Garuda - Garba Rujukan Digital

Community Service on Implementing Learning Media as Support Technology for Neurodivergent Children Community in Surabaya Melvie Paramitha; Yulius Hari; Minny Elisa Yanggah; Chitra Santi
Asia Pacific Journal of Management and Education (APJME) Vol 7, No 2 (2024): July 2024
Publisher : AIBPM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32535/apjme.v7i2.3359

Neurodivergent children may present with conditions such as autism spectrum disorder (ASD), attention deficit hyperactivity disorder (ADHD), dyslexia, or other learning differences. These children often face challenges in communication, social interaction, and academic performance, necessitating tailored support within educational settings. This community service program partners with ELMO, a community for neurodivergent children. The program's goals are twofold: to develop assistive learning media in the form of eLearning modules, and to facilitate technology transfer to ensure its sustainability. The Asset Based Community Development (ABCD) technique guides the program's methodology. Information gathering utilizes questionnaires and focus group discussions to tailor the program to the specific needs of neurodivergent students. The results have demonstrated a positive impact, satisfying both our partner organization and the parents of neurodivergent children who can now track their children's progress more effectively. The positive impact on learning and parental tracking highlights the potential of such collaborations to improve educational equity for neurodivergent students. Future efforts can focus on expanding the modules and promoting wider adoption to reach more children.

Model Integration of Information Technology in Optimizing the Food Supply Chain of the Free Nutritious Meal (MBG) Program to Reduce Food Waste Yulius Hari; Minny Elisa Yanggah; Arief Budiman
Journal of Applied Data Sciences Vol 7, No 1: January 2026
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v7i1.1039

The Free Nutritious Meal Program in Surabaya is a major government initiative designed to improve child nutrition and reduce hunger among schoolchildren from low-income families. Despite its importance, the program faces significant challenges of food loss and waste due to inefficiencies in transportation, storage, and demand matching. This study introduces a Smart MBG Cloud Platform and applies a linear programming model to optimize the program’s supply chain under two operational scenarios: a baseline system without Information Technology (IT) support and an IT-enhanced system integrating route optimization and digital inventory monitoring. Simulation results reveal substantial efficiency gains in the IT-integrated model. This study was conducted using a mixed-method approach involving samples from schools as beneficiaries and the Nutrition Fulfillment Service Unit as providers of free nutritious meals. Using simulation data from five kitchens and ten schools and conducting 50 stochastic replications, the IT-enhanced model achieved a 28% reduction in transportation cost and the total objective value declined by 22%, compared to without IT support scenario. These results demonstrate that incorporating digital route planning and inventory monitoring not only reduces operational expenses but also mitigates organic waste, ensuring fresher meal delivery and supporting sustainability targets. These improvements highlight the potential of digital tools to minimize inefficiencies, ensure fresher meal delivery, and strengthen the nutritional impact of the program. Beyond operational savings, the IT-based model contributes to reduced organic waste generation and aligns with broader sustainability goals. The findings provide empirical evidence that digital transformation can significantly enhance the performance of public food programs and offer practical insights for policymakers to replicate these strategies in similar urban initiatives.

Assessing Novice Voter Resilience on Disinformation During Indonesia Elections 2024 with Naïve Bayes Classifier Yulius Hari; Minny Elisa Yanggah; Adi Suryaputra Paramita
Journal of Applied Data Sciences Vol 6, No 1: JANUARY 2025
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v6i1.489

With the rise of social media platforms, the spread of fake news has become a significant concern. During the 2024 presidential election is dominated with novice voters, who are exposed to a lot of news from social media. As first-time voters, they get a lot of information and news exposure mainly from social media. This is also exacerbated by the fact that influencers are used to lead opinions. This research tries to measure the resilience of novice voters in dealing with hoax news compared with Naïve Bayes classifier to assessing the news. The purpose of this research is so that novice voters aware and are not easily polarized to prevent national disintegration due to disinformation and hoax news. Subsequently, this research also tries to develop a database of content and categories for hoax news from beginner voter data with a classification model. Data collection was carried out offline and online with interviews and questionnaires conducted with a total of 283 respondents from two private universities in East Java and came from various study programs. From the data, a classification approach using the naïve Bayes method was also built to help recommend a category whether this news is a hoax or news that can be verified. From the results of this study, it can also be concluded that the classification model with Naïve Bayes has a very good accuracy of up to 90.303% capable of categorizing a news story whether it is a hoax, dubious news, or valid news. In contrast, this study shows that the average accuracy of first-time voters is only 29.68%, which means that they are very vulnerable to hoax news, due to the many perceptions and assumptions in public comments that make views biased.

Model Integration of Information Technology in Optimizing the Food Supply Chain of the Free Nutritious Meal (MBG) Program to Reduce Food Waste Yulius Hari; Minny Elisa Yanggah; Arief Budiman
Journal of Applied Data Sciences Vol 7, No 1: January 2026
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v7i1.1039

The Free Nutritious Meal Program in Surabaya is a major government initiative designed to improve child nutrition and reduce hunger among schoolchildren from low-income families. Despite its importance, the program faces significant challenges of food loss and waste due to inefficiencies in transportation, storage, and demand matching. This study introduces a Smart MBG Cloud Platform and applies a linear programming model to optimize the program’s supply chain under two operational scenarios: a baseline system without Information Technology (IT) support and an IT-enhanced system integrating route optimization and digital inventory monitoring. Simulation results reveal substantial efficiency gains in the IT-integrated model. This study was conducted using a mixed-method approach involving samples from schools as beneficiaries and the Nutrition Fulfillment Service Unit as providers of free nutritious meals. Using simulation data from five kitchens and ten schools and conducting 50 stochastic replications, the IT-enhanced model achieved a 28% reduction in transportation cost and the total objective value declined by 22%, compared to without IT support scenario. These results demonstrate that incorporating digital route planning and inventory monitoring not only reduces operational expenses but also mitigates organic waste, ensuring fresher meal delivery and supporting sustainability targets. These improvements highlight the potential of digital tools to minimize inefficiencies, ensure fresher meal delivery, and strengthen the nutritional impact of the program. Beyond operational savings, the IT-based model contributes to reduced organic waste generation and aligns with broader sustainability goals. The findings provide empirical evidence that digital transformation can significantly enhance the performance of public food programs and offer practical insights for policymakers to replicate these strategies in similar urban initiatives.

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