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All Journal Jurnal Informatika Jurnal Teknik Proceedings of KNASTIK e-Jurnal Eco-Teknologi UWIKA (eJETU) Prosiding Seminar Nasional Sains Dan Teknologi Fakultas Teknik Jurnal Teknologi Informasi dan Ilmu Komputer Proceeding SENDI_U Proceeding of the Electrical Engineering Computer Science and Informatics Jurnal Nasional Komputasi dan Teknologi Informasi Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Abdimas Toddopuli: Jurnal Pengabdian Pada Masyarakat JATI (Jurnal Mahasiswa Teknik Informatika) GUYUB: Journal of Community Engagement Journal of Applied Data Sciences IJECS: Indonesian Journal of Empowerment and Community Services Journal Software, Hardware and Information Technology E-Jurnal SPIRIT PRO PATRIA Jurnal Pengabdian Masyarakat untuk Negeri (UN-PENMAS) Jurnal Pengabdian Mandiri Prosiding SNPBS (Seminar Nasional Pendidikan Biologi dan Saintek) Asia Pacific Journal of Management and Education Indonesian Journal of Society Development (IJSD) JOINCS (Journal of Informatics, Network, and Computer Science) Jurnal Sistem Cerdas dan Rekayasa Seminar Nasional Ilmu Terapan Prosiding Seminar Nasional Teknologi Informasi dan Bisnis Prosiding Seminar Nasional Pengabdian Masyarakat Seminar Nasional Riset dan Teknologi (SEMNAS RISTEK)
Yulius Hari
Teknik Informatika, Universitas Widya Kartika Surabaya
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Journal : Journal of Applied Data Sciences

 1 
Assessing Novice Voter Resilience on Disinformation During Indonesia Elections 2024 with Naïve Bayes Classifier Hari, Yulius; Yanggah, Minny Elisa; Paramita, Adi Suryaputra
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

Abstract

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 Hari, Yulius; Yanggah, Minny Elisa; Budiman, Arief
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

Abstract

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.
Co-Authors - Darmanto ., Darmanto Adi Suryaputra Paramita Agus Prayitno Alexandra Graciene Michaeline Dharmahusada Alfajriyah, Aimmatul Ummah Andre Saputra, Nova Arief Budiman Arnoldus Primus Setwin Windiarjo Budhi, Robby Kurniawan Budi Hermawan Budi Hermawan Churota'ayun, Elisa Darmanto ., Darmanto Darmanto Darmanto Darmanto Darmanto Darmanto Darmanto Darmanto, D Dhaniswara, Erwin Endang Setyawati Erwin R. Tan Felensia Chandra Florencia Irena Forno, Adrian Christian Fransisca Hanita Rusgowanto Fransiska Kurniawati Hakiki, M. Taufik Henry, William hidayat, dwi taufik Hizkia Pesik, Yosafat Ho, Abraham Cahyadi Imam Safawi Ahmad, Imam Safawi Indra Budi Trisno Johan William Tanusaputra Kambey, Abner Christian Kevin Brian Kevin Winata Tanjung Lenny Endang Lenny Endang Lily Puspa Dewi Majid, Bimantara Maria Apriana Melvie Paramitha Melvie Paramitha Minny Elisa Yanggah Mohamad Atok Murpin Josua Sembiring Muslichah Erma Widiana Nico, Abed Novan, Andrean Pratama, Christian Alexander Ririn Dina Mutfianti Robby Kurniawan Budhi Roger Jeremy Safira, Safira Santi, Chitra Saputri, Prilyandari Dina Sholichuddin Al Ayyubi Putra Ary Siswono, Galuh Oktavia Soehardjoepri, Soehardjoepri Surianto, Ratna Susan Uce Indahyanti Ulil Azmi Vajra Vidya Kusala Widianto Yonatan, Widianto Widyaningrum, Mahmudah Enny Windiarjo, Arnoldus Primus Setwin Yen Vania Yoga Alif Kurnia Utama Yonathan Widianto Yulia Setyarini, Yulia