RANCANG BANGUN APLIKASI PENGATUR POLA MAKAN BERDASARKAN KEBUTUHAN ASUPAN KALORI DENGAN K-MEANS

Penulis

  • Sabrina Yose Amelia Universitas Matana
  • Prya Artha Widjaja Universitas Matana

DOI:

https://doi.org/10.31000/jika.v9i1.12527

Abstrak

Diet merupakan salah satu cara menjaga berat badan yang ideal dengan mengatur pola makan. Pada saat sedang menjalankan diet, dianjurkan untuk mencatat berat badan dalam beberapa waktu sekali agar dapat memantau berat badan masing-masing orang yang menjalankan diet. Bagi yang menjalankan diet berdasarkan kalori, sebaiknya juga mencatat kalori yang sudah dikonsumsi perhari untuk memantau jumlah kalori agar tidak melebihi atau kurang dari jumlah kalori yang dibutuhkan perharinya. Pada survei yang dibagikan kepada seratus responden, terdapat 65 orang yang sedang menjalankan diet dan memiliki kendala dalam pencatatan berat badan dan kendala-kendala lainnya. Aplikasi ini dibuat dalam bentuk mobile menggunakan framework Quasar dengan menggunakan rumus yang terdapat pada website p2ptm milik Kementerian Kesehatan Republik Indonesia untuk menghitung kalori yang dibutuhkan. Sedangkan rekomendasi makanan yang sesuai dengan jumlah kalori yang dibutuhkan perhari dibuat dengan K-Means. Aplikasi ini juga memiliki fitur untuk mencatat dan memantau berat badan pengguna, menampilkan daftar makanan beserta kalori dalam beberapa gram, serta menghitung jumlah kalori yang telah dikonsumsi oleh pengguna aplikasi dalam satu hari

Referensi

Ali, S. M. (2022). Software Requirement Engineering Practical Approach. https://www.researchgate.net/publication/362609452

Cena, H., & Calder, P. C. (2020). Defining a healthy diet: Evidence for the role of contemporary dietary patterns in health and disease. In Nutrients (Vol. 12, Issue 2). MDPI AG. https://doi.org/10.3390/nu12020334

Cholis Anggoro, N., & Akbar, M. (2023). Chatbot Pemilihan Makanan dan Minuman Berdasarkan Kalori menggunakan Natural Language Processing. In Jurnal ForAI | (Vol. 1, Issue 1).

Darmawan Sidik, A., & Ansawarman, A. (2022). Prediksi Jumlah Kendaraan Bermotor Menggunakan Machine Learning. Formosa Journal of Multidisciplinary Research (FJMR), 1(3), 559–568. https://doi.org/10.55927

Festi W, P. (2018). Buku Ajar Gizi dan Diet. UMSurabaya Publishing.

KEMENKES. (2018). Laporan Nasional Riskesdas 2018.

KEMENKES. (2023). Survei Kesehatan Indonesia 2023.

Kristiawan, K., & Widjaja, A. (2021). Perbandingan Algoritma Machine Learning dalam Menilai Sebuah Lokasi Toko Ritel. Jurnal Teknik Informatika Dan Sistem Informasi, 7(1). https://doi.org/10.28932/jutisi.v7i1.3182

Murad, D. F., Widjaya, W., Noviani, D. R., Fitriyyah, N., & Saputri, L. M. (2019). Hybrid Mobile Executive Information (m-EIS) System Using Quasar Framework for Indonesia Financial Service Authority. Journal of Information Systems Engineering and Business Intelligence, 5(2), 195. https://doi.org/10.20473/jisebi.5.2.195-207

Ningtyas, D. F., & Setiyawati, N. (2021). Implementasi Flask Framework pada Pembangunan Aplikasi Purchasing Approval Request. Jurnal Janitra Informatika Dan Sistem Informasi, 1(1), 19–34. https://doi.org/10.25008/janitra.v1i1.120

P2PTM Kemenkes RI. (2018). Berapa kebutuhan kalori Anda per hari ? Https://P2ptm.Kemkes.Go.Id/Infographic-P2ptm/Obesitas/Berapa-Kebutuhan-Kalori-Anda-per-Hari.

Putra, D. J. J. (2022). Rancang Bangun Website Layout Builder Berbasis Media Sosial Menggunakan Framework Quasar. Jurnal Pendidikan Tambusai.

Rego Rodríguez, F. A., Germán Flores, L., & Vitón-Castillo, A. A. (2022). Artificial intelligence and machine learning: present and future applications in health sciences. Seminars in Medical Writing and Education, 1, 9. https://doi.org/10.56294/mw20229

Steven Dharmawan, W., Purwaningtias, D., & Risdiansyah, D. (2018). Penerapan Metode SDLC Waterfall Dalam Perancangan Sistem Informasi Administrasi Keuangan Berbasis Desktop. JURNAL KHATULISTIWA INFORMATIKA, VI(2).

WHO. (2019). Healthy Diet.

Unduhan

Diterbitkan

2025-01-31

Terbitan

Vol 9 No 1 (2025): JIKA (Jurnal Informatika)

Bagian

Articles

Lisensi

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