DETEKSI KALORI PADA CITRA MAKANAN DENGAN ALGORITMA SINGLE SHOT MULTIBOX DETECTOR

Authors

  • Fifin ayu puspitasari Universitas putera batam
  • Hotma Pangaribuan

DOI:

https://doi.org/10.33884/comasiejournal.v12i2.9714

Keywords:

food detection, SSD, artificial intelligence, public health, calorie estimation

Abstract

The increasing prevalence of non-communicable diseases such as obesity and diabetes mellitus has become a major public health concern in Indonesia. Uncontrolled food consumption is one of the primary contributing factors to these issues. Therefore, a system is needed to help individuals monitor their calorie intake more effectively. This study aims to develop a food calorie detection system using the Single Shot Multibox Detector (SSD) method. The model is applied to identify and classify food objects with high accuracy. Calorie estimation is performed based on predefined fixed portion rules. The results indicate that the developed system can recognize various types of food in real-time with optimal performance. The implementation of this system is expected to raise public awareness of healthy eating habits and support efforts to prevent non-communicable diseases in Indonesia.

References

Dandi, M., Fauzi Tsp, H., & Rizal, S. (2021). PERANCANGAN APLIKASI PERHITUNGAN NUTRISI PADA MAKANAN BERBASIS ANDROID DENGAN METODE CONVOLUTIONAL NEURAL NETWORK (CNN) THE DESIGN OF NUTRITION CALCULATION APPLICATION FOR ANDROID USING CONVOLUTIONAL NEURAL NETWORK (CNN) METHOD. Bandung. Retrieved from https://openlibrary.telkomuniversity.ac.id/pustaka/files/172246/jurnal_eproc/implementasi-algoritma-yolo-pada-aplikasi-pendeteksi-citra-makanan-berbasis-android.pdf

Darma Udayana, I. P. A. E., & Nugraha, P. G. S. C. (2020). PREDIKSI CITRA MAKANAN MENGGUNAKAN CONVOLUTIONAL NEURAL NETWORK UNTUK MENENTUKAN BESARAN KALORI MAKANAN. Jurnal Teknologi Informasi Dan Komputer, 6(1). https://doi.org/10.36002/jutik.v6i1.1001

Faqih, H., Lesmana, H., & Cahya Putri Utami, B. (2023). SI KALORI: Sistem Pakar Penghitung Jumlah Ideal Kalori Harian Berbasis Mobile. Indonesian Journal on Software Engineering (IJSE), 9(1), 46–54. Retrieved from http://ejournal.bsi.ac.id/ejurnal/index.php/ijse46

Gonzalez, R. C., & Woods, R. E. (2018). Digital image processing 4th edition, global edition.

Goodfellow, I. J., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., … Bengio, Y. (2019). Generative adversarial networks (2014). ArXiv Preprint ArXiv:1406.2661, 1406.

Redmon, J. (2018). Yolov3: An incremental improvement. ArXiv Preprint ArXiv:1804.02767.

Rewasan, M., Fredrik Langi, F. G., Kalesaran, A. F., & Kesehatan Masyarakat Universitas Sam Ratulangi Manado ABSTRAK, F. (2022). Studi Ekologi Obesitas Sentral Dengan Diabetes Melitus Pada Penduduk Usia Di Atas 15 Tahun Di Indonesia. In Jurnal KESMAS (Vol. 11).

Riswanto, R., Ahmad, A., Hazriani, H., & Tribuana, D. (2024). Deteksi Kalori Makanan Tradisional Indonesia Menggunakan Metode Single Shot Multibox Detector (SSD). MALCOM: Indonesian Journal of Machine Learning and Computer Science, 4(3), 819–829. https://doi.org/10.57152/malcom.v4i3.1332

Wardani, N. H. R., Trop, M. K., Nurhayati, S., Afni, A. C. N., Anggraini, N. Y., Kep, M., … Mahendra, N. D. (2023). Kebutuhan Dasar Manusia. Rizmedia Pustaka Indonesia.

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Published

2025-02-03

How to Cite

Fifin ayu puspitasari, & Hotma Pangaribuan. (2025). DETEKSI KALORI PADA CITRA MAKANAN DENGAN ALGORITMA SINGLE SHOT MULTIBOX DETECTOR. Computer and Science Industrial Engineering (COMASIE), 12(2), 91–100. https://doi.org/10.33884/comasiejournal.v12i2.9714