ratio (CAR) hasno effect on profitability (ROA), 2) Loan to Deposit Ratio (LDR) has a  positiveeffect and significant on profitability (ROA), 3) Net Interest Margin (NIM) has a positive effect on profitability (ROA), 4) Non Performing Loans (NPL) has a negative effecton profitability (ROA).  Key Words :  return on asset, capital adequacy ratio, loan to deposit ratio , net interest margin, non performing loan.