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All Journal Jurnal Ampere PENDIPA Journal of Science Education JUTIS : Jurnal Teknik Informatika Pelita Eksakta Suluah Bendang: Jurnal Ilmiah Pengabdian Kepada Masyarakat Jurnal Abdimas Bina Bangsa Publikasi Hasil Pengabdian Kepada Masyarakat. UNP Journal of Statistics and Data Science Indonesian Journal of Statistics and Its Applications
Dina Fitria, Dina
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Humanities Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Mathematics Physics Social Sciences Other

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Journal : Indonesian Journal of Statistics and Its Applications

 1 
Classification of Rice Growth Phase Using Regression Logistic Multinomial Model and K-Nearest Neighbors Imputation on Satellite Data Ghaly, Fayyadh; Kurniawati, Yenni; Amalita, Nonong; Fitria, Dina
Indonesian Journal of Statistics and Applications Vol 9 No 1 (2025)
Publisher : Departemen Statistika, IPB University dengan Forum Perguruan Tinggi Statistika (FORSTAT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/ijsa.v9i1p1-9

Abstract

One of the efforts made by the government to maintain food security is to provide statistical data on rice production through accurate calculation of harvest areas using the area sampling framework approach. Although area sampling framework surveys produce accurate estimates, the costs required are quite high when applying this method. To overcome this problem, one solution that can be applied is to utilize satellite imagery to monitor the greenness index of plants using the enhanced vegetation index. However, in real conditions, the Landsat-8 optical satellite is susceptible to cloud cover, which results in missing data. This study aims to model the phase of rice plants using the regression logistic multinomial model by utilizing Landsat-8 satellites and k-nearest neighbors imputation handling to overcome missing data. The results showed that the model had varying performance in each phase, with an average balanced accuracy of 66.45%. This figure shows that the model can classify the area sampling framework data imputed using the k-nearest neighbors imputation method well. The model shows optimal performance in the late vegetative and generative phases but is less effective in detecting the harvest, puso, and non-rice paddy phases.
Application of Singular Spectrum Analysis in Predicting Rupiah Exchange Yuan Hendrawan, Muhammad; Zilrahmi, Zilrahmi; Kurniawati, Yenni; Fitria, Dina
Indonesian Journal of Statistics and Applications Vol 9 No 1 (2025)
Publisher : Departemen Statistika, IPB University dengan Forum Perguruan Tinggi Statistika (FORSTAT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/ijsa.v9i1p75-85

Abstract

The exchange rate between two countries is the price of the currency used by residents of these countries to trade with each other, the relationship between the Rupiah exchange rate and the Yuan is one of the important aspects in the dynamics of international trade. Therefore, forecasting the exchange rate is important as an effort to predict the exchange rate of Rupiah against Yuan in the future. The method used for forecasting is Singular Spectrum Analysis, namely decomposition and reconstruction. The accuracy of the resulting forecast is measured using the Mean Absolute Percentage Error criterion. The exploration results obtained are forecasting accuracy based on the Mean Absolute Percentage Error value of 2.15% with a window length of 23 which identifies that the forecasting results are accurate and effective. Forecasting is said to be accurate if the Mean Absolute Percentage Error value is lower than 10% and close to 10%
Co-Authors Abdillah, Muhammad Mukhlis Abdul Aziz, Ahmad Malik Abdur Rahim, Abdur Al Aziz, Saddam Alamin, M. Anggari Linda Destiana Antasya, Faridah Darussalam, Muhammad Illyas Day, Dafzel Dewi Rawani Dinul Haq, Asra Dodi Vionanda Dony Permana Fathonah, Deffya Ghaly, Fayyadh Hendrawan, Muhammad Indri Astuti Joni Joni Khalida, Rizqiana Maulana, Muhammad Arif Moh. Wahyu Aminullah Moulita, R.A. Nurul Muhni Pamuji, Muhni Mujaidiah Mukhti, Tessy Octavia Nahdah, Athaya Nisrina Nonong Amalita Nugroho, Agung Pajrini, Nurul Hasni Permana, Dony Putri, Sindy Amelia Revelino, Imanuel Ridho, Fakhru Rini Afrianti Salma, Admi Suhady, Suhady Suherman, Suherman Suparmin Suparmin Syafriandi Syafriandi Turrohmah, Azizah Yarman Yarman, Yarman Yenni Kurniawati Yudi Irwansi, Yudi Yuwon, Yuwon zafira, Rufaidah Zamahsary Martha Zilrahmi, Zilrahmi