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All Journal JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI Techno.Com: Jurnal Teknologi Informasi Jurnal Simetris CAUCHY: Jurnal Matematika Murni dan Aplikasi TELKOMNIKA (Telecommunication Computing Electronics and Control) JUTI: Jurnal Ilmiah Teknologi Informasi Jurnal Teknologi Informasi dan Ilmu Komputer Scientific Journal of Informatics Kubik Jurnal Matematika dan Statistika serta Aplikasinya (Jurnal MSA) Jurnal Fourier Jurnal Sains Matematika dan Statistika InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Sistemasi: Jurnal Sistem Informasi Jurnal Pemberdayaan Masyarakat Madani (JPMM) INTEGER: Journal of Information Technology Indonesian Journal of Artificial Intelligence and Data Mining BAREKENG: Jurnal Ilmu Matematika dan Terapan JOURNAL OF APPLIED INFORMATICS AND COMPUTING MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jurnal Telematika Infotekmesin ARBITRER: Jurnal Pendidikan Bahasa dan Sastra Indonesia InPrime: Indonesian Journal Of Pure And Applied Mathematics KUBIK: Jurnal Publikasi Ilmiah Matematika Journal of Mathematics Education and Science Al-Hilal: Journal of Islamic Astronomy Jurnal Matematika Integratif STATISTIKA Scientica: Jurnal Ilmiah Sains dan Teknologi NERO (Networking Engineering Research Operation)
Nurissaidah Ulinnuha
Institut Teknologi Sepuluh Nopember
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Languange, Linguistic, Communication & Media Library & Information Science Mathematics Mechanical Engineering Medicine & Pharmacology Physics Social Sciences Transportation Other

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Journal : KUBIK: Jurnal Publikasi Ilmiah Matematika

 1 
Penerapan Extreme Learning Machine Dalam Meramalkan Harga Minyak Sawit Mentah Siti Aisyah; Nurissaidah Ulinnuha; Abdulloh Hamid
KUBIK Vol 7, No 2 (2022): KUBIK: Jurnal Publikasi Ilmiah Matematika
Publisher : Jurusan Matematika, Fakultas Sains dan Teknologi, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/kubik.v7i2.20460

Abstract

The need for crude palm oil has increased due to the large demand for vegetable oils in various parts of the world. Beginning in March 2022, the price of crude palm oil set a record high which caused international cooking oil prices to soar, especially for Indonesia. This study aims to predict the price of crude palm oil with test parameters, namely hidden neurons and activation functions. The method used is Extreme Learning Machine (ELM). This method is a development of the artificial neural network (ANN) method which can overcome weaknesses in the learning speed process. There are several stages in this study: (1) pre-processing the data by normalizing the data and dividing the data using the time series split method, (2) analyzing the data using the ELM method by testing parameters, namely hidden neurons and activation functions, (3) analyzing the results of the best parameter trials, (4) calculating forecasting data using the best parameters that have been obtained, and (5) analyzing the forecasting results that have been obtained. This study uses daily data on the price of crude palm oil from April 1 2021 to April 14 2022 obtained from the Investing website. The results of the research that has been carried out obtained MAPE and RMSE values of 0.0173 and 0.0308 with the best parameters namely the number of hidden neurons of 5 and the binary sigmoid activation function. Based on the results obtained, it is hoped that it will make it easier for the government to determine the price of crude palm oil in the future.
Ekstraksi Topik Pantun di Twitter Menggunakan K-Means Clustering Ulinnuha, Nurissaidah; Indriyani, Jiphie Gilia
KUBIK Vol 8, No 1 (2023): KUBIK: Jurnal Publikasi Ilmiah Matematika
Publisher : Jurusan Matematika, Fakultas Sains dan Teknologi, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/kubik.v8i1.29191

Abstract

Pantun is an old form of poetry in Indonesia. Over time, the anxiety of the existence of rhymes in society has become the anxiety of literary, language and cultural activists. This study aims to explore the existence of the use of rhymes on social media which was highly encouraged by young people in the era of Society 5.0. There are two types of rhymes studied, namely general and islamic rhymes. The method used is K-Means clustering analysis to find rhyme topics that are often used in social media. The general category of pantun cluster structure belongs to the weak structure because the silhouette coefficient values are in the range of 0.26-0.5 while the Islamic pantun group structure belongs to the good too strong structure because the silhouette coefficient values are in the range of 0.4-0.9. It was found that the general category of rhymes were still widely used on social media with the type of theme being youth rhymes. The purpose of using the rhyme is more dominant to express feelings. On the other hand, the islamic category of rhymes is rarely used on social media with the type of theme being parental rhymes. The purpose of using the rhyme is more dominant to religious symbols.
Implementation of BiLSTM to Predict World Crude Oil Prices Sari, Firda Yunita; Ulinnuha, Nurissaidah
KUBIK Vol 10 No 1 (2025): IN PRESS
Publisher : Jurusan Matematika, Fakultas Sains dan Teknologi, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The main source of energy worldwide is crude oil, which is used by almost all countries as an energy source. Crude oil plays a key role in driving the global economy, especially in the industrial and transportation sectors. Along with technological developments, crude oil price predictions can be made more sophisticated using artificial intelligence-based methods, one of which is the Bidirectional Long Short-Term Memory (BiLSTM) method which is a development of the Long Short-Term Memory (LSTM) method by combining past and future information when processing sequential data, BiLSTM uses forward and backward LSTM simultaneously to increase accuracy. The study used world crude oil price data for 1 year. There are 57 tests with several parameters such as data division, number of neurons, batch size, and activation function. After testing with the BiLSTM method for 57 scenarios, there is the smallest MAPE value of 0.09% at a data division of 90:10, number of neurons 100, batch size of value 4, and ReLu activation function. The resulting prediction model is highly accurate based on the MAPE criterion value.
Co-Authors Abdulloh Hamid Abdulloh Hamid Ahmad Hanif Asyhar Alfirdausy, Roudlotul Jannah Almumtazah, Nilna Aprilianti, Inggrit Delima Aqilah Khansa, Shafa Fitria Ardelia, Nita Ariestia Ramadhani Aris Fanani Daffa Nur Cholis Dino Ramadhan Elisa Syafaqoh FAJAR SETIAWAN Farmita, Mayandah Fransisca, Velicia Hilmi, Moh. Aditya Sirojul Imama Sabilla, Wilda Indriyani, Jiphie Gilia Intan, Putroue Kumala Isye Arieshanti Khasanah, Rofina Muti'atun Kiromi, Muhammad Sahrul Lutfi Hakim Maghfiroh, Wardatul Maulana, Achmad Resnu Maulidya, Rahmania Moh. Hafiyusholeh Mohamat Ulin Nuha Mu'afa, Sulthan Fikri Nafis, Urwatun Novianti, Fahriza Prilindaputra, Brilian Purwanti, Ida Putri, Anindya Maya Putri, Dinda Rima Rachcita Putroue Keumala Intan Rafika Veriani Romdloni, Ro’iqotul Fathiyyah SA'DYAH, HALIMATUS Safira, Icha Dwi Sari, Dian Candra Rini Novita Sari, Firda Yunita Sari, Ghaluh Indah Permata Septiani, Intan Karunia Septiani Sholihah, Siti Azizatus Siti Aisyah Sufriyah, Lailiyatus Sulthan Fikri Mu'afa Tussholikhah, Anissa Nurul Farida USWATUN KHASANAH Utami, Tri Mar'ati Nur Wahyudi, Sharenada Norisdita Wika Dianita Utami Wika Dianita Utami Yanuwar Reinaldi Yudhi Purwananto Yuliati, Dian Yuniar Farida, Yuniar Yunita Ardilla Yusuf Ababil, Achmad Fachril