Prediksi Masa Kedaluwarsa Wafer dengan Artificial Neural Network (ANN) Berdasarkan Parameter Nilai Kapasitansi

https://doi.org/10.22146/agritech.9541

Erna Rusliana Muhamad Saleh(1*), Erliza Noor(2), Taufik Djatna(3), Irzaman Irzaman(4)

(1) Program Studi Teknologi Hasil Pertanian, Fakultas Pertanian, Universitas Khairun, Jl. Raya Pertamina, Gambesi, Ternate 97716
(2) Departemen Teknologi Industri Pertanian, Fakultas Teknologi Pertanian, Institut Pertanian Bogor, Kampus Institut Pertanian Bogor Darmaga Bogor 16680
(3) Departemen Teknologi Industri Pertanian, Fakultas Teknologi Pertanian, Institut Pertanian Bogor, Kampus Institut Pertanian Bogor Darmaga Bogor 16680
(4) Departemen Fisika, Fakultas Matematika dan Ilmu Pengetahuan Alam, Institut Pertanian Bogor, Kampus Institut Pertanian Bogor Darmaga Bogor 16680
(*) Corresponding Author

Abstract


Wafer is type of biscuit frequently found on expired condition in market, therefore prediction method should be implemented to avoid this condition. apart from the prediction of shelf-life of wafer done by laboratory test, which were time-consuming, expensive, required trained panelists, complex equipment and suitable ambience, artificial neural network (ANN) based dielectric parameters was proposed in nthis study. The aim of study was to develop model to predict shelf-life employing aNN based capacitance parameter. Back propagation algorithm with trial and error was applied in variations of nodes per hidden layer, number of hidden layers, activation functions, the function of learnings and epochs. The result of study was the model was able to predict wafer shelf-life. The accuracy level was shown by low MSE value (0.01) and high coefficient correlation value (89.25%).

ABSTRAK

Wafer adalah jenis makanan kering yang sering ditemukan kedaluwarsa. Penentuan masa kedaluwarsa dengan observasi laboratorium memiliki beberapa kelemahan, diantaranya memakan waktu, panelis terlatih, suasana yang tepat, biaya dan alat uji yang kompleks. alternatif solusinya adalah penggunaan artificial Neural Network (ANN) berbasiskan parameter kapasitansi. Tujuan kerja ilmiah ini adalah untuk memprediksi masa kedaluwarsa wafer menggunakan aNN berbasiskan parameter kapasitansi. algoritma pembelajaran yang digunakan adalah Backpropagation dengan trial and error variasi jumlah node per hidden layer, jumlah hidden layer, fungsi aktivasi, fungsi pembelajaran dan epoch. Hasil prediksi menunjukkan bahwa aNN hasil pelatihan yang dikombinasikan dengan parameter kapasitansi mampu memprediksi masa kedaluwarsa wafer dengan MSE terendah 0,01 dan R tertinggi 89,25%.


Keywords


Artificial Neural Network; shelf-life; waffer; dielectric; capacitance

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DOI: https://doi.org/10.22146/agritech.9541

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Agritech (print ISSN 0216-0455; online ISSN 2527-3825) is published by Faculty of Agricultural Technology, Universitas Gadjah Mada in colaboration with Indonesian Association of Food Technologies.


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