Application of Design Thinking on BPD Bali Mobile Banking

Kadek Dwi Natasya Pradnyani — 2024-05-27

The banking company, which is one of the driving factors of economic growth in the country, is continuously innovating for its customers by leveraging technological advancements. This development is also utilized by Bank BPD Bali through the launch of BPD Bali Mobile Banking. When developing this, considering the functionality, usability, needs, and user comfort of the application is crucial, including creating a good and attractive UI/UX design to ensure user satisfaction. In the evaluation of BPD Bali's mobile banking, the obtained SUS score is 57.19. Therefore, a redesign of BPD Bali's mobile banking using Design Thinking is necessary. This method allows for true empathy with the target users and effectively developing solutions for user problems and needs. By going through 5 stages, Empathize, Define, Ideate, Prototype, and Test, the final result obtained is a prototype recommendation, which has been tested using SUS. In the prototype testing, a SUS score of 79.69 was obtained, which can be interpreted as users being able to accept the prototype recommendation.

Prediction of The Islamic Stock Price Index and Risk of Loss Using The Long Short-Term Memory (LSTM) and Value At Risk (VaR)

Ikbar Athallah Taufik — 2024-05-27

Investment aims to increase the value of capital or earn additional income through asset growth, dividends or profits. One investment instrument that is in demand, especially among the Muslim community, is Islamic stocks, which are in accordance with Islamic principles that focus on a healthy economy. This research is focused on predicting Islamic stock prices using the Long Short-Term Memory (LSTM) method and measuring risk with Value at Risk (VaR) using the Cornish-Fisher Expansion (ECF) method. Stock price data from the food sector (PT Indofood), technology sector (Telkom Indonesia), and construction sector (Indocement) for the period 2018-2023 were analyzed. The results show that the ADAM model provides the best performance with the lowest prediction error rates for INTP and TLKM stocks (around 1.22%, 1.98%, and 1.41%). In addition, the SGD model shows limitations in accurate predictions with an error rate above 12%. VaR analysis reveals a slightly higher level of risk in INTP stocks, with a VaR value of around 2.85% at the 95% confidence level. Meanwhile, TLKM stock shows a lower level of risk, with a VaR of around 2.25% at the same confidence level. An in-depth understanding of the risk and growth characteristics of each stock, as well as the selection of the optimization model, are key in making wise investment decisions.

IJDASEA (International Journal of Data Science, Engineering, and Analytics)

Application of Design Thinking on BPD Bali Mobile Banking

Prediction of The Islamic Stock Price Index and Risk of Loss Using The Long Short-Term Memory (LSTM) and Value At Risk (VaR)