PENGARUH CURRENT ACCOUNT SAVING ACCOUNT (CASA), LOAN TO DEPOSIT RATIO (LDR), DAN NET PERFORMING LOAN (NPL) TERHADAP LABA BERSIH PERUSAHAAN PERBANKAN YANG TERDAFTAR DI BEI PERIODE 2016-2020

Penelitian ini memiliki tujuan melihat adanya pengaruh CASA, LDR dan NPL terhadap laba bersih perusahaan perbankan yang terdaftar di BEI periode 2016 – 2020. Metode kuantitatif digunakan dalam penelitian ini dengan teknik pengumpulan data berupa studi dokumentasi pada data sekunder berupa laporan keuangan periode 2016-2020 dan penelitian terdahulu sedangkan untuk teknik analisis menggunakan Regresi Linier Berganda melalui program IBM SPSS versi 24. Penelitian ini mendapat hasil (1) CASA berpengaruh positif terhadap laba bersih perusahaan perbankan yang terdaftar di BEI periode 2016-2020 (2) LDR tidak berpengaruh terhadap laba bersih perusahaan perbankan yang terdaftar di BEI periode 2016-2020 dan (3) NPL berpengaruh negatif terhadap laba bersih perusahaan perbankan yang terdaftar di BEI periode 2016-2020. Penelitian ini diharapkan dapat membuka wawasan kepada investor terkait analisis fundamental perusahaan perbankan yang dapat dijadikan pertimbangan dalam berinvestasi.

Investment Pattern, Preferences and Financial Mangement Practices of Wesleyan University-Philippines Employees

This study determined the investment pattern, preferences, and practices of Wesleyan University-Philippines employees with the used of descriptive correlational methods of research, and the data were collected using a researcher-made survey questionnaire. Respondents of the study were the 305 employees chosen purposively. The result shows that most of the respondents belonged within the age range of 19 – 28 years old, married, a college graduate with 1 – 6 years in service, permanent, had a monthly income of 10000-21000 and had other sources of income from their husband/wife income. Likewise, most of the respondents had a saving for an emergency and unforeseen circumstances, had an investment and invested 1 – 5 percent of their income. Most of them had a saving account, intended to invest the money to more than five years in which the principal amount is secured, invested in the private sector, and expected to grow steadily. Similarly, this study found out that the respondents sometimes practice the five indicators of financial management practices used in the study. Moreover, profile variables were significantly correlated with financial management practices. Age, number of years in service, employment status, monthly income, and other sources of income were significantly associated with money management practices. Similarly, a number of years in service were correlated considerably with savings management practices. Finally, age, employment status, and other sources of income were significantly associated with investment management practices. Further, there is a significant difference in the respondents' assessment in all indicator of financial management practices.

THE EFFECT OF SAVING ACCOUNT OWNERSHIP AND ACCESS TO FINANCIAL INSTITUTIONS ON HOUSEHOLD LOANS IN INDONESIA

This study investigates whether saving account ownership and access to financial institutions influence household credit in Indonesia. Using a multinomial logit regression model and a sample of 294,426 households from the 2018 national socioeconomic survey and the village potential data, we find that account ownership is essential in encouraging formal credit and reducing informal credit. Access to commercial banks, rural banks, and cooperatives can then improve formal credit without significantly reducing informal credit. Hence, the government needs to encourage bank account ownership and facilitate access to financial institutions in order to promote formal credit and reduce informal credit.

Applying Convolutional-GRU for Term Deposit Likelihood Prediction

Banks are normally offered two kinds of deposit accounts. It consists of deposits like current/saving account and term deposits like fixed or recurring deposits.For enhancing the maximized profit from bank as well as customer perspective, term deposit can accelerate uplifting of finance fields. This paper focuses on likelihood of term deposit subscription taken by the customers. Bank campaign efforts and customer detail analysis caninfluence term deposit subscription chances. An automated system is approached in this paper that works towards prediction of term deposit investment possibilities in advance. This paper proposes deep learning based hybrid model that stacks Convolutional layers and Recurrent Neural Network (RNN) layers as predictive model. For RNN, Gated Recurrent Unit (GRU) is employed. The proposed predictive model is later compared with other benchmark classifiers such as k-Nearest Neighbor (k-NN), Decision tree classifier (DT), and Multi-layer perceptron classifier (MLP). Experimental study concludesthat proposed model attainsan accuracy of 89.59% and MSE of 0.1041 which outperform wellother baseline models.

On Restoration of the Investment Income at a Military Serviceman`s Personal Saving Account in Case of Their Undue Inclusion into the Register of Participants of the Savings and Mortgage System

In accordance with Federal law No. 117-FZ of August 20, 2004 «On the accumulative mortgage system of housing provision for military personnel», in the modern period of time, it has already allowed many military personnel to purchase their own housing. However, like any public relations, the exercise of their right to housing has a number of issues, including those related to late registration in the register of participants in the accumulative mortgage system, which in turn causes a decrease in funds on the registered savings account.

The Innovations of Hibahasan Instrument of Islamic Finance and Islamic Estate Management in MalaysiaAhmad Khilmy Abdul Rahim

The application of hibah as an instrument in estate management is gaining popularity among the Muslim community in Malaysia. “Hibah is a unilateral contract” that elevate welfare and charity. The Islamic financial institutions in Malaysia, including Islamic banks as well as Islamic wealth institutions apply varities of hibah instruments in the products accessible by them. Hibah is a cooperating shariah contract in the Malaysia‟s Islamic banking and financial framework. The aim is to incentivize clients for storing their cash into the institution as well as remunerate for clients to pay their financing by agreeing planned. The use of hibah is based on the stated fundamentals and objectives of the “Shariah Advisory Council (SAC) of Bank Negara Malaysia”. Nowadays, hibah instrument has been applied in various forms using Islamic financial institutions especially in Malaysia. This article discusses and analyzes in general the application of contemporary forms of hibah such as Trust Hibah (Hibah Amanah), Conditional Hibah (Hibah Mu'allaqah), Hibah with discussion (Hibah Bi al-Thawab), hibah in saving account (Wadiah) and rental (al-Ijarah) accounts and hibah in Takaful benefit.

Applying Convolutional-GRU for Term Deposit Likelihood Prediction

Banks are normally offered two kinds of deposit accounts. It consists of deposits like current/saving account and term deposits like fixed or recurring deposits. For enhancing the maximized profit from bank as well as customer perspective, term deposit can accelerate uplifting of finance fields. This paper focuses on likelihood of term deposit subscription taken by the customers. Bank campaign efforts and customer detail analysis can influence term deposit subscription chances. An automated system is approached in this paper that works towards prediction of term deposit investment possibilities in advance. This paper proposes deep learning based hybrid model that stacks Convolutional layers and Recurrent Neural Network (RNN) layers as predictive model. For RNN, Gated Recurrent Unit (GRU) is employed. The proposed predictive model is later compared with other benchmark classifiers such as k-Nearest Neighbor (k-NN), Decision tree classifier (DT), and Multi-layer perceptron classifier (MLP). Experimental study concludes that proposed model attains an accuracy of 89.59% and MSE of 0.1041 which outperform well other baseline models.