Prediksi Perhitungan Jumlah Produksi Tahu Mahanda dengan Teknik Fuzzy Sugeno

Siti Hajar(1*), Masrof Badawi(2), Yudika Dwi Setiawan(3), Muhammad Noor Hasan Siregar(4), Agus Perdana Windarto(5),

(1) STIKOM Tunas Bangsa, Pematangsiantar, Sumatera Utara - Indonesia
(2) STIKOM Tunas Bangsa, Pematangsiantar, Sumatera Utara - Indonesia
(3) STIKOM Tunas Bangsa, Pematangsiantar, Sumatera Utara - Indonesia
(4) Universitas Graha Nusantara, Padangsidimpuan, Sumatera Utara - Indonesia
(5) STIKOM Tunas Bangsa, Pematangsiantar, Sumatera Utara - Indonesia
(*) Corresponding Author

Abstract


"Mahanda" tofu industry is a home industry managed by family members located in the city of Pematangsiantar. The purpose of this research is to analyze the amount of "Mahanda" tofu production using fuzzy logic. Sources of data obtained by conducting interviews and direct observation. Fuzzy logic used is the Sugeno method. The variables used are demand variables, inventory variables, and production variables. Each variable has 3 fuzzy sets, the request variable consists of {down, medium, up}. Inventory variables consist of {few, medium, many}. And the production variable consists of {reduced, tolerable and increased}. The test data results there is a difference of error of 0.19% so that this method can be applied to the "Mahanda" tofu factory in the estimated tofu production for the next period.

Full Text:

PDF

References


S. Nurdini, G. W. Nurcahyo, and J. Santony, “Analisis Perkiraan Jumlah Produksi Tahu Menggunakan Metode Fuzzy Sugeno,” J. Sistim Inf. dan Teknol., vol. 1, no. 3, pp. 19–24, 2019, doi: 10.35134/jsisfotek.v1i3.5.

D. N. Midayanto and S. S. Yuwono, “Penentuan Atribut Mutu Tekstur Tahu Untuk Direkomendasikan Sebagai Syarat Tambahan Dalam Standar Nasional Indonesia [in Press Oktober 2014],” J. Pangan dan Agroindustri, vol. 2, no. 4, pp. 259–267, 2014.

A. P. Windarto, “Implementasi Jst Dalam Menentukan Kelayakan Nasabah Pinjaman Kur Pada Bank Mandiri Mikro Serbelawan Dengan Metode Backpropogation,” J-SAKTI (Jurnal Sains Komput. dan Inform., vol. 1, no. 1, pp. 12–23, 2017.

A. P. Windarto, L. S. Dewi, and D. Hartama, “Implementation of Artificial Intelligence in Predicting the Value of Indonesian Oil and Gas Exports With BP Algorithm,” Int. J. Recent Trends Eng. Res., vol. 3, no. 10, pp. 1–12, 2017, doi: 10.23883/IJRTER.2017.3482.J5BBS.

A. P. Windarto, “Implementation of Data Mining on Rice Imports by Major Country of Origin Using Algorithm Using K-Means Clustering Method,” Int. J. Artif. Intell. Res., vol. 1, no. 2, pp. 26–33, 2017.

E. S. Puspita and L. Yulianti, “Perancangan sistem peramalam cuaca berbasis Logika Fuzzy,” Media Infotama, vol. 12, no. 1, pp. 1–10, 2016.

S. Sitohang and R. Denson Napitupulu, “Fuzzy Logic Untuk Menentukan Penjualan Rumah Dengan Metode Mamdani (Studi Kasus: Pt Gracia Herald),” J. ISD, vol. 2, no. 2, pp. 2528–5114, 2017.

A. Y. Mutmainah and J. Suprijadi, “Penerapan Model Hybrid ARIMA- Neural Network pada Data Saham IHSG,” in Seminar Nasional Statistika Fmipa UNPAD, 2017, vol. 7, no. Sns Vi, pp. 55–61.

A. Koesriputranto, “Prediksi Harga Saham Di Indonesia Dengan Menggunakan Metode Hybrid Principal Component Analysis Dan Support Vector Machine (PCA-SVM),” 2015.

A. Wanto, “Analisis Penerapan Fuzzy Inference System (FIS) Dengan Metode Mamdani Pada Sistem Prediksi Mahasiswa Non Aktif (Studi Kasus : AMIK Tunas Bangsa Pematangsiantar),” in Seminar Nasional Inovasi Dan Teknologi Informasi (SNITI) 3, 2016, vol. 3, pp. 393–400, doi: 10.17605/OSF.IO/HGMYC.

A. Ahmad, “Mengenal Artificial Intelligence, Machine Learning, Neural Network, dan Deep Learning,” J. Teknol. Indones., no. October, p. 3, 2017.

Eka Sabna and Muhardi, “Penerapan Data Mining Untuk Memprediksi Prestasi Akademik Mahasiswa Berdasarkan Dosen , Motivasi , Kedisiplinan , Ekonomi ,” CoreIT, vol. 2, no. 2, pp. 41–44, 2016.

D. A. Silitonga, M. Anjelita, and A. P. Windarto, “Fuzzy Inference System Pada Prediksi Pembelian Bahan Bakar Pertamax Pada SPBU di Kota Pematangsiantar,” Syntax J. Inform., vol. 8, no. 2, p. 75, 2019, doi: 10.35706/syji.v8i2.1841.

F. A. Gumelar, R. Regasari, and M. Putri, “Implementasi Fuzzy Time Series Pada Prediksi Harga Daging Di Pasar Kabupaten Malang,” J. Pengemb. Teknol. Inf. dan Ilmu Komput. Univ. Brawijaya, vol. 2, no. 8, pp. 2724–2733, 2018.

S. Kusumadewi and S. Hartati, Neuro-Fuzzy Integrasi Sistem Fuzzy dan Jaringan Syaraf. 2006.

N. Walia, H. Singh, and A. Sharma, “ANFIS: Adaptive Neuro-Fuzzy Inference System- A Survey,” Int. J. Comput. Appl., 2015, doi: 10.5120/ijca2015905635.

N. Talpur, M. N. M. Salleh, and K. Hussain, “An investigation of membership functions on performance of ANFIS for solving classification problems,” in IOP Conference Series: Materials Science and Engineering, 2017, doi: 10.1088/1757-899X/226/1/012103.




DOI: http://dx.doi.org/10.30645/j-sakti.v4i1.200

Refbacks

  • There are currently no refbacks.



J-SAKTI (Jurnal Sains Komputer & Informatika)
Published Papers Indexed/Abstracted By:


Jumlah Kunjungan :

View My Stats