Rescollacomm (E-Journals)
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Education Revolution: Leveraging Technology to Improve Learning Quality by 2025
Get PDFThe technological transformation in education in 2025 has had a significant impact on the way we teach and learn. The use of artificial intelligence (AI) and learning analytics enables a more personalized, interactive, and adaptive learning experience. AI helps provide rapid feedback and adapts learning materials to students’ needs, while learning analytics enables real-time monitoring of student progress. Despite the many benefits that can be gained, the main challenges faced are the digital divide between urban and rural areas, limited infrastructure, and issues of training for educators and protection of students’ personal data. Therefore, investment in infrastructure, training for educators, and development of data protection policies are crucial to ensure effective implementation of technology in education. Technology can play a major role in creating a more inclusive and adaptive education, provided that the existing challenges can be overcome
Comparison of Poisson and Negative Binomial Regression Models in Identifying Factors Influencing Covid-19 Deaths in Indonesia.
Get PDFThis research compares Poisson Regression and Generalized Negative Binomial (GNB) Regression to underscore the factors that influence the growth of COVID-19 deaths in Indonesia. Count data such as mortality cases often violates the Poisson assumption of equidispersion (null mean equals variance) causing overdispersion. The GNB model is suggested as a remedy for overdispersed data crime prevention has become increasingly necessary for systematic development because secondary data from the Indonesian government has included dependable variables such as mortality rates for people aged over 60, diabetes mellitus, heart disease, lung disease, healthcare worker percentages, referral hospitals, and the population. The Poisson Regression reported R² of 87.67% and experienced overdispersion (θ₁ = 356.27, θ₂ = 417,597). The GNB model, in contrast, with a lower AIC (499.5566), overtook Poisson. Important factors that had significant impact on both models were mortality rates for individuals over 60, diabetes mellitus, healthcare workers, and referral hospitals, whereas heart and lung disease mortality rates were the ones that were not material. The GNB model had a better fit and tackled the issues of overdispersion in the Poisson Regression
The Relationship between Self-Efficacy, Resilience, Social Support, and Subjective Well-being among Female Conditional Cash Transfer Beneficiaries in Panggungharjo Village, Indonesia
Get PDFUnderstanding the psychosocial factors shaping the subjective well-being of female Program Keluarga Harapan (PKH), a conditional cash transfer program in Indonesia, beneficiaries is fundamental to evaluating intervention success beyond economic metrics. The numerous persistent challenges faced by disadvantaged women in Indonesia have been shown to influence their assessments of well-being. This paper aims to investigate the relationship between self-efficacy, resilience, social support, and subjective well-being. This study utilizes a quantitative approach, employing a survey method and a purposive sampling technique for 198 female beneficiaries of the PKH conditional cash transfer in Panggungharjo Village, Yogyakarta Province, Indonesia. Data analysis was conducted using the Somers’d correlation test using SPSS version 29. The results indicate that self-efficacy (dyx = 0.131; p>0.05) is not significantly correlated with subjective well-being. In contrast, the finding reveals that resilience (dyx = 0.257; p<0.001) and social support (dyx = 0.219; p<0.05) are positively and significantly correlated with subjective well-being. These findings confirm that resilience and social support play a crucial role in enhancing subjective well-being. These findings underscore the importance of optimizing interventions that can strengthen resilience and social support, as well as exploring additional psychological variables to understand the psychosocial dynamics of subjective well-being. This research contributes to the literature on the psychosocial condition of female conditional cash transfer beneficiaries in Indonesia, while also serving as a basis for policy formulation aimed at reducing poverty levels in Indonesia
The Effect of Double Date Discounts on Sales Levels In E-Commerce Shopee (Case Study on Students of Padjadjaran University in Jatinangor)
Get PDFThis study aims to analyze the impact of double date sale discounts on sales levels on the Shopee e-commerce platform, focusing on students from Universitas Padjadjaran in Jatinangor, who are primarily from the millennial and Generation Z cohorts. The method used is simple linear regression, linking discount variables to sales. Additionally, the study conducts classical assumption testing to ensure the models validity and sensitivity analysis to assess the effect of parameter changes on the predicted outcomes. The results show that double date sale discounts significantly influence sales, with the double date sale coefficient (eta_1) being highly sensitive to changes. The regression model yields a low MSE, indicating good prediction accuracy. While changes in the intercept (eta_0) also affect the predictions, the impact is smaller compared to changes in the double date sale coefficient
Investment Portfolio Optimization on Technology Sector Stocks Using Mean-Variance Model with Asset-Liability Based on ARIMA-GARCH Approach
Get PDFIn this era of rapid technological advancement, various sectors are experiencing changes, one of which is investment. Investors are starting to turn their attention to technology sector stocks as new investment targets. However, investments are inherently linked to return and risk levels and stock prices can be highly volatile. Therefore, forming an optimal investment portfolio is very important to achieve a balance between return and risk. In addition, coping with volatile stocks is also very important. The ARIMA-GARCH time series model is a method that can be used to deal with such volatility. A popular strategy for portfolio optimization is to use the Mean-Variance model, also known as the Markowitz model. This study aims to form an optimal portfolio consisting of five technology sector stocks in Indonesia with the codes AXIO, DIVA, EDGE, MCAS, and CASH using the Mean-Variance model with assets-liabilities equipped with the ARIMA-GARCH approach. Based on the results of the study, the optimal portfolio is obtained with the composition of each weight is 23.16% of the capital allocated to AXIO; 2.95% for DIVA; 56.48% for EDGE; 6.36% for MCAS; and 11.05% for CASH. The weight allocation composition can generate a portfolio return of 0.0066 and a variance (risk) return of 0.0082
Investment Portfolio Optimization Using Genetic Algorithm on Infrastructure Sector Stocks Based on the Single Index Model
Get PDFInvestment is a strategic step in managing assets to gain profits in the future by allocating some funds in the present. However, behind the promising potential returns, investment also contains risks that cannot be ignored. One way to reduce the level of risk in investing is to implement a portfolio diversification strategy, which is to form an optimal portfolio by allocating investments to various stocks. This study aims to identify the stocks that form the optimal portfolio, determine the optimal weight of each stock, and calculate the expected return and risk of the portfolio. The portfolio optimization process is carried out using Genetic Algorithm, with the calculation of expected return and risk using the Single Index Model (SIM) approach. The data used includes data on stocks in the infrastructure sector for the period July 1, 2023 to June 30, 2024. The results showed that there were six stocks selected in forming the optimal portfolio with the weight of each stock: PGEO 15.0023%, ISAT 32.1522%, GMFI 4.7822%, EXCL 15.3236%, JSMR 29.7379, and OASA 3.0018%. This optimal portfolio provides an expected return of 0.1167% with a portfolio risk of 0.0152%
Stock Investment Portfolio Optimization Using Mean-Variance Model Based on Stock Price Prediction with Long-Short Term Memory
Get PDFStock investment in the technology sector in Indonesia offers high potential returns. However, like any other investment instruments, the associated risks cannot be overlooked. Therefore, an appropriate portfolio optimization strategy is needed to enable investors to achieve optimal returns while managing risk. In this study, the author combines stock price prediction approaches with portfolio optimization methods to construct an efficient portfolio. The Long-Short Term Memory (LSTM) model is used to predict daily closing stock prices, with model performance evaluated using Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE) metrics. An optimal LSTM model is obtained with a batch size hyperparameter of 16 for ISAT, MTDL, MLPT, and EDGE stocks, and a batch size of 32 for DCII stock. For all stocks, the average prediction error from the actual values falls within the range of 1.53% ≤ MAPE ≤ 3.52%. The optimal portfolio is constructed using the Mean-Variance risk aversion model to maximize expected returns while considering risk. The resulting optimal portfolio composition consists of a weight allocation of 19.7% for ISAT stock, 36.8% for MTDL stock, 34.8% for MLPT stock, 3.6% for EDGE stock, and 15% for DCII stock. This portfolio yields an expected portfolio return of 0.001249 and a portfolio variance of 0.000311
Promoting the Consumption of Fish-Based Processed Products as A Strategy to Improve Children\u27s Nutrition in Majakerta Village, Majalaya District, Bandung Regency
Get PDFEfforts to increase fish consumption offer numerous benefits, not only enhancing intelligence but also boosting the fisheries industry. Currently, stunting remains a concerning issue, and data indicates that fish consumption is not evenly distributed across Indonesia. This represents one of the health problems that serves as an indicator of the health and well-being of a community. One of the themes of this community service program (or also known as PPM in Indonesia) is raising awareness about improving children\u27s nutrition among the residents of Majakerta Village, Majalaya District, Bandung Regency. The implementation of the program is conducted in collaboration with student community service (or also known as KKN in Indonesia) activities. The primary objective of this program is to improve children\u27s nutrition through the promotion of fish-based processed food consumption and to educate mothers in Majalaya District about recognizing stunting symptoms and addressing them. The main target of this program is children aged 612 years. The method used in this awareness campaign includes educational games about fish and fish-based processed food to make the material easier for elementary school children to understand. Additionally, one type of fish-based processed food is distributed for children to taste directly, aiming to increase their interest in fish consumption. The results achieved include improved knowledge about the importance of eating fish due to its many health benefits
Community Empowerment through Pharmaceutical Technology: Post-Harvest Rhizome Utilization and Product Packaging Skills Enhancement at Kebun Merdesa, Cikarawang Village, Bogor Regency
Get PDFThis study presents a community service initiative aimed at empowering a rural community in Indonesia through training in the post-harvest utilisation of rhizomes using pharmaceutical technology, packaging design, and digital marketing. The project involved 20 participants from the Kebun Merdesa community and was conducted by a team of three lecturers and seven students from the University of Pakuan. The training was divided into several stages, including the production of herbal tea, herbal drinks, and kitchen spices, followed by packaging design using the Canva and Pacdora applications and digital marketing using social media platforms and the Buffer application. The results showed significant improvements in the participants\u27 knowledge and skills across all areas, with increases ranging from 31% to 34% in rhizome processing, herbal product manufacturing, packaging design, and digital promotion. These findings align with previous studies that have highlighted the effectiveness of targeted training programs in enhancing participants’ competency in specialised skill areas. The integration of technical production, innovative packaging, and digital marketing has been shown to significantly impacts the economic resilience and competitiveness of small enterprises in rural areas. This initiative demonstrates a practical model for rural community empowerment that can be replicated in other agricultural areas with similar resources and challenges, supporting the Sustainable Development Goals of decent work, economic growth, and responsible consumption and production. The success of this program provides a strong argument for policy support and funding for community-based pharmaceutical product development, contributing to the resilience of rural economies against market fluctuations and climate-related agricultural risk
Coastal Ethnomathematics in Geometry Learning: A Study at Senior High Schools in Panimbang Regency
Get PDFThis study examines the integration of coastal ethnomathematics into geometry learning in senior high schools in Panimbang Regency, Indonesia. Ethnomathematics merges local cultural elements with mathematical concepts, providing a contextualized approach to teaching. The research focuses on how coastal culture, such as fishing boat designs and net patterns, can be used to teach geometric concepts like symmetry, angles, and shapes. A pretest-posttest experimental design was conducted with 30 Grade X students. Initially, students were taught using a traditional method, followed by a pretest to assess their understanding. They then learned geometry through coastal cultural examples, with a posttest measuring their progress. The average test score improved from 61.4 to 77.2, indicating a significant enhancement in learning outcomes. A questionnaire revealed that students found the ethnomathematics approach made geometry more relatable, easier to grasp, and increased their motivation. The study concludes that integrating ethnomathematics into geometry lessons not only improves students\u27 understanding and engagement but also fosters a greater appreciation for their local cultur