Value Of Car Research Articles

ANALISIS KOMPARASI KINERJA KEUANGAN BANK UMUM SYARIAH DENGAN PENDEKATAN METODE CAMEL

This study aims to compare the performance levels of two Islamic commercial banks in Indonesia, namely Bank BCA Syariah and Bank Muamalat Indonesia for the period 2018 to 2022. This study uses a method that is often used to analyze the level of performance of Islamic banking, namely the CAMEL method. The indicators in this study consist of five financial ratios, namely CAR, NPF, NPM, ROA, and FDR. This research uses quantitative methods with comparative research types. Using secondary data from financial reports published on the official website of each bank. Kolmogorov-Smirnov test is used for data normality testing and hypothesis testing using independent t-test and Mann-Whitney test. The results showed statistically significant differences in the values of CAR, NPF, ROA, and FDR in Islamic banking between Bank BCA Syariah and Bank Muamalat Indonesia, then there was no significant difference in the NPM ratio between the two banks. Based on the results described, Bank BCA Syariah has a superior average value in terms of CAR, NPF, NPM and ROA ratios compared to Bank Muamalat Indonesia. Meanwhile, the performance of Bank Muamalat Indonesia's FDR proportion is better than Bank BCA Syariah in recent years. Therefore, it can be said that Bank BCA Syariah and Bank Muamalat Indonesia have different performance.Keywords: Financial Performance; Islamic Banks; Camels Method

Prediction of Resale Value of Pre-Owned Luxury Cars in the Indian Market Employing Machine Learning Techniques

Abstract: The market for second-hand luxury cars in India is witnessing a significant surge, expected to grow at a rate of 16.30% from 2024 to 2032. This growth is fueled by increased car manufacturing, rising disposable incomes, and a shift in consumer preferences towards luxury brands. However, accurately determining the resale value of these vehicles presents a challenge due to various influencing factors. In this dynamic market, informed decision-making is crucial for luxury car buyers. Digital platforms have revolutionized access to real-time market data, helping both buyers and sellers stay updated on pricing trends. Our research explores the complexities of predicting prices for pre-owned luxury cars and introduces a predictive analytics framework using advanced machine learning algorithms. We collected and preprocessed a comprehensive dataset and conducted an in-depth exploratory data analysis. Various regression techniques, including Linear Regression, Decision Tree, Random Forest, and Extreme Gradient Boosting, were employed to forecast prices. These models were evaluated using metrics such as Mean Absolute Error (MAE), Mean Squared Error (MSE), and Root Mean Squared Error (RMSE) to identify the most accurate predictive model. This study offers a systematic solution for price prediction, enhancing the buying process for stakeholders in the second-hand luxury car market

Implication of Different Data Split Ratios on the Performance of Models in Price Prediction of Used Vehicles Using Regression Analysis

Introduction; Artificial intelligence (AI) and Machine Learning have become buzzwords lately due to technological changes and data quality testing, especially in shape and finish analysis. Lots of research has been conducted for linear regression algorithms to predict the price in different sectors for share stock, rental properties, prices of used cars etc. This study provides suitable data split ratio for optimum cost estimation based on linear regression model. In present days there is an increasing demand for having own car for every middle class family therefore this have given opportunity to motor vehicle business to offer wide range of used vehicle for re-sale especially companies like Maruti Suzuki, Tata motors & Mahendra motors in Indian motor vehicle industries. Therefore, it is important to know the current value of your car before spending your hard-earned money on any item. Objective; The objective of this paper is finding appropriate value of cars in Metropolitans or even in state capitals. Features like model, mileage, AC, seating capacities, fuel type automatic will be taken into account when doing this. This estimate is designed to help customers find the right options to suit their needs. Methods; We have used a linear regression model to estimate the value of the respective car. Results; For doing this price prediction in this paper using liner regression we have tried to find the optimum accuracy of model by varying data split ratio for training and test data set and concluded with the result that 80/20 ratio is the best ratio with optimum model accuracy for business domain analysis with labelled data set. Conclusion; The findings underscore the importance of careful consideration when selecting a data split ratio for price prediction models in the used vehicle market. The insights gleaned from this study can inform future research and contribute to the development of more accurate and reliable regression models in similar domains.

MSA-Net: A Precise and Robust Model for Predicting the Carbon Content on an As-Received Basis of Coal.

The carbon content as received (Car) of coal is essential for the emission factor method in IPCC methodology. The traditional carbon measurement mechanism relies on detection equipment, resulting in significant detection costs. To reduce detection costs and provide precise predictions of Cars even in the absence of measurements, this paper proposes a neural network combining MLP with an attention mechanism (MSA-Net). In this model, the Attention Module is proposed to extract important and potential features. The Skip-Connections are utilized for feature reuse. The Huber loss is used to reduce the error between predicted Car values and actual values. The experimental results show that when the input includes eight measured parameters, the MAPE of MSA-Net is only 0.83%, which is better than the state-of-the-art Gaussian Process Regression (GPR) method. MSA-Net exhibits better predictive performance compared to MLP, RNN, LSTM, and Transformer. Moreover, this article provides two measurement solutions for thermal power enterprises to reduce detection costs.

Associations of C reactive protein to albumin ratio, neutrophil to lymphocyte ratio, platelet to lymphocyte ratio with disease activity in patients with juvenile idiopathic arthritis

IntroductionRecent works in the scientific literature reported the role of C reactive protein to albumin ratio (CAR), neutrophil to lymphocyte ratio (NLR) and platelet to lymphocyte ratio (PLR) as biomarkers of disease activity in rheumatic diseases.ObjectivesTo investigate the role of CAR, PLR and NLR as potential markers of disease activity in children with non-systemic JIA (nsJIA) and their correlation with the risk of persistent disease activity of flare during follow up.MethodsOur prospective, cross-sectional study involved 130 nsJIA patients (74 with active disease and 56 with inactive disease according to Wallace criteria) and 62 healthy controls. Demographic, clinical and laboratory data were collected at baseline (T0) and at 3 (T1), 6 (T2), 12 (T3) and 18 months (T4) during follow up. Disease activity was evaluated through Juvenile Arthritis Disease Activity Score (JADAS-27).ResultsAt baseline, CRP and CAR were higher in patients than in controls (p = 0.046), while no differences were found for NLR and PLR. However, there was no positive correlation between CAR, NLR, PLR and JADAS-27 in JIA patients. To better investigate the role of CAR, NLR and PLR as markers of disease activity, we used a generalized estimating equation (GEE) model, applied to all patients either with or without active disease. According to this analysis, CAR and NLR baseline levels were predictive of higher risk of disease activity at 6 months follow up (p < 0.001).ConclusionsCAR and NLR could indicate persistent disease activity in patients with JIA. Their predictive value could be increased by their combined use and by the observation of their trend during follow up, since increasing CAR values over time could predict a disease flare in the brief time.

The interim analysis of a first-in-human phase 1 trial of ET-901, a CRISPR edited allogeneic immune-cloaked anti-CD19 CAR-T cell therapy in patients with r/r B-NHL.

e19010 Background: Allogeneic CAR T-cell therapy faces challenges like limited persistence and host rejection. Current research has improved its viability by modifying genes like B2M, despite new challenges like NK cell targeting have emerged. Through CRISPR screening, we discovered a novel gene, named GeneX, and its role in enhancing T cell persistence against allogeneic attacks and AICD. GeneX influences glycan composition, affecting immune responses and AICD initiation. Engineered GeneXKO/TCRKO/anti-CD19 CAR T cells (ET-901) resisted allogeneic killing and maintained anti-tumor effects without causing GvHD, marking a significant advancement in CAR T-cell therapy. Methods: ET-901 is being tested in a phase 1 trial for r/r B-NHL at a single center, utilizing a 3+3 dose escalation scheme and planning for expansion at the recommended Phase 2 dose. Participants must have an ECOG status of 0–2, without a history of allo-HSCT or CAR-T therapy. The study's main goals are to assess ET-901's safety and establish the optimal Phase 2 dosage. Patients undergo a 3-day lymphodepletion with fludarabine (30-50 mg/m2/d) and cyclophosphamide (500-1000 mg/m2/d), followed by a single-dose infusion of ET-901 at escalating doses (DL1:1*10e6/kg, DL2:3*10e6/kg, and DL3:10*10e6/kg). Pharmacokinetic monitoring occurs during follow-up. Results: From September 2023, a total of six patients were enrolled in the escalation cohort, including 4 patients with LBCL and 2 with FL. In these patients (3 males), the median age was 53 years (range: 46–55 years), and the median number of prior treatment lines was 5. The median SPD was 7,650 mm2 (range: 2,700-43,400 mm2). Notably, two cases in DL2 exhibited unusual lymphoma infiltration sites: patient No.4 in the forearm muscle and patient No.5 in the spleen. Update to February 2024, we have completed the safety evaluation of Dose Level (DL) 1 and DL2. No DLTs were observed. The most common TRAEs of any grade included leukopenia (6/6), granulocytopenia (6/6), anemia (6/6), thrombocytopenia (6/6), CRS (6/6), infection (2/6), ICANS (2/6), and GvH like reaction (1/6). All patients achieved objective responses, with 2 cases of PR and 4 cases of CR (1 in DL1, 3 in DL2). The peak values of CAR+ cells count and VCN in peripheral blood were 36.0/μl (range: 14.0-48.0/μl, median: day 7), and 9.6e4 copies/μg (range: 7.7e4-1.2e5 copies/μg, median: day 7), respectively. In all patients, a second expansion of CAR-T cells was observed alongside B cell recovery. This confirms that GeneX knockout enables allo CAR-T cells to maintain long-term immune privilege while preserving their biological function. Conclusions: The study demonstrated the safety and feasibility of ET-901 in patients with r/r B-NHL. These findings highlight the potential of ET-901 as an effective therapeutic approach for improving outcomes for these patients. Clinical trial information: NCT06014073 .

Determining of Appropriate Passenger Car Unit Values Due to a Change in Effective Width of Roadway

Legitimately, the passenger car equivalent value is determined based on the type and width of the road as well as the traffic volume. Interestingly, the effective width of roadway often varies due to land topography conditions and level of side friction. Theoretically, the number of survey posts should be determined based on road geometric and environmental conditions because traffic volume is a reflection of the choice of speed. Unfortunately, due to limited funds, traffic volume, travel speed and ride friction surveys were carried out at 1 survey point. As a result. the recommendations for strategies and/or traffic management and engineering techniques could be bias. This study aims to calculate the impact of differences in the effective road width on the equivalent value of passenger cars using the Speed Method. For this reason, a speed survey was carried out on a number of arterial roads in the Kupang urban area. It was found that changes in the effective width of road lanes have a significant impact on changes in motorbike speed so that the use of passenger car equivalent value for motorcycle should be based on the result of field survey, instead of a standardized value as it was recommended by Indonesian Highway Capacity Guide

Profitability Function on Capital Adequacy Ratio Model

The purpose of this study is to look at the relationship between the variables NIM, Loan to Deposit Ratio (LDR), Current Exchange Rate (CER), and Capital Adequacy Ratio (CER). This is predicated on the observation that multiple prior studies have yielded differing results, which motivates academics to conduct additional study. This study used 10 cross-sectional samples and a six-year time series with panel data multiple regression analysis. It is classified as quantitative descriptive research. This research formula uses NIM as an intervening variable with the goal of maximizing the CAR value. The primary focus of this research is the banking businesses that are listed on the Indonesian Stock Exchange. The use of multiple regression analysis is made to investigate panel data techniques, and two integrated research models are created into a single study model. The first study model's findings support the relevant theory by showing that CER can positively correlate its effect on NIM. Another finding in the second research model is that NIM has a positive association with its influence on CAR, which is consistent with the relevant theory. Only the relationship between CER and CAR can be explained by the NIM function as an intervening variable. It is envisaged that these findings would serve as a manual for Indonesian banking professionals to help them optimize the capital adequacy ratio

Function of Non-Performing Loans In The Capital Adequacy Ratio Model of the Banking Sector

Research is being done in order to address the discrepancies in the findings of earlier investigations as well as the phenomenon of non-performing loans (NPL), which cannot account for the effect it has on the CARR. As a result, the researchers used different time series and cross-sectional data in their subsequent studies. Using multiple regression analysis, this type of descriptive quantitative research examines panel data from 22 samples of banking sector firms over a seven-year period. This formula uses the research object, which are companies in the banking sector listed on the Indonesia Stock Exchange, and uses NPL as an intervening variable to maximize the CAR value. Two research models are combined in one model, and each model is subjected to the Chow Test, Hausman Test, Lagrange Multiplier Test, and model selection test stages. Findings in the first model indicate that LDR's negative connection with NPL can be used to explain its impact. These outcomes differ from the relevant theory. Similar to the first study model, where the results are not as relevant as the theory, the results in the second model are also just LDR and may directly explain its effect on CAR with a negative association. It is hoped that these findings would give banking sector managers the best possible direction

The role of C-reactive protein:albumin ratio and Neutrophil:lymphocyte ratio in predicting coronary artery disease.

Acute coronary syndrome (ACS), one of the most common causes of death worldwide, is a condition characterised by ischaemia and/or infarction due to reduced coronary blood flow. The most prevalent cause of ACS is coronary artery disease. In this study, we aimed to investigate the relationship between blood parameters that we commonly use in the laboratory [C-reactive protein (CRP), albumin, neutrophils and lymphocytes] and coronary artery disease (CAD). This retrospective, single-centre study included 100 patients who underwent coronary angiography, with the diagnosis of acute coronary syndrome between January and June 2023, and 106 patients with high clinical suspicion and normal coronary arteries as a control group. The NLR was obtained from the ratio of neutrophils to lymphocytes and the CAR was obtained from the ratio of CRP to albumin. We analysed the relationship between CAD and NLR and CAR according to laboratory findings and demographic characteristics of the patients. The average age of the study group was 59 ± 10 years. NLR and CAR values were higher in the patient group than the control group (5.2 ± 3.3 vs 2.27 ± 1.2, p = 0.004 and 0.5 ± 0.1 vs 0.097 ± 0.095, respectively, p < 0.001). Albumin ratios were found to be statistically significantly lower in the patient group than the patient group (42.4 ± 4 vs 44 ± 3.3, respectively, p = 0.01). In addition, CAR and NLR showed a significant diagnostic value for CAD in receiver operating characteristic curve analysis (area under the curve: 0.68 ± 0.07, p = 0.003; 0.66 ± 0.09 p ≤ 0.001). NLR and CAR values, which are important indicators of inflammation, were found to be higher in the patient group. We believe it may be important to monitor these patients more frequently and follow them closely in terms of CAD, especially if the rate is higher in individuals without CAD who come for out-patient clinic check-ups.

Measuring the Resilience of Rural Banks Against COVID-19 Pandemic: Evidence from West Java, Indonesia

The potential disruption of operational activities in rural banks is linked to MSME actors' inability to repay loans amid the COVID-19 pandemic. The quality of credit and financing provided by these banks is vital in ensuring income and interest continuity, thereby impacting profitability. This study aims to analyze the financial performance dynamics and factors influencing rural banks' profitability in West Java, Indonesia, during COVID-19. The research utilized multiple linear regression with REM estimation. Despite the pandemic's challenges, the ROA, CAR, and equity values of the rural banks met minimum standards, though NPL values exceeded maximum limits. The combined factors of CAR, NPL, equity, net income, and the pandemic collectively influence profitability. Specifically, NPL and the pandemic have significant negative effects, while net income positively impacts profitability. To bolster the resilience of rural banks during crises, suggested policy measures include strengthening capital reserves, tightening credit policies, implementing good governance practices, and enhancing operational cost efficiency.

Analisis Kesehatan Bank Pada Perusahaan Bank BUMN Periode 2018 – 2022

This research aims to determine the health level of state-owned banks for the period 2018 – 2022. The tool used to measure the health level of banks is the CAMEL (Capital, Asset, Management, Earnings, and Liquidity) analysis. The population of this research is 3 (three) state-owned banks listed on the Indonesia Stock Exchange (BEI), namely BRI, BNI, and Mandiri. The data used are financial reports from the three banks for the period 2018 - 2022. The results of this research show that in general the best financial performance is obtained by BRI, followed by Mandiri, and third is BNI and has the HEALTHY predicate. This is shown by the highest CAR, KAP, NIM, ROA, BOPO and LDR ratio values obtained by BRI, followed by Mandiri and the lowest is BNI. In general, the CAMEL score can illustrate that state-owned bank for the 2018 - 2022 period are quite good in terms of their financial performance and maintaining the bank's health level.

Концепція оцінки ергономічної стійкості транспортного потоку великих міст з урахуванням динамічності зміни впливових факторів

The methodological approach of forecasting the congestion of the streets of large cities, taking into account the fluctuations in the density of traffic flows and the speed of movement of cars in the flow, received further development. The methodical approach takes into account fluctuations in the dynamics of the traffic flow in the form of changes in the acceleration of the movement of cars in the flow and fluctuations in changes in the infrastructure of the road environment, which is associated with the number of traffic lights, pedestrian crossings and the number of lanes for the movement of vehicles. Through modeling, it was found that increasing the acceleration values of cars in the stream significantly increases the range of robustness. At low values of acceleration of cars, the reserve of resistance to the formation of traffic jams decreases, which negatively affects the traffic flow, there is a probability of the formation of traffic jams. The presence of fluctuations in the density of the traffic flow and the speed of movement of cars in the flow, due to changes in the acceleration of cars, allows making adjustments to the value of the robustness criterion. Adjustments can be made for different clusters of the road network, for different times of the day, and take into account the period of fluctuations. The dependences of the change in the robustness range of the traffic flow upon changing the infrastructure of the road network are given. It has been established that increasing the number of lanes and simultaneously reducing the number of traffic lights and pedestrian crossings on the controlled cluster significantly increases the stability of the movement of vehicles in the flow. Conversely, reducing the number of lanes, increasing the number of traffic lights and pedestrian crossings on the controlled cluster significantly reduces the stability of the movement of vehicles in the flow. Adjustment of density and movement speed can be performed taking into account the amplitude of oscillations. The concept of modeling and forecasting the stability of traffic flows of large cities to the formation of traffic jams is formulated. The main components of the concept, according to which such an assessment is performed step by step, taking into account the dynamics of changes in influencing factors, are substantiated. The proposed concept differs from the known ones in that it takes into account fluctuations in traffic flow parameters - the density and speed of movement of vehicles over time. Such changes are characteristic of the city's road network during "peak hours".

Komparasi Tingkat Kesehatan Bank Syariah dan Bank Konvensional dengan Pendekatan Resiko

This research aims to find out how the health level of Sharia Banks and Conventional Banks compares using the Risk-Based Bank Rating (RBBR) method. This research is quantitative research with comparative methods. This research data uses secondary data taken from the Bank Indonesia website. This research data analysis uses comparative quantitative statistics. The total sample is 10 banks consisting of 5 sharia banks and 5 conventional banks. The research results show that there is a significant (real) difference between the average value of credit risk in Islamic banks and conventional banks. There is no significant (real) difference between the average value of liquidity risk in Islamic banks and conventional banks. There is a significant (real) difference between the average ROA value for Islamic banks and conventional banks. There is no significant (real) difference between the average NIM value of Islamic banks and conventional banks. There is a significant (real) difference between the average CAR value for Islamic banks and conventional banks.

The influence of financial performance on profitability of sharia commercial banks in Indonesia using the CAMEL method

IntroductionResearch on Islamic commercial banks in Indonesia have been extensively conducted, with a focus on banks in general and large banks. However, research specifically targeting medium-sized banks, namely PT Bank Muamalat Indonesia, PT Bank Mega Syariah, PT Bank Panin Dubai Syariah, PT Bank BCA Syariah, and PT Bank KB Bukopin Syariah, is still limited.ObjectivesThis study aims to examine the influence of the financial performance of Islamic banks on their profitability using the CAMEL indicator.MethodThis research is quantitative with a correlational approach. The population in this study consists of 12 Islamic commercial banks in Indonesia, with 5 of them selected as samples. The sampling technique used is purposive sampling. The study utilizes secondary data from quarterly financial ratio reports of Islamic banks published by the Financial Services Authority (OJK). The analysis involves evaluating the impact of CAR, NPF, NOM, BOPO, and FDR on ROA using multiple linear regression analysis.ResultsThe findings indicate that, partially, CAR and NPF do not significantly affect the ROA of Islamic banks. However, NOM, BOPO, and FDR have a significant impact on the ROA of Islamic banks.Implicationsthe research motivates Islamic bank management to improve their financial ratios to meet the health criteria set by Bank Indonesia (BI) and OJK. Maintaining healthy financial ratios has implications for the level of trust that customers and potential customers have in Islamic banks and ultimately determines the long-term existence of these banks.Originality/NoveltyThis study contributes to the development of risk management theory by examining the factors influencing the fluctuations in the values of CAR, NPF, NOM, BOPO, and FDR on the ROA of Islamic banks.

High-sensitivity C-reactive protein/albumin (hs-CRP/albumin) ratio as a predictor of deterioration of clinical outcome in central nervous system infections

Central nervous system (CNS) infections such as encephalitis, meningitis, or myelitis have high morbidity and mortality in Indonesia. High sensitivity C-reactive protein (hs-CRP) is a sensitive marker of acute inflammation, while albumin is the most abundant protein component in plasma and cerebrospinal fluid (CSS). Infection triggers an inflammatory response so that an increase in the hs-CRP/albumin ratio (CAR) can be a predictor of worsening clinical outcome in patients with CNS infections. However, studies examining the predictor value of serum and CSF CAR on worsening clinical outcomes of patients are limited, particularly in CNS infections. The purpose of this study was to prove the CAR as a predictor of worsening clinical outcome in patients with CNS infections. It was an observational study using a prospective cohort design. Fifty subjects recruited until October 2021 at Dr. Sardjito General Hospital were involved. The multivariate regression analysis showed that serum CAR (OR=3.604; 95%CI=1.487-8.736; p =0.005) could be a single predictor. However, by combining three variables, namely serum CAR, CSF CAR, and decreased consciousness at admission, could be a stronger predictor of worsening clinical outcome in patients with CNS infection (AUC = 97.1%; 95%CI = 0.929-1.00; p &lt;0.001). The optimal cut-off value for serum CAR was 1.35 (Youden index = 0.88, sensitivity = 96%, specificity = 92%) while for CSF CAR was 0.14 (Youden index = 0.60, sensitivity = 76%, specificity = 84%). In conclusion, a combination predictive model of three variables, namely serum CAR, CSF CAR, and awareness at admission can be a stronger predictor of clinical outcome in patients with CNS infection than serum CAR alone.

The Impact of Macroeconomics Variables and Bank Internal Factors on Islamic Banking Performance During Covid-19 in Indonesia

&#x0D; &#x0D; &#x0D; 200&#x0D; &#x0D; &#x0D; Previous studies focused on Bank internal factors in analysing the financial performance of Islamic banks. In this paper, we examine the performance of Islamic Banks in Indonesia by using key macroeconomics and bank internal variables as well as including covid-19 as a dummy variable from 2010 to 2021. The study used secondary data collected from World Bank database and Islamic banks annual financial reports. An Econometrics models such as VAR, unit root test and Johansen cointegration test were employed in the estimation process in which ROA was used as a proxy to measure the performance of Islamic Bank whereas Eight variables such as GDP, BOPO, CAR, FDR, NPF, Trade, Inflation, and Covid-19 were used in determining the performance of Islamic Banks in Indonesia. The findings indicate that, the lagged values of Gross Domestic Product (GDP), BOPO, CAR, FDR trade and Covid-19 all have a positive relationship with ROA. In the other hand, the lagged variable of Non-performing Financing (NPF) shows a negative and statistically insignificant relationship with ROA. Consequently, the study recommends that government should introduce expansionary fiscal policy to stimulate economic growth thereby enhancing Islamic banks performance. From this results, management of Islamic banks and those in academia can use it in understanding the macroeconomic and bank internal factors that impact the financial performance of Islamic banking. However, this paper could not examine other variables like digital index, taxation and banks governance structure in determining the financial performance of Islamic banks in Indonesia.&#x0D; &#x0D; &#x0D;

Solid particle erosion evaluation of automotive paint coatings under the influence of artificial weathering

Solid particle erosion (SPE) is one of the most critical tribological problems causing damage to automotive paint coatings. The correct characterization of SPE and resistance against it makes the possible extended service life of the coating, increasing the resale value of cars. Car manufacturers and paint industries have developed new techniques to apply coatings and coatings that improve the initial and long-term appearance, scratch performance, and durability of coatings. Several works have focused on studying the degradation and performance of paint coatings. However, there needs to be more understanding of wear progress under different environmental degradation conditions. This study investigates the mechanisms and resistance of erosive wear of actual automotive paint coatings before and after exposure to an accelerated weathering process. Steel substrate panels with a typical paint coating system were exposed to weathering degradation by UV and immersion in an artificial acid rain solution. The chemical changes induced in the coatings were analyzed by FT-IR spectroscopy. Then erosive tests were carried out using silica sand particles at two different angles of incidence (30° and 90°) and temperatures (25 °C and 60 °C) for both samples (unexposed and weathering conditions). The SPE rate was determined for each coating by mass loss estimation using an analytical balance; meanwhile, wear mechanisms were analyzed in detail by SEM. The results showed decreased SPE resistance promoted by chemical changes in samples exposed to both weathering processes.

Pengaruh Proporsi Sepeda Motor terhadap Kinerja Ruas Jalan Tanpa Median

Motorcycles are a mode of transportation that is very commonly used in Indonesia. The large number of motorbikes on the road often causes congestion, because the ratio between the number of two-wheeled vehicles and four-wheeled vehicles when on the road becomes unbalanced. Passenger Car Equivalence Value for Motorcycles (MC) = 0.25 , Light Vehicles (HV) = 1.2 and Heavy Vehicles (LV) = 1.0. The influence of the Equivalence value of a motorcycle Passenger Car (emp) on the Degree of Saturation (DS) value, the smaller the Equivalence of a Passenger Car (emp), the smaller the Degree of Saturation (DS). The maximum degree of saturation (DS) occurs in the proportion of motorcycles 0.83%. And the influence of the proportion of motorcycles on Jalan Jendral Sudirman, Pasir Turtle District on Monday was 63.91%. while on Sunday the proportion of motorbikes was 65.37%.

Comparative Analysis of Islamic Banks’ Performance in Indonesia and Malaysia with RGEC and the Islamicity Performance Index (2018-2021)

Using the RGEC (Risk Profile, Good Governance, Profit, Capital) method for measuring financial performance and the Islamicity Performance Index (IPI) for measuring Shariah performance, this study seeks to identify differences in the performance of Islamic banks in Indonesia and Malaysia for the period from 2018-2021. Target sampling was used to select the sample, which consisted of secondary data from two Islamic banks in Indonesia and two Islamic banks in Malaysia from the banks’ 2018-2021 annual reports. Financial ratio analysis and various test analyses using the non-parametric Mann-Whitney U method are used as analytic methods. According to the statistical calculations of the RGEC method, there is no difference in the average values of NPF, GCG, ROA, and BOPO, but there is a difference in the average values of FDR, ROE, NI, and CAR between Bank Syariah Indonesia and Bank Syariah Malaysia. The IPI method reveals that the average values of PSR, ZPR, EDR, and the ratio of Islamic Income vs non-Islamic Income recorded differences in average value, and the ratio of Islamic Investment vs non-Islamic Investment demonstrates that there is no difference between the average scores of Indonesian Shariah Banks and Malaysian Shariah Banks.