Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : Informatika

Implementasi Deep Learning Untuk Menentukan Harga Buah Sawit Manurung, Romtika; Sihombing, Volvo; Hasibuan, Mila Nirmala Sari
Jurnal Informatika Vol 12, No 3: INFORMATIKA
Publisher : Fakultas Sains & Teknologi, Universitas Labuhanbatu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36987/informatika.v12i3.6029

Abstract

This study aims to analyze the price of palm oil using Convolutional Neural Network (CNN) method in deep learning. CNN was chosen for its ability to process complex data and recognize patterns from diverse data. The stages of research include data analysis, data pre-processing, predictive model design for CNN method, CNN classification model prediction results, CNN method evaluation, and CNN method evaluation results. This study aims to produce a model that can predict the price of oil palm with high accuracy, based on data covering a variety of characteristics of farmers and the quality of oil palm crops. Prediction results were conducted using data from 50 oil palm farmers. From the prediction, as many as 23 data farmers get a price of IDR 2,300, 13 other farmers get a price of IDR 2,000, and the remaining 14 data farmers get a price of IDR 1,800. The results of this prediction are based on data from farmers and the quality of oil palm crops they grow and produce. By utilizing the CNN method, the model can capture various factors that affect the price of palm oil, including the quality of palm fruit and agricultural conditions. Evaluation of the CNN method showed very good results, with almost perfect accuracy. This method managed to predict palm oil prices very precisely, showing that CNN can be an effective tool in the analysis of palm oil prices. The results of this evaluation confirmed that the CNN method can be relied upon to provide accurate predictions, helping farmers and palm oil industry players in determining prices that are in accordance with the quality and condition of the crop.
Co-Authors Abdillah, Ihsan Abdillah, Syakira Adi, Puput Dani Prasetyo Adi, Puput Dani Prasetyo Adi Aditya, Nanda Ajeng Lestari, Dinda Alam, Dewi Pathimah Alpiansyah, Fredy Andriyani, Wahyu Fitri Angreani Hulu, Linca Elma Popi Ariska, Fevi Aurianda, Rieke Bangun, Budianto Barasa, Kristina Dewi Utami, Yarma Agustya Dwiyanti, Dida Dwiyanti, Didan Efendi, Davina Rizky Esterlin, Esterlin Fachry Abda El Rahman Fadilla Hasibuan, Intan Gultom, Gregorius Apri K Gustriyadi, Eko Halawa, Prianus Harefa, Sinema Hasibuan, Dilla Puspita Hasibuan, Mila Nirmala Sari Hasibuan, Sabdi Albi Hendriyanti, Yurika Cici Hia, Faomaha Hutagalung, Charles Efendy Irmayani , Deci Irmayani Irmayani Irmayani, Deci Jannah , Ely Jati, Dewi Sekar Juledi, Angga Putra Juni Yanris, Gomal Latifah Hanum Lumban Gaol, Tid Verawati Maizura, Safrina Manurung, Romtika mawarni, Putri Sigit Mega, Mega Muhammad Halmi Dar Muliani, Sonia Sri Munthe , Ibnu Rasyid Munthe, Ibnu Rasyid Mustamu, Novilda Elizabeth Nasution, Fitri Aini Nasution, Marnis Nurdila, Nurdila Pakto, Dedi Pertiwi, Nur Fajar Kurnia Petromak Sinaga, Gandhi Naek Purba, Mila Hanim Purwati Purwati Putra Juledi, Angga Ramadhani, Siska Rangkuti, M. Andri Gautama Rani Rahayu, Rani Rasyid Munthe, Ibnu Rizky Mangunsong, Annisa Rusmiana, Rusmiana Rusmina, Eva Safitri, Nina Siddik, Rasid Simamora, Rikardo Lasroha Sinaga, Veranica siregar, Victor M.M. Siti Kholijah, Siti Kholijah Sitio, Arjon Samuel Sitompul, Joni Awendri Sitorus, Anggiat Selamat Suci Ramadhani, Suci Suhaylah, Suhaylah Syafitri, Risma Syahputra, Rapian Tasyabila, Tasyabila Tawanta Natalia Sembiring, Sri Tiara, Dewi Tria Wulandari Wiranti, Dea Yanris, Gomal Juni