Implementation Fuzzy Mamdani Algorithm To Predict Web Based Inventory

(1) * Bambang Adiwinoto Mail (Institut Sains dan Bisnis Atma Luhur, Indonesia)
(2) Dian Novianto Mail (Institut Sains dan Bisnis Atma Luhur, Indonesia)
*corresponding author

Abstract


Mamdani's fuzzy algorithm enables the use of fuzzy logic to overcome the uncertainties and ambiguities associated with inventory predictions. This study describes implementing the Mamdani fuzzy algorithm to predict web-based inventory. Fuzzy algorithms allow specific reasons to deal with the uncertainties and ambiguities associated with inventory predictions. We collect relevant inventory data, including input variables such as the number of items sold, customer demand, and other factors that affect inventory. We also use historical inventory data to create the Mamdani fuzzy model. We implement fuzzification by specifying a linguistic variable for each input variable and converting the numeric to a linguistic value using a predefined membership function, then build a  rule-based fuzzy Mamdani which includes a set of rules that relate language values as input variables with linguistic values of output variables., i.e., inventory prediction. After the inference process, we apply defuzzification using the Mamdani method to convert the linguistic values of the output variables into numeric values that can be used in practice. Through this implementation, we managed to integrate the power of Mamdani's fuzzy algorithm with web technology so that users can access the inventory prediction system online. This system can assist inventory managers in making better decisions in production planning, stock procurement, and delivery schedule. This system is expected to increase efficiency and optimize inventory availability in a rapidly changing business environment.


Keywords


Fuzzy Algorithm; Artificial Intelligent; Inventory

   

DOI

https://doi.org/10.29099/ijair.v7i1.1.909
      

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References


Badan Pusat Statistik Republik Indonesia. “Statistik Telekomunikasi Indonesia Tahun 2021â€. Sumber: https://www.bps.go.id/publication/2022/09/07/bcc820e694c537ed3ec131b9/statistik-telekomunikasi-indonesia-2021.html

Kementerian Komunikasi dan Informatika Republik Indonesia. “Pertumbuhan E-Commerce di Indonesiaâ€. Sumber: https://www.kominfo.go.id/content/detail/16770/kemkominfo-pertumbuhan-e-commerce-indonesia-capai-78-persen/0/sorotan_media

Ananto E. Prasetiadi. “WEB 3.0: TEKNOLOGI WEB MASA DEPAN,†INDEPT, Vol 1, No. 3, Oktober 2011.

Jehan Saptia Kurnia, Fitria Risyda. “RANCANG BANGUN PENERAPAN MODEL PROTOTYPE DALAM PERANCANGAN SISTEM INFORMASI PENCATATAN PERSEDIAAN BARANG BERBASIS WEB.†Jurnal Sistem Informasi, Vol. 8 No. 2. Tahun 2021.

M. Irfan, L. P. Ayuningtias, and J. Jumadi, “ANALISA PERBANDINGAN LOGIC FUZZY METODE TSUKAMOTO, SUGENO, DAN MAMDANI ( STUDI KASUS : PREDIKSI JUMLAH PENDAFTAR MAHASISWA BARU FAKULTAS SAINS DAN TEKNOLOGI UIN SUNAN GUNUNG DJATI BANDUNG),†J. Tek. Inform., 2018.

A. R. Wardani, Y. N. Nasution, and F. D. T. Amijaya, “Aplikasi Logika Fuzzy Dalam Mengoptimalkan Produksi Minyak Kelapa Sawit Di PT. Waru Kaltim Plantation Menggunakan Metode Mamdani,†Inform. Mulawarman J. Ilm. Ilmu Komput., vol. 12, no. 2, p. 94, 2017, doi: 10.30872/jim.v12i2.651.

Nurhayati and I. Immanudin, “Penerapan Logika Fuzzy Mamdani Untuk Prediksi Pengadaan Peralatan Rumah Tangga Rumah Sakit,†Komputika J. Sist. Komput., 2019.

A. W. F. Much Junaidi, Eko Setiawan, “Penentuan Jumlah Produksi Dengan Aplikasi Fuzzy - Mamdaniâ€, pp. 95 – 104, 2005.

Abdurrasyid, Meilia Nur Indah Susanti, Dini Setria Ningsih. “IMPLEMENTASI METODE FUZZY MAMDANI PADA APLIKASI INVENTORY UNTUK PREDIKSI PENGADAAN BARANG DI PT. PERTAMINA (PERSERO) PERKAPALAN,†Jurnal Petir. Vol. 10, No. 2., 2017

George J. Klir, Bo Yuan. Fuzzy Sets And Fuzzy Logic Theory And Applications. 1995

D. Purnomo, “Model Prototyping Pada Pengembangan Sistem Informasi,†J I M P - J. Inform. Merdeka Pasuruan, vol. 2, no. 2, pp. 54–61, 2017, doi: 10.37438/jimp.v2i2.67.

Dian Novianto, Tri Sugihartono. 2020. Sistem Deteksi Kualitas Buah Jambu Air Berdasarkan Warna Kulit Menggunakan Algoritma Principal Component Analysis (PCA) dan K-Nearest Neigbor (K-NN). JURNAL ILMIAH INFORMATIKA GLOBAL VOLUME 11 No. 2 Desember 2020




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