The problem of power factor in the industry is critical. This is due to the issue of low power factor that can make the vulnerability of industrial equipment damaged. This problem has been resolved in various ways, one of which is the Automatic Power Factor Correction, with the most popular device called capacitor bank. There are also many methods used, but several methods require certain calculations so the system can adapt to the new plant. In this study, researchers proposed a capacitor bank control system that can adapt to plants with different capacitor values without using any calculations by using an Artificial Neural Network with a closed-loop controller. The system is simulated using Simulink Matlab to know the performance with two testing scenarios. The first is changing the value of the power factor on the system and changing the value of the capacitor power at each bank, the second comparing it with the conventional methods. The results show that the system has been able to adapt to different capacitor power values and has a better performance than the conventional method in power factor oscillation due to the extreme power factor interference

Every mobile robot mission starts with the robot being moved to the task site. From there, the robot executes its tasks. A control system is required to move the mobile robot's actuator (which may be in the shape of wheels or legs) and comprehend the environment around the robot to perform these movements (perception). This research aims to develop a technique to control a robot’s movement while detecting obstacles and distances toward an object. The robot is equipped with LIDAR and a camera to perform these tasks. The control is divided into two major parts, low-level and high-level controller. As part of a low-level controller robot, the Model Predictive Control (MPC) method is proposed to help with the control of the wheel while the Artificial Neural Network (ANN) approach to use in this study to identify obstacles and the Convolutional Neural Network (CNN) method for detecting objects, both ANN and CNN as a control for high-level part of the robot. The results of this study can prove that CNN can help detect existing objects with a value of 45% for detecting some objects. The obtained result from the MPC method, which has been combined with an ANN as an obstacle detector, is that the smaller the horizon value, the shorter the time needed to reach the desired coordinates with the result being 45 seconds.

This research discusses comparison between of financial performance of State-Owned Islamic Banks before merger, PT. Bank Syariah Mandiri (BSM), PT. Bank Rakyat Indonesia Syariah (BRI Syariah), and PT. Bank Negara Indonesia Syariah (BNI Syariah) with after merger into PT. Bank Syariah Indonesia (BSI) Tbk. The method used descriptive quantitative. Type of data used secondary data, with the company's financial statements for 2020 and in 2021, which was obtained from the official website of Indonesia Stock Exchange www.idx.go.id. Technique used in data collection is literature study. The results showed that average ratio of companies before the merger PT. BSM, PT. BRI Syariah, and PT. BNI Syariah in 2020 is Return On Asset (ROA) 1.26%, Return On Equity (ROE) 10.01%, Capital Adequacy Ratio (CAR) 19.09%, Operating Cost and Operating Income (BOPO) 85.46%, Non Performing Financing (NPF) 1.28%. The value of the financial ratio after the merger (PT. BSI, Tbk) in 2021 showed that values of ROA 1.61%, ROE 13.71%, CAR 22.09%, BOPO 80.46%, and NPF 0.87%. Results of descriptive analysis using statistic process is difference tests have a strong and also positive relationship between the company's financial performance before and after the merger with a significant value 0.00. In addition, there was an improvement in the company's financial performance after the merger into PT. BSI, Tbk. Then with these results, it shows that the company's financial performance after the merger as measured by the ratio of ROA, ROE, CAR, BOPO, and NPF is more better than the company before the merger.

Islamic Banking as an alternative financial institution for the community and its current condition is growing. Likewise with some sharia products offered began to adjust to the needs of the community. Given that most of Indonesia's population is Muslim, the potential for the development of Islamic banking is also quite large. Islamic banking should be able to develop more broadly to demonstrate sharia values reflected in law, economic, social and political institutions. The Islamic banking system is expected to apply Islamic economic rules to avoid the conventional system to conform to Islamic religious teachings. The development of Islamic banking customers today not only targets the worker segment but also targets generation Z, the majority of whom this year work as students. The current condition of Islamic banking is unknown among generation Z, so it is necessary to analyze what factors influence the selection of Islamic banking as a financial institution to facilitate economic activities. The results of the analysis can be formulated to carry out strategies related to marketing, operations, risk, and finance in carrying out activities. In answering this, research was conducted using quantitative methods using multiple linear regression which aimed to see psychological, cultural, social, personal, and marketing factors in relation to the selection of Islamic banking. The results showed that partially psychological factors, social factors, personal factors and marketing factors had a positive effect on variable Y, namely the selection of Islamic banking services generation Z and factor X represented by cultural factors had a negative influence not significantly.

Bank is a financial institution that functions as a liaison between parties who have excess funds and those who need funds. In creating bank health, it is measured by profitability indicators to see the ability to increase profits, measure effectiveness and efficiency in management.  Its profitability can be seen from the value of ROA (Return On Assets) and ROE (Return On Equity).  The banking industry has problems in bad debtors which can be seen from the value of NPL (Non-Performing Loan) and this is exacerbated by special conditions that have occurred in recent years, namely the Covid-19 pandemic. So it is necessary to see how the effect of non-performing loans on bank profitability during the Covid-19 pandemic and this study conducted a case study on Buku III banks in Indonesia represented by 7 banks that reported financial data from 2019-2021, namely Bank HSBC Indonesia, Bank Tabungan Negara, Bank DBS Indonesia, Bank Permata, Bank Mega, Bank DKI, and Maybank Indonesia. The results show that the results of the analysis using SPSS version 25, partially non-performing loans represented with NPLs have no effect on the profitability of banks represented with ROA and ROE. Meanwhile, the same condition occurs in the results of the analysis test simultaneously or together with non-performing credit variables, namely NPLs, do not affect bank profitability, namely ROA and ROE.