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All Journal Jurnal TIMES Jurnal Teknologi Informasi dan Ilmu Komputer JTAM (Jurnal Teori dan Aplikasi Matematika) Absorbent Mind Jurnal Pusat Inovasi Masyarakat Indonesian Journal of Statistics and Its Applications
Rizki, Akbar
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Computer Science & IT Education Engineering Mathematics Social Sciences Other

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Journal : Indonesian Journal of Statistics and Its Applications

 1 
Application of Univariate and Multivariate Long Short Term Memory for World Crude Palm Oil Price Prediction : Penerapan Long Short Term Memory Peubah Tunggal dan Ganda untuk Prediksi Harga Minyak Kelapa Sawit Dunia Izzany, Nabil; Masjkur, Mohammad; Rizki, Akbar
Indonesian Journal of Statistics and Applications Vol 9 No 1 (2025)
Publisher : Statistics and Data Science Program Study, IPB University, IPB University, in collaboration with the Forum Pendidikan Tinggi Statistika Indonesia (FORSTAT) and the Ikatan Statistisi Indonesia (ISI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/ijsa.v9i1p10-20

Abstract

Time series analysis is essential for predicting economic and other important factors; it can be done univariately or multivariately. Technological developments created long short term memory that can handle vanishing gradients and long-term dependencies. This research will predict the world price of crude palm oil because Indonesia, as the world's largest crude palm oil producer, is strongly influenced by the world crude palm oil price. This study uses monthly data on crude palm oil, soybean oil, and crude oil prices from January 2002 to May 2024 obtained from the World Bank Commodity Price Data. This research applies univariate and multivariate long short term memory to predicting crude palm oil prices. The use of long short term memory is because the data shows non-linear elements and high volatility. The input used for univariate long short term memory is the crude palm oil price, while multivariate long short term memory uses crude palm oil, soybean oil, and crude oil prices. The univariate long short term memory proved to be more effective in the case of world crude palm oil price prediction. This is proven by the lower mean absolute percentage error of 6,574% compared to the multivariate long short term memory of 6,689%. This univariate long short term memory uses a combination of hyperparameters: neuron 32, epoch 100, time steps 1, batch size 64, and learning rate 0,01.
Analysis of Covid-19 Risk Perception Survey Result Using Generalized Structured Component Analysis: Analisis Hasil Survei Persepsi Risiko Covid-19 Menggunakan Generalized Structured Component Analysis Robert, Zahira Rahvenia; Rizki, Akbar; Susetyo, Budi; Amir, Sulfikar
Indonesian Journal of Statistics and Applications Vol 6 No 2 (2022)
Publisher : Statistics and Data Science Program Study, IPB University, IPB University, in collaboration with the Forum Pendidikan Tinggi Statistika Indonesia (FORSTAT) and the Ikatan Statistisi Indonesia (ISI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/ijsa.v6i2p336-347

Abstract

The capital city of Indonesia, Jakarta, became the province with the highest number of Covid-19. Response this situation, LaporCovid-19 collaborate with the Social Resilience Lab, Nanyang Technological University conducted a survey to measure how Jakarta residents perceive the risk of Covid-19 from May 29 to June 20 2020. Factors of risk perception are variables that cannot be measured directly, so they are analyzed used a Structural Equation Modeling (SEM) approach, namely Generalized Structured Component Analysis (GSCA). The Likert scale used can be considered as interval or ordinal depending on the point of view of the theory built. Therefore, this study will compare the GSCA method with the nonlinear GSCA and evaluate six variables, namely risk perception, knowledge, information, health behavior , social capital, and economy. Evaluation of the overall model showed that the nonlinear GSCA model can explain the diversity of qualitative data better than the GSCA model with FIT > 0.9. Based on GSCA nonlinear model, information has significantly influence of knowledge, economy and social capital have a real reciprocal relationship, along knowledge and risk perception have significantly influence of health behavior.
Co-Authors Alfan, Tony Alleluia, Rianti Amelia, Reni Amir, Sulfikar Anik Djuraidah Arnof, Naufal Azizah, Farras Hanifah Budi Susetyo Erfiani Fitri, Zafira Ilma Fitrianto, Anwar Gunawan, Windi Halim, Christin Hananti, Shabira Fahria Indahwati Ishar, Meilia Izzany, Nabil Khairani Khairani Khusnul Khotimah Kusman Sadik Mahesa, Hakim Zoelva Matondang, Harita Julie Zefanya Mohammad Masjkur Nabilah, Amelya Qois Nurhambali, Muhammad Rizky Putri, Adelia Rahmi, Salsabila Dwi Ranggabulawan, Gita Christy Ananda Robert, Zahira Rahvenia Saputra, Eka Adi Suwarso, Dhiya Khalishah Tsany Yenni Angraini