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Training on Basic Mathematics for 12th Grade Students of SMA Pasundan Majalaya in Preparation for the 2024 SNBT Hidayana, Rizki Apriva; Yuningsih, Siti Hadiaty; Syarifudin, Abdul Gazir; Amelia, Rika; Nurkholipah, Nenden Siti
Operations Research: International Conference Series Vol. 5 No. 2 (2024): Operations Research International Conference Series (ORICS), June 2024
Publisher : Indonesian Operations Research Association (IORA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/orics.v5i2.316

Abstract

Basic math training plays an important role in preparing students for the National Selection Based Test (SNBT), which is one of the entry pathways to public universities in Indonesia. This study aims to evaluate the effectiveness of academic ability test training in improving the readiness of XII grade students of Pasundan Majalaya High School to face SNBT 2024. The research method used is descriptive quantitative with a case study approach. The study population was all XII grade students of Pasundan Majalaya High School who participated in the training program. Data were collected through observations and tests conducted before and after the training. Data analysis was conducted to measure the improvement of students' academic ability and readiness. The results showed that the academic proficiency test training implemented at Pasundan Majalaya High School was effective in improving students' pre and post test results. There was a significant increase in proficiency test scores through pre and post test results. In addition, the training also helped students in developing time management skills, problem solving strategies, and critical thinking skills. The findings suggest that structured and comprehensive training can significantly improve students' academic readiness, thus helping them to face SNBT more confidently and competitively. This research is expected to contribute to the preparation of Pasundan Majalaya High School students for college entrance selection.
Modeling of COVID-19 Growth Cases in Bandung Regency and Bandung City Using Vector Autoregression Megantara, Tubagus Robbi; Hidayana, Rizki Apriva; Syarifudin, Abdul Gazir; Amelia, Rika; Nurkholipah, Nenden Siti
International Journal of Global Operations Research Vol. 5 No. 4 (2024): International Journal of Global Operations Research (IJGOR), November 2024
Publisher : iora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/ijgor.v5i4.342

Abstract

COVID-19 is a global health epidemic due to increasing infections and deaths. Indonesia has many confirmed cases with high daily case growth, including the Bandung City and Bandung Regency areas. High mobility between regions can impact the growth of COVID-19 cases. Strategies to prevent the growth of COVID-19 cases need to be carried out by considering the growth of COVID-19 cases in the nearest area. The Vector Autoregression (VAR) model is a forecasting model that can consider geographic impacts. This study aims to model the growth of cases in adjacent areas and have high mobility using the VAR method. The growth of COVID-19 cases in Bandung City and Bandung Regency is integrated into the VAR model to see the impact of each other. The VAR model also considers the impact of case growth in the past on its region's future. Transformation and differencing are carried out on the time series of case growth in each region to achieve time-series stationarity so that the VAR model can be carried out. First-order VAR becomes a model representing the growth of COVID-19 cases in Bandung City and Bandung Regency. The model shows that COVID-19 cases in each region will decrease over time and each region impacts each other. Decreasing cases growth can be caused because people who have been infected and vaccinated have sound immune systems to prevent re-infection. However, prevention still needs to be done to stop the pandemic. Therefore, restrictions on mobility between regions can be used as a strategy to prevent COVID-19 infection.
Forecasting Rice Sales Using Weighted Moving Average Method: Case Study at KAKANG MART GROSIR Bandung Nurkholipah, Nenden Siti; Megantara, Tubagus Robbi; Hidayana, Rizki Apriva
International Journal of Global Operations Research Vol. 6 No. 3 (2025): International Journal of Global Operations Research (IJGOR), August 2025
Publisher : iora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/ijgor.v6i3.395

Abstract

Effective inventory management is critical for retail businesses, and accurate sales forecasting is its cornerstone, especially for staple products like rice. This study aims to forecast the sales of packaged rice at KAKANG MART GROSIR, a major retailer in Bandung, by analyzing its daily sales data. The research utilizes the Weighted Moving Average (WMA) method on primary sales data for six top-selling rice brands collected over a three-month period from March 1 to May 31, 2025. The WMA model, which assigns greater importance to recent observations, was employed to smooth short-term fluctuations and identify underlying sales trends. The analysis revealed highly dynamic and distinct sales patterns: the JM Cianjur brand showed the highest average sales but with significant weekly volatility , the Setrawangi RS brand demonstrated strong and consistent growth to become a market leader , while the Setrawangi DI brand experienced a sharp decline. Furthermore, the BMW brand was found to have remarkably stable and predictable sales , whereas the Lahap and Sedap Wangi brands consistently remained at the lowest sales tier. The findings confirm that the WMA is a valuable tool for identifying diverse sales trajectories, providing actionable insights for developing tailored inventory strategies for each product.
Analysis of Multistability of Financial Risk Chaos Systems and Its Application to Voice Cryptography Yuningsih, SIti Hadiaty; Hidayana, Rizki Apriva; Nurkholipah, Nenden Siti
International Journal of Research in Community Services Vol. 5 No. 3 (2024)
Publisher : Research Collaboration Community (Rescollacom)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijrcs.v5i3.699

Abstract

In the chaos literature, the application of modeling and control of dynamic systems in chaos theory arising in several fields is investigated. In this article we analyze complex financial chaos systems with countries as interest rates, investment demand, and price indices. The proposed chaotic flow's dynamic behavior is examined using phase portraits, eigenvalues, bifurcation diagrams, and Lyapunov exponent spectra. A significant quantity of research on secure communication systems has been published in recent years as a result of the major advancements in communications equipment and encryption techniques. A new voice encryption algorithm design is given using a financial chaos model. An application for voice encryption is conducted using the suggested algorithm, and the outcomes are described.
Empowering High School Students with Software-Based Mathematical Skills for College and Career Readiness Megantara, Tubagus Robbi; Hidayana, Rizki Apriva; Nurkholipah, Nenden Siti; Amelia, Rika; Syarifudin, Abdul Gazir; Mulyo, Lukman Widoyo; Khan, Muhammad Fardeen; Agustin, Nemia
International Journal of Research in Community Services Vol. 6 No. 4 (2025): International Journal of Research in Community Service (IJRCS)
Publisher : Research Collaboration Community (Rescollacom)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijrcs.v6i4.1069

Abstract

In the current data-driven era, data literacy is a critical competency, yet many high school students lack practical training in essential software like Microsoft Excel, creating a significant skills gap. To address this challenge, the Mathematics Study Program at Universitas Kebangsaan Republik Indonesia conducted a community service program designed to empower high school students with foundational data analysis and visualization skills through a structured, hands-on Excel workshop. The program employed a phased approach, beginning with a socialization session for 31 students, followed by an intensive training workshop for a final cohort of 12 students. The workshop was segmented into three progressive modules: Foundations of Data Management, Logical Analysis and Data Interpretation, and Data Visualization. The program's effectiveness was evaluated using qualitative performance-based assessments and a feedback survey to measure changes in skill and confidence. The results indicate that the training was highly successful, demonstrably improving participants' competence and confidence as evidenced by overwhelmingly positive survey feedback. The foundational and data visualization modules were particularly effective, while the module on logical functions was identified as the most significant challenge for students. This initiative not only succeeded in delivering essential digital skills for college and career readiness but also offered valuable pedagogical insights, confirming the effectiveness of hands-on workshops and highlighting areas for refinement in technical education.