The importance of learning mathematics can not be separated from its role in all aspects of life. This research aims to analyze the achievement of the students' self-proficiency who are taught by using cooperative learning with Team Assisted Individualization (TAI) and conventional learning. Students need to possess self-proficiency ability well so that they could have confidence that they are capable of confronting and of solving their daily life problems in general or mathematical tasks in particular. The population in this research was students of Statistics study program at one of public universities in Makassar. The sampling technique used in this research was purposive sampling, while the instrument used was self-proficiency scale (SPr) which has been validated. The data were analyzed by using parametric and non-parametric statistics. The result of this research is that the achievement of the students' self-proficiency who are taught by using cooperative learning with TAI is better than students who are taught by using conventional learning.Keywords: cooperative learning with TAI, conventional learning, self-proficiency
The aim of this study was to identify and classify the student's concept image and its influence on the reasoning of the problem-solving of the derivative. The research used a qualitative description approach and used eight research subjects. From the answers collected upon the given problems, we obtained several variations of students' concept images, thus it showed how students' concept image influenced the reasoning. In order to clarify and classify the characteristic of the obtained answers, we summarized there were three categories of the concept image of the derivative, namely symbolically related to a basic formula of the derivative of a function, limit of the ratio of difference value of the functions, and the properties of the derivative of the functions. Furthermore, our study suggested that each student's concept image affecting the reasoning of the derivative. In addition, we found some misperceptions in answering the problem and misconception in the use of the basic formula of the derivative of the functions among the students' answers.
This research examines the effect of the crisis due to the COVID-19 pandemic on dividend policy in Indonesia. The purposive sampling method was used to collect data from corporates listed on the IDX from 2014 to 2020 and analyzed using static and dynamic panel data approaches. The fixed-effect models (FEM) were selected for the static panel data regression. Meanwhile, the first difference-generalized method of moments (FD-GMM) and system-generalized method of moments (SYS-GMM) were used for determine the robustness of the estimated dynamic panel data. The results showed that the crisis due to the pandemic led to higher dividend distribution on SYS-GMM. Furthermore, companies maintained the dividend level as a positive signal for investors which lifted the sluggish trade condition in the capital market. Profitability and previous year dividends positively affect dividend policy robustly. Furthermore, the results showed that age affects dividend policy on FD-GMM. Financial leverage has a robust effect, and firm size has an effect on FD-GMM in different directions, while investment opportunity does not affect dividend policy. Statistically, the FEM selected that violates the best linear unbiased estimation was proven to form parameters that were not much different from the estimates produced by the dynamic model, both from the coefficient of influence direction and significance, and the omitted variable bias occurs as evidenced in the robust test with dynamic model was solved. This research is also used as a reference for considering investors’ investment decisions in the new normal condition. Therefore, dividend policy can be considered as a positive signal to investors with the ability to stock trading activities in the capital market.
Metode Kuadrat Terkecil (MKT) merupakan metode penduga parameter yang paling banyak digunakan pada analisis regresi. MKT merupakan metode penduga parameter tak bias yang baik selama asumsi komponen galatnya terpenuhi. Namun dalam aplikasinya sering ditemui terjadinya pelanggaran asumsi. Diantaranya, pelanggaran asumsi galat berdistribusi normal disebabkan adanya outlier pada data amatan. Oleh karena itu, dibutuhkan suatu metode yang kekar terhadap keberadaan outlier. Metode pendugaan parameter yang kekar terhadap keberadaan outlier pada regresi linier diantaranya ialah penduga M, penduga S, dan penduga MM yang masing-masing memiliki keunggulan dari segi efisiensi dan breakdown point yang tinggi. Tujuan dari penelitian ini adalah untuk membandingkan penduga M, S, dan MM dalam menduga parameter regresi pada analisis regresi linier sederhana terhadap keberadaan outlier menggunakan data simulasi. Simulasi dilakukan untuk ukuran sampel yang berbeda (20, 60, dan 120) ketika terdapat 20% dan 45% outlier pada variabel bebas dan variabel terikat. Metode terbaik ialah metode dengan Standard Error (SE) dan Mean Square Error (MSE) terkecil. Hasil yang diperoleh menunjukkan bahwa penduga MM lebih baik dibandingkan penduga M dan penduga S.
<p>The inconsistent distribution of dividends is a unique phenomenon and it needs to be examined. Therefore, the purpose of this study is to examine ten predictors affecting dividend policy of the inconsistent distribution of dividends. This study used the purposive sampling method to analyze the data that were obtained from a total sample of 133 observation objects collected in the 19 real estates, property, and building construction companies listed on the IDX Between 2013 - 2019. Furthermore, the method used is hypotheses testing and statistical analysis tool used is the hierarchical multiple panel data regression with the Least Squares Dummy Variables. The results obtained from panel A are firm risk, financial leverage, and investment opportunity that affect the dividend policy. Meanwhile, the panel B results are company risk, financial leverage, investment opportunity, and previous dividend, although the previous dividend had no effect due to the different direction of influence. This study proves the determinants and relevance of the parametric statistical analysis in the inconsistent distribution of dividends. Moreover, it is useful for managerial practitioners to pay attention to predictors for increasing company performances and to ensure investors obtain optimal return of their dividend.</p>
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