Murniyati Murniyati
Universitas Bina Sarana Informatika

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Penerapan Manajemen Risiko pada Tingkat Efisiensi Keuangan di Bank DKI Jakarta Saridawati Saridawati; Murniyati Murniyati; Ratih Hastasari; Suharini Suharini
Owner : Riset dan Jurnal Akuntansi Vol. 5 No. 2 (2021): Article Research Volume 5 Number 2, Agustus 2021
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/owner.v5i2.425

Abstract

Efficiency is one measure of bank performance. The efficiency of a bank is influenced by the way management manages risk. Financial services authority regulation number 18 /pojk.03/2016 issued by Bank Indonesia which requires every bank in Indonesia to form a risk management team. Risk management problems in the banking world are related to the losses they experience, and Regional Development Banks are expected to be able to detect maximum losses that may arise in the future. This team is obliged to control various aspects of risk management in each bank and observe the impact of risk management implementation. This study aims to determine the efficiency level of conventional banking at PT Bank Pembangunan Daerah Jawa Tengah and the effect of financing risk, operational risk and liquidity risk on the efficiency level. Efficiency is measured by the method of Operating Expenses from Operating Income. The data used as the object of this research is Bank DKI Jakarta for the 2015-2020 period. The level of influence of the variables X1, X2, X3 on Y on the determinant coefficient (R2) shows the Adjusted R Square number of 0.359 or 35.9% which means that the variation in efficiency level can be explained by financing risk, operational risk and liquidity risk, the remaining 64.1% can be explained from other variables outside, for previous related studies there is no similarity in the influence of independent (x) and dependent (Y) values, because of differences in values ??generated from SPSS processing data. Based on the results of statistical tests and discussion analysis, it is known that financing risk, operational risk, liquidity risk simultaneously have no effect on the level of efficiency and only financing risk has a significant positive effect on the level of efficiency at PT Bank DKI Jakarta.
HYPER-PERSONALIZATION IN MARKETING: REDEFINING CONSUMER EXPECTATIONS IN THE AGE OF BIG DATA Bilgah Bilgah; Suripah Suripah; Murniyati Murniyati; Eka Putri Handayani
Journal of Economic, Bussines and Accounting (COSTING) Vol. 7 No. 6 (2024): COSTING : Journal of Economic, Bussines and Accounting
Publisher : Institut Penelitian Matematika, Komputer, Keperawatan, Pendidikan dan Ekonomi (IPM2KPE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31539/costing.v7i6.14288

Abstract

This research examines the impact of hyper-personalization and big data usage on consumer expectations and customer engagement within the context of the Spotify platform. Utilizing a quantitative research design, data were collected from 150 students at the Faculty of Economics and Business, Bina Sarana Informatika University, through a structured questionnaire. The analysis employed Smart PLS to evaluate the relationships between the variables, with consumer expectations as the dependent variable, hyper-personalization and big data usage as independent variables, and customer engagement as an intervening variable. The findings reveal that while big data usage significantly enhances customer engagement, its direct influence on consumer expectations is negligible. Conversely, hyper-personalization demonstrates a strong positive effect on both consumer expectations and customer engagement. Furthermore, customer engagement positively impacts consumer expectations, indicating that increased interaction with personalized content elevates user satisfaction. These results suggest that marketers should focus on implementing effective hyper-personalization strategies to optimize consumer experiences and foster brand loyalty in the competitive digital music streaming landscape. This study contributes valuable insights into consumer behavior, emphasizing the essential role of data-driven personalization in shaping user expectations and engagement.