Penggunaan Artificial Intelligence dalam Klasifikasi Kandungan Gula pada Minuman Berpemanis

Yulita Sirinti Pongtambing; Rasyad Bimasatya; Eliyah Acantha Manapa Sampetoding

doi:10.59581/jusiik-widyakarya.v3i1.4386

Authors

Yulita Sirinti Pongtambing Universitas Negeri Makassar
Rasyad Bimasatya Universitas Hasanuddin
Eliyah Acantha Manapa Sampetoding Universitas Hasanuddin

DOI:

https://doi.org/10.59581/jusiik-widyakarya.v3i1.4386

Keywords:

Artificial intelligence, sugar content classification, sweetened drinks

Abstract

Excessive sugar consumption has become a serious public health problem. Increasing patterns of food and drink consumption in line with changes in modern lifestyles have contributed to an increase in the prevalence of non-communicable diseases such as obesity, type 2 diabetes and cardiovascular disorders. This study analyzes and analyzes the use of Artificial Intelligence (AI), especially Deep Learning techniques and Neural Network algorithms, in the classification of sugar content in sweetened drinks. The Systematic Literature Review (SLR) method was used to filter relevant studies published between 2020-2024. The study results show that AI is able to provide more efficient and accurate solutions than manual methods. However, although the literature results show great potential, the application of AI in sugar content classification still requires further empirical research. This study emphasizes the importance of developing AI models tailored to the characteristics of sweetened drinks to support consumer decision making regarding healthier drink choices.

References

Putri Dewi, S. (2024). Pengaruh Sikap, Motif, Tingkat Kepentingan, dan Harapan Masyarakat di Kota Denpasar terhadap Rencana Kebijakan Ekstensifikasi Cukai pada Minuman Berpemanis.

Ratu, C. A., Anggraeni, D. F., Eka, S. C., & Miftah, Z. P. Z. (2022). Kemampuan Membaca Label Gizi dengan Konsumsi Makanan dan Minuman Kemasan Tinggi Gula.

Zhou, L., Zhang, C., Liu, F., Qiu, Z. and He, Y. (2019), Application of Deep Learning in Food: A Review. Comprehensive Reviews in Food Science and Food Safety, 18: 1793-1811.

Mezgec, S. and Seljak, B.K., 2019. Using deep learning for food and beverage image recognition. 2019 IEEE International Conference on Big Data (Big Data), Los Angeles, CA, USA, pp.5149-5151. doi: 10.1109/BigData47090.2019.9006181.

Srivastava, S. and Srivastava, R., 2022. Novel approach to classify different beverages using back propagation algorithm. 2022 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS), Greater Noida, India, pp.873-878. doi: 10.1109/ICCCIS56430.2022.10037659.