Santoso, Shania Chairunnisa (2026) Pembuatan Sistem Rekomendasi Makanan Berbasis Machine Learning pada Aplikasi Cholestify. Project Report (Praktek Kerja Lapang dan Magang). Fakultas Ilmu Komputer. (Unpublished)
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Abstract
Cholestify app is one of the final learning outcomes of the Bangkit Academy program, a form of implementation of learned skills by addressing real-life problems. Hypercholesterolemia is a significant health problem in Indonesia, with its prevalence continuing to rise and contributing to the risk of heart disease. To help address this issue, the Cholestify app was developed using a machine learning approach. This app implements an embedding-based Neural Collaborative Filtering (NCF) algorithm built using TensorFlow to provide personalized food recommendations tailored to the user's nutritional needs. The app development process included data collection, data preprocessing, and model training using the Adagrad optimizer, with evaluation using precision, recall, and AUC metrics. The evaluation results showed improved model performance with each epoch, indicating the app's ability to provide relevant food recommendations. With features such as cholesterol level evaluation, food recommendations, and daily nutrition recording, this app is expected to support healthy diet management and reduce the risk of complications from hypercholesterolemia.
| Item Type: | Monograph (Project Report (Praktek Kerja Lapang dan Magang)) | ||||||||
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| Subjects: | Q Science > Q Science (General) Q Science > QA Mathematics > QA76.6 Computer Programming Q Science > QA Mathematics > QA76.87 Neural computers |
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| Divisions: | Faculty of Computer Science > Departemen of Information Systems | ||||||||
| Depositing User: | Shania Chairunnisa Santoso | ||||||||
| Date Deposited: | 21 Jul 2026 01:17 | ||||||||
| Last Modified: | 21 Jul 2026 01:17 | ||||||||
| URI: | https://repository.upnjatim.ac.id/id/eprint/56440 |
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