Sistem Pengering Daun Kelor Berbasis Internet of Things dan Artificial Intteligence

https://doi.org/10.22146/ijeis.89823

I wayan Sudiarsa(1), Putu Sugiartawan(2*), I Gede Iwan Sudipa(3), Ni Made Maharianingsih(4), I Kadek Adiana Putra(5)

(1) INSTITUT BISNIS DAN TEKNOLOGI INDONESIA
(2) INSTITUT BISNIS DAN TEKNOLOGI INDONESIA
(3) INSTITUT BISNIS DAN TEKNOLOGI INDONESIA
(4) Universitas Bali Internasional
(5) INSTITUT BISNIS DAN TEKNOLOGI INDONESIA
(*) Corresponding Author

Abstract


Drying Moringa leaves is needed to reduce the water content so that the Moringa leaves become fresh and can be used for the following process. Drying Moringa leaves to change the water content from 80% to 9.2% requires ideal heating conditions because the heating speed must not damage the nutritional content in the leaves. Developing an existing drying system using IoT to monitor humidity and temperature to increase the drought stability of the Moringa leaves produced. By using IoT, it is hoped that drying conditions can be watched from anywhere and recorded so that if undesirable things happen, it will be easier to track the history of the drying process that has taken place. This system is also connected to a recommendation system using an Artificial Neural Network (ANN). This system will provide recommendations for the best conditions for Moringa flour production because various external factors influence the drying of Moringa leaves. Utilization of the ANN model can recognize data patterns in seasonal time series. The results of implementing the Moringa leaf drying machine can reduce the time by 120 minutes faster than the previous tool

Keywords


Moringa; Auto dryer; IOT; ANN;

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References

I. Kurniawati and M. Fitriyya, “Characteristics of Moringa Leaf Flour with Sunlight Drying Method,” J. Gizi dan Pangan, vol. 1, pp. 238–243, 2018, [Online]. Available: http://prosiding.unimus.ac.id

V. A. Koehuana, K. Y. Goab, and M. Jafri, “Pengujian Rumah Pengering Daun Kelor dengan Efek Rumah Kaca (Solar Dryer) Melalui Variasi Kecepatan Udara,” JMPM (Jurnal Mater. dan Proses Manufaktur), vol. 5, no. 2, pp. 68–81, 2022, doi: 10.18196/jmpm.v5i2.13899.

M. Warnis, L. A. Aprilina, and L. Maryanti, “Pengaruh Suhu Pengeringan Simplisia Terhadap Kadar Flavonoid Total Ekstrak Daun Kelor (Moringa oleifera L.),” Semin. Nas. Kahuripan, pp. 264–268, 2020, [Online]. Available: https://conference.kahuripan.ac.id/index.php/SNapan/article/view/64

A. Taufan et al., “Studi Eksperimental dan Model Matematika Pengeringan Daun Kelor (Moringa Oleifera) dengan Empat Tipe Pengeringan,” J. Ris. Teknol. Ind., vol. 14, no. 2, p. 341, 2020, doi: 10.26578/jrti.v14i2.6518.

Riskianto, S. E. Kamal, and M. Aris, “Aktivitas Antioksidan Ekstrak Etanol 70% Daun Kelor ( Moringa oleifera Lam.) terhadap DPPH,” J. Pro-Life, vol. 8, no. 2, pp. 168–177, 2021.

D. A. Kusmardika, “Journal Of Health Science and Physiotherapy,” Potensi Akt. Antioksidan Daun Kelor (Moringa Oleifera) dalam Kangker, vol. 5, no. 3, pp. 248–253, 2020.

L. S. Marhaeni, “Daun Kelor (Moringa oleifera) Sebagai Sumber Pangan Fungsional dan Antioksidan,” Agrisia, vol. 13, no. 2, pp. 40–53, 2021.

J. Dian, F. D. Silalahi, and N. D. Setiawan, “Sistem Monitoring Detak Jantung Untuk Mendeteksi Tingkat Kesehatan Jantung Berbasis Internet Of Things Menggunakan Android,” JUPITER (Jurnal Penelit. Ilmu dan Teknol. Komputer), vol. 13, no. 2, pp. 69–75, 2021, [Online]. Available: https://jurnal.polsri.ac.id/index.php/jupiter/article/view/3669

P. Sugiartawan, R. Pulungan, and A. K. Sari, “Prediction by a Hybrid of Wavelet Transform and Long-Short-Term-Memory Neural Network,” Int. J. Adv. Comput. Sci. Appl., vol. 8, no. 2, pp. 326–332, 2017.

P. Sugiartawan, S. Hartati, and A. Musdholifah, “Modeling of a Tourism Group Decision Support System using Risk Analysis based Knowledge BaseNo Title,” Int. J. Adv. Comput. Sci. Appl., vol. 11, no. 7, pp. 354–363, 2020.



DOI: https://doi.org/10.22146/ijeis.89823

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