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All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika CHEDS: Journal of Chemistry, Education, and Science
Maulidna, Maulidna
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Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Education Materials Science & Nanotechnology

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Comparison of Activation Functions on Convolutional Neural Networks (CNN) to Identify Mung Bean Quality Karo Karo, Ichwanul Muslim; Karo Karo, Justaman Arifin; Ginting, Manan; Yunianto, Yunianto; Hariyanto, Hariyanto; Nelza, Novia; Maulidna, Maulidna
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 4 (2023): Article Research Volume 7 Issue 4, October 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i4.13107

Abstract

Mung bean production levels by farmers in Indonesia are not stable. When there is a surplus, the stock of mung beans in the warehouse will accumulate, the storage factor affects the quality of mung beans. Indicators of quality mung beans can be seen from the color and size through direct observation. However, the aspect of view and assessment and the level of health of each observer is a human error in the classification of mung bean quality so that the results are less than optimal. One alternative way to identify object quality is to use deep learning algorithms. One of the popular deep learning algorithms is convolution neural network (CNN). This study aims to build a model to classify the feasibility of mung beans. The process of building the model also goes through the image preprocessing stage. In the process of building the model, there are ten setup parameters and four setup data used to produce the best model. As a result, the best CNN algorithm model performance is obtained from data setup I, with accuracy, precision, recall and F1 score above 75%. In addition, this study also analyzes Rel U and Adam activation functions on CNN algorithm on model performance in identifying mung bean quality. CNN algorithm with Adam activation function has 92% accuracy, 92.53% precision, 91.9% recall, and 92.19% F1 score. In addition, the performance of CNN algorithm with Adam activation function is superior compared to CNN algorithm with Adam activation function and previous study
ANALISIS KADAR NaCl PADA PROSES REGENERASI RESIN DALAM PENURUNAN KESADAHAN Ca2+ DAN Mg2+ PADA PROSES WATER TREATMENT DI PT. ANY Nelza, Novia; Maulidna, Maulidna; Rachmiadji, Irwan; Barus, Adil; Donda, Donda; Darmadi, Herry
CHEDS: Journal of Chemistry, Education, and Science Vol 8, No 2 (2024)
Publisher : Universitas Islam Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30743/cheds.v8i2.10127

Abstract

Resin merupakan bahan yang mengandung ion-ion yang dapat ditukar dengan ion-ion yang ada di dalam air. Resin sebagai media penukar ion memiliki kemampuan terbatas dalam menukar ion hingga resin jenuh. Resin yang telah mengalami kejenuhan akan diregenerasi menggunakan larutan NaCl sehingga kemampuan resin dalam menukar ion kembali efisien. Dari perhitungan yang telah dilakukan diketahui bahwa jumlah NaCl yang digunakan untuk proses regenerasi dapat ditentukan dengan menghitung jumlah zat reaktif yang ditukar resin dengan kesadahan yang terkandung dalam air. Cara penentuan tingkat kesadahan dalam air menggunakan metode titrasi kompleksometri. Dari hasil penelitian yang telah dilakukan diketahui besarnya kekerasan yang terserap sebesar 18,9387 mg/L untuk logam Ca2+ dan 9,324 mg/L untuk logam Mg2+, jumlah zat reaktif Na+ yang ditukar sebesar 14,4763 mg/L untuk Ca2+ dan 7,0462 mg/L. mg/L untuk logam Mg2+ dan jumlah NaCl yang dibutuhkan sebesar 21,1504 mg/L untuk regenerasi resin.
Co-Authors Barus, Adil Darmadi, Herry Donda, Donda Ginting, Manan HARIYANTO HARIYANTO Ichwanul Muslim Karo Karo Karo karo, Justaman Arifin Nelza, Novia Rachmiadji, Irwan Yunianto Yunianto