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Lila Setiyani
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Journal : Scientific Journal of Informatics

 1 
Arabica Coffee Price Prediction Using the Long Short Term Memory Network (LSTM) Algorithm Setiyani, Lila; Utomo, Wiranto Herry
Scientific Journal of Informatics Vol 10, No 3 (2023): August 2023
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v10i3.44162

Abstract

Purpose:  Arabica coffee beans have been widely cultivated in various parts of the world. The need for coffee beans is estimated to increase every year. This was followed by the rapid growth of franchised coffee shops and cafes, therefore Arabica coffee beans have been traded legally in the world, thus making the price of these Arabica coffee beans a public concern. This prediction of the price of Arabica coffee beans can be input for business actors in the coffee shop, café franchises, and farmers in the decision-making process. This study aims to predict the price of Arabica coffee beans in 2023 and 2024 using the long short-term memory (LSTM) Algorithm.Methods:  The research procedure is carried out by collecting data, data analysis, and preprocessing, and building a forecasting model using the Long Short-Term Memory Network (LSTM) algorithm. Arabica coffee bean price datasets in this study were taken from The Pink Sheet World Bank Commodity Price Data, which presents Arabica coffee bean prices from 1960 to February 2023.Results:  The results of this study indicate the predicted price of Arabica coffee beans in 2023 and 2024 with Error (MAE), which is the average absolute difference between the actual value and the predicted value.Novelty:  What is most important and what differentiates it from previous research is in the preprocessing using two algorithms namely MinMaxScaler and Sliding Window. Meanwhile, for the training model, GridSearchCV is used. The model is evaluated using the lost function using Mean Squared Error (MSE) and Mean Absolute Error (MAE) thereby making it easy to evaluate the performance of the model. 
Co-Authors -, Yulindawati Abilio Alfredo Abin Syamsudin Alfiansyah, Deden Moh Alpudoli, Muhamad Anwar Maulana Apit Priatna Arief Ramadhan Arienabila, Firda Arif Maulana Yusuf Arifin, Daeng Awalludin, Dudi Azis Somadulloh Bahari, Mochamad Adzan Benny Setiawan Daeng Arifin Damanhuri, Ahmad Damas Setiadi Sukardi Deden Moh Alfiansyah Dedih Dedih, Dedih Devi Fajar Wati Dewi Purwati Dudi Awaludin Effendy, Femmy Elanda, Anggi Evelyn Tjandra Evelyn Tjandra Fajar Wati, Devi Fathurrozaq, Shiddieq Fauziah Gusni Femmy Femmy Effendy Finna Puspita Priasih Kriswanto Fitria Nurapriani Furqon Kautsar Syabani Gintings, Abdorrakhman Giofanny Theresia Liswadi Hamzah, M Jafat Ali Hidayat , Shelza Aurelia Indahsari, Ayu Nur Inpresta Natali Inpresta Natali Istandi, Rifal Hildan J, Muhammmad Jembar Jajang Jajang Jaka Abdul Haris Jaki Wagiar Jasmine Fitriyah Yamani Jasmine Fitriyah Yamani Juwita, Rahma Luis Makluf Luis Makluf M. Wahidin Maman Suryaman Maman Suryaman Marthiasari, Ghina Fadhilla Mayra Zannuba Prawidhi Mokhamad Wahidin Murni Kurniasih Naufal Athif Syarifudin Novia Larasati Setyo Ningrum Nugroho, Lucky Satrio Puspa Dewi R. Mega Yulianto Rahayu, Dhian Nur Rahmah, Via Aulia Rahmat Gunawan Reni Rachmawati Risnawati Risnawati Risnawati Rizka Amalia Rostiani, Yeny RR. Ella Evrita Hestiandari Rusdianto Roestam Saskia, Ayu Siti Aisyah Slamet, Annisa Anggraini Sri Purwani Suhada, Karya Surya Surya Syamsudin, Abin Syarifudin, Naufal Athif Thio Viedya Susanto Tjandra, Evelyn Tobi, Tobi Tri Ratnasari Vina Maulidina Wahyu Diana Saputra Wangsih, Wangsih Wati, Devi Fajar Wiilys Wiranto Herry Utomo Yahya Suherman Yudiana Yudiana Yulindawati -