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All Journal JOURNAL OF SCIENCE AND SOCIAL RESEARCH Journal of Computer Science and Research Journal of Technology and Computer (JOTECHCOM)
Aprilia, Katharina Tyas
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Library & Information Science Social Sciences

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Optimization of Nutritional Meal Allocation Using the Greedy Algorithm : A Data – Driven Approach for Food Security in Indonesia Irwansyah Sitorus; Aprilia, Katharina Tyas; Muhammad Rasyid Ridha; Ricky Martin Ginting
Journal of Computer Science and Research (JoCoSiR) Vol. 2 No. 4 (2024): October: Artificial Intelligence
Publisher : Asosiasi Perguruan Tinggi Informatika dan Ilmu Komputer (APTIKOM) Provinsi Sumatera Utara

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Abstract

Food security and nutrition programs play a crucial role in improving public welfare, particularly in developing countries such as Indonesia. Efficient allocation of limited government resources to regions most in need remains a key challenge in reducing poverty and malnutrition. This study applies the Greedy Algorithm as a computational optimization method to determine the most effective and equitable distribution of nutritional meal program budgets cross Indonesian provinces. The algorithm prioritizes provinces with higher poverty rates and greater nutritional needs while ensuring that the total expenditure does not exceed the national budget constraint. By employing a data-driven approach and calculating the value-to-cost ratio for each province, the algorithm selects allocations that yield the maximum nutritional impact per unit of cost. The results indicate that the Greedy-based allocation model improves efficiency by approximately 18–25% compared to traditional allocation methods. This approach offers a transparent, adaptable, and computationally efficient framework that can support policymakers in enhancing food security, promoting social equity, and advancing sustainable development goals.
Comparison of Random Forest and Naïve Bayes Classifier Methods for Monkeypox Classification Aprilia, Katharina Tyas; Sitorus, Irwansyah Putera; Ridha, Muhammad Rasyid; Novelan, Muhammad Syahputra
Journal of Technology and Computer Vol. 3 No. 1 (2026): February 2026 - Journal of Technology and Computer
Publisher : PT. Technology Laboratories Indonesia (TechnoLabs)

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Monkey Pox is a disease caused by a virus with the genus orthopoxvirus that can infect humans. The initial symptoms of this disease are the appearance of lumps due to swollen lymph nodes, muscle pain, fever, feeling tired and weak. Although similar to Chickenpox, Monkey Pox is clinically difficult to distinguish from other smallpox diseases. This study aims to classify Monkey Pox disease using the "Monkey-Pox PATIENTS Dataset". Classification of Monkey Pox disease is done using Random Forest and Naïve Bayes methods. Random Forest produces higher accuracy than Naïve Bayes in classifying Monkey Pox disease, which is 69.24% with a k-fold value of 5 and the number of trees 64 using an unbalanced dataset with 6 attributes. While Naïve Bayes produces an accuracy of 68.56% using a dataset without balancing with 8 attributes (k-fold=5, kernel=Gaussian) and 9 attributes (k-fold=3 and 10, kernel=Gaussian).
ANALISIS PERSEPSI MAHASISWA PASCASARJANA TERHADAP PENGGUNAAN CHATGPT DALAM PENULISAN KARYA ILMIAH DITINJAU DARI ETIKA AKADEMIK Ridha, Muhammad Rasyid; Sitorus, Irwansyah Putera; Aprilia, Katharina Tyas; Amin, Muhammad
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 9, No 1 (2026): February 2026
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v9i1.5824

Abstract

Abstract: The development of artificial intelligence, particularly generative Artificial Intelligence (AI) such as ChatGPT, has brought significant changes to the world of higher education. ChatGPT, as a form of intelligent system, is utilized by postgraduate students to support scientific writing. This study aims to analyze postgraduate students' perceptions of the use of ChatGPT in scientific writing and to review them from an academic ethics perspective. The research method used was a quantitative descriptive survey approach. Data were collected through a Likert-scale-based questionnaire distributed to postgraduate students who had used ChatGPT in academic activities. Data analysis was conducted using descriptive statistics to illustrate the trends in respondents' perceptions. The results show that ChatGPT is perceived to provide convenience and benefits in assisting the process of scientific writing, but also raises concerns regarding potential violations of academic ethics if used without clear boundaries. Therefore, an understanding and ethical guidelines are needed for the use of ChatGPT in higher education environments. Keyword: ChatGPT; Intelligent Systems; Academic Ethics; Graduate Students; Generative AI Abstrak: Perkembangan kecerdasan buatan, khususnya Artificial Intelligence (AI) generatif seperti ChatGPT, telah membawa perubahan signifikan dalam dunia pendidikan tinggi. ChatGPT sebagai salah satu bentuk sistem cerdas dimanfaatkan oleh mahasiswa pascasarjana dalam mendukung penulisan karya ilmiah. Penelitian ini bertujuan untuk menganalisis persepsi mahasiswa pascasarjana terhadap penggunaan ChatGPT dalam penulisan karya ilmiah serta meninjaunya dari perspektif etika akademik. Metode penelitian yang digunakan adalah kuantitatif deskriptif dengan pendekatan survei. Data dikumpulkan melalui kuesioner berbasis skala Likert yang disebarkan kepada mahasiswa pascasarjana yang pernah menggunakan ChatGPT dalam kegiatan akademik. Analisis data dilakukan menggunakan statistik deskriptif untuk menggambarkan kecenderungan persepsi responden. Hasil penelitian menunjukkan bahwa ChatGPT dipersepsikan memberikan kemudahan dan manfaat dalam membantu proses penulisan karya ilmiah, namun juga menimbulkan kekhawatiran terkait potensi pelanggaran etika akademik apabila digunakan tanpa batasan yang jelas. Oleh karena itu, diperlukan pemahaman dan pedoman etis dalam pemanfaatan ChatGPT di lingkungan pendidikan tinggi. Kata kunci: ChatGPT, Sistem Cerdas, Etika Akademik, Kata kunci: ChatGPT, Sistem Cerdas, Etika Akademik, Mahasiswa Pascasarjana, AI Generatif
Co-Authors Fachry Abda El Rahman Irwansyah Sitorus Muhammad Amin Muhammad Rasyid Ridha Muhammad Syahputra Novelan Ricky Martin Ginting Sitorus, Irwansyah Putera