Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal Neptunus: Jurnal Ilmu Komputer dan Teknologi Informasi
Saiba Siregar
Unknown Affiliation
Computer Science & IT

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Implementasi Jaringan Syaraf Tiruan Backpropagation pada Klasifikasi Jenis Kopi Berdasarkan Cita Rasa dan Aroma Mimi Sartika Ritonga; Lailan Sofinah; Saiba Siregar
Neptunus: Jurnal Ilmu Komputer Dan Teknologi Informasi Vol. 3 No. 4 (2025): November: Neptunus: Jurnal Ilmu Komputer Dan Teknologi Informasi
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/neptunus.v3i4.1186

Abstract

Coffe is one of Indonesia’s leading commodities, known for its diverse flavors and aromas. Traditionally, coffee quality assessment is conducted manually through cupping tests performed by expert panelists. However, this method is subjective and requires considerable time and cost. This study aims to implement an Artificial Neural Network (ANN) using the backpropagation algorithm to classify coffee types based on sensory parameters such as flavor, aroma, acidity level, and body. Simulated data were generated from five common Indonesian coffee varieties: Arabica Gayo, Robusta Lampung, Arabica Toraja, Liberica Jambi, and Excelsa. The results show that the ANN-based classification system with a 4-8-1 architecture achieved an accuracy rate of 93% after 500 training epochs, with a final error value of 0.07. The implementation of this method provides an efficient and objective technological alternative to assist the coffee industry in maintaining product quality and automatically identifying coffee types.
Co-Authors Lailan Sofinah Mimi Sartika Ritonga