Insurance fraud claims have become a major problem in the insurance industry. Several investigations have been carried out to eliminate negative impacts on the insurance industry as this immoral act has caused the loss of billions of dollars. In this paper, a comparative study was carried out to assess the performance of various classification models, namely logistic regression, neural network (NN), support vector machine (SVM), tree augmented naïve Bayes (NB), decision tree (DT), random forest (RF) and AdaBoost with different model settings for predicting automobile insurance fraud claims. Results reveal that the tree augmented NB outperformed other models based on several performance metrics with accuracy (79.35%), sensitivity (44.70%), misclassification rate (20.65%), area under curve (0.81) and Gini (0.62). In addition, the result shows that the AdaBoost algorithm can improve the classification performance of the decision tree. These findings are useful for insurance professionals to identify potential insurance fraud claim cases.

Many past studies concentrate on the relationship between macroeconomic factors and happiness. There is, however, very little empirical research on the same subject available in the case of Malaysia. Therefore, this study examines the effect of selected macroeconomic factors on levels of happiness in Malaysia. The time period considered in this study is from the year 2004 to 2021, and the data obtained come from various sources. To achieve the objective, data are analyzed by using the descriptive statistic tests and the multiple regression test. Output from multiple regression test provides an indication that the government expenditure (G) factor has a strong and positive association with happiness, while real GDP, on the other hand, recorded a negative relationship. This finding confirms the Easterlin paradox which made an assertion of a negative association between real GDP and happiness. Other than that, the positive relationship between government expenditures and happiness shows that increasing government spending over the years in schools, healthcare, road and infrastructure repairs, and social welfare has proven to improve happiness among Malaysians. The result for the inflation and unemployment test is positive and insignificant. These findings recommend that the Malaysian government should aim policies to promote people’s happiness by considering relevant and significant macroeconomic determinants of happiness.

Kajian ini bertujuan untuk mengukur tahap pengurusan stres dalam kalangan pelajar universiti, mengenal pasti faktor akademik yang mempengaruhi pengurusan stres, dan membandingkan perbezaan skor min bagi menentukan pengaruh faktor akademik terhadap tahap pengurusan stres umum. Data dikumpulkan menggunakan borang soal selidik Perceived Stress Scale 10 (PSS10) dan set soalan khusus yang dibangunkan untuk mengukur stres akademik. Seramai 100 pelajar dari pelbagai universiti awam terlibat dalam kajian ini. Analisis menunjukkan bahawa tahap pengurusan stres pelajar berada pada M=2.16 (Rendah), manakala stres akademik mencatatkan M=2.52 (Sederhana), dengan perbezaan 16.67% lebih tinggi dalam stres akademik berbanding stres umum. Dapatan kajian menunjukkan bahawa pengukuran faktor secara individu memberikan maklumat yang lebih mendalam tentang pengaruh faktor akademik terhadap pengurusan stres dalam kalangan pelajar. Selain itu, pengukuran tahap pengurusan stres dan stres akademik juga dilakukan untuk mengenal pasti tahap tekanan yang dihadapi oleh pelajar dalam konteks akademik. Dengan menganalisis skor min perbezaan antara stres umum dan akademik, kajian ini memberikan gambaran jelas tentang betapa besar pengaruh faktor akademik terhadap pengurusan stres dalam kalangan pelajar universiti. Secara keseluruhannya, kajian ini menekankan pentingnya menangani stres akademik sebagai satu langkah penting dalam mengurangkan kesan negatif terhadap kesejahteraan pelajar universiti.

HRMARS is well established journal publisher based in Pakistan. It is publishing prominent journals in social sciences since 2011.

This study aims to investigate the association between credit market performance and economic security in the United Arab Emirates (UAE) from 1990 to 2023 using various estimation techniques. The Gregory-Hansen cointegration test, ARDL bounds-testing approach, and DOLS, CCR, and FMOLS estimators were employed. Results from the cointegration tests show a long-term relationship between economic security and credit market performance, even with structural breaks. ARDL estimation indicates that domestic credit supply, nonperforming loans, lending interest rates, and institutional quality negatively affect both short-term and long-term economic security. These findings demonstrate that inefficiencies in the credit market, characterized by a rapid increase in credit supply and nonperforming loans, weak institutions, and a high cost of borrowing, pose a substantial challenge to the UAE's economic security and stability. Moreover, the ARDL findings suggest that oil price increases, public expenditure, foreign capital inflows, and real GDP contribute positively to economic security. These findings are confirmed by the robustness of FMOLS, CCR, and DOLS estimations. Based on these findings, policies, measures, and strategies to strengthen credit risk management in the financial sector, control unchecked credit growth, enhance the quality of economic institutions, and sustain the diversification of the economy away from oil and credit risks are recommended.