Article Per Year (5 Year)
p-Index From 2021 - 2026
4.748
P-Index
This Author published in this journals
All Journal Jurnal Ilmu Komputer JAIS (Journal of Applied Intelligent System) Sistemasi: Jurnal Sistem Informasi Sinkron : Jurnal dan Penelitian Teknik Informatika RABIT: Jurnal Teknologi dan Sistem Informasi Univrab JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING JURNAL MEDIA INFORMATIKA BUDIDARMA JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jurnal Teknologi Sistem Informasi dan Aplikasi J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Manajemen Informatika EDUMATIC: Jurnal Pendidikan Informatika Building of Informatics, Technology and Science Progresif: Jurnal Ilmiah Komputer Infotekmesin Jurnal Manajemen Informatika dan Sistem Informasi Journal of Robotics and Control (JRC) Abdimasku : Jurnal Pengabdian Masyarakat Jurnal Pengabdian kepada Masyarakat Nusantara J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Informatika: Jurnal Pengembangan IT LogicLink: Journal of Artificial Intelligence and Multimedia in Informatics Inovasi Sosial: Jurnal Pengabdian Masyarakat Advance Sustainable Science, Engineering and Technology (ASSET)
Winarsih, Nurul Anisa Sri
Universitas Dian Nuswantoro
Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mechanical Engineering Social Sciences

Published : 39 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search
Journal : journal of applied informatics and computing

 1 
Forecasting Air Quality Indeks Using Long Short Term Memory Ramadhani, Irfan Wahyu; Saputra, Filmada Ocky; Pramunendar, Ricardus Anggi; Saraswati, Galuh Wilujeng; Winarsih, Nurul Anisa Sri; Rohman, Muhammad Syaifur; Ratmana, Danny Oka; Shidik, Guruh Fajar
Journal of Applied Informatics and Computing Vol. 8 No. 1 (2024): July 2024
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v8i1.7402

Abstract

Exercise offers significant physical and mental health benefits. However, undetected air pollution can have a negative impact on individual health, especially lung health when doing physical activity in crowded sports venues. This study addresses the need for accurate air quality predictions in such environments. Using the Long Short-Term Memory (LSTM) method or what is known as high performance time series prediction, this research focuses on forecasting the Air Quality Index (AQI) around crowded sports venues and its supporting parameters such as ozone gas, carbon dioxide, etc. -others as internal factors, without involving external factors causing the increase in AQI. Preprocessing of the data involves removing zero values "‹"‹and calculating correlations with AQI and the final step performs calculations with the LSTM model. The LSTM model which adds tuning parameters, namely with epoch 100, learning rate with a value of 0.001, and batch size with a value of 64, consistently shows a reduction in losses. The best results from the AQI, PM2.5, and PM10 features based on performance are MSE with the smallest value of 6.045, RMSE with the smallest value of 4.283, and MAE with a value of 2.757.
Stacking of DT, RF, and Gradient Boosting Algorithms for Classification of Building Damage Due to Earthquakes Ilmi, Nur Aqliah; Winarsih, Nurul Anisa Sri
Journal of Applied Informatics and Computing Vol. 9 No. 6 (2025): December 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i6.11272

Abstract

Classification of building damage levels due to earthquakes is an important aspect in disaster mitigation and post-disaster risk assessment. This study aims to improve classification accuracy on imbalanced data using an ensemble stacking method. It combines Decision Tree, Random Forest, and Gradient Boosting algorithms, with Logistic Regression as a meta-learner. The building damage dataset from the 2015 Gorkha Nepal earthquake underwent data cleaning, categorical transformation, normalization, and balancing using ADASYN. Evaluation showed that Random Forest was the best single model. The stacking model achieved the highest accuracy of 91.77% after balancing. These results show that stacking improves generalization and classification accuracy on imbalanced data. This suggests significant potential for integration into disaster decision-support systems that require fast, accurate building-damage assessment.
Spatiotemporal Analysis of Peatland Fire Hotspots and Fire Intensity in Riau Province Using MODIS–VIIRS Multisensor Satellite Data Najwa Ratu Afi; Ramadhan Rakhmat Sani; Ricardus Anggi Pramunendar; Nurul Anisa Sri Winarsih; Ika Novita Dewi
Journal of Applied Informatics and Computing Vol. 10 No. 3 (2026): June 2026
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v10i3.12686

Abstract

Peatland fires in Riau Province frequently occur during the dry season and contribute significantly to regional haze, environmental degradation and carbon emissions. Effective monitoring of these fires remains challenging due to their widespread distribution and varying intensity across peatland areas. This research aims to analyze the spatiotemporal characteristics of peatland fire hotspots in Riau Province using multisensor satellite observations from the NASA Fire Information for Resource Management System (FIRMS). The dataset integrates Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) data from the Suomi-NPP, NOAA-20 and NOAA-21 satellites. After applying filtering criteria of confidence ≥70% and Fire Radiative Power (FRP) ≥5 megawatts (MW), a total of 7,297 significant hotspots were identified during the July–October 2025 dry season. The results show that fire activity peaked in July with a maximum daily FRP of 25,611 MW and a monthly total of 65,120 MW, followed by a decline in September and a slight increase in October. The FRP distribution was highly right-skewed, with an average value of13.2 MW, while the most intense hotspots reached 189.4 MW. Estimated carbon dioxide (CO₂) emissions reached approximately 122,472 tons, indicating substantial environmental impacts. Spatial clustering and persistence analysis revealed several high-risk peatland zones with repeated fire occurrences. These findings demonstrate the importance of multisensor satellite monitoring for improving early fire detection, emission assessment and disaster mitigation strategies in peatland regions.
Co-Authors Abu Salam Adhitya Nugraha Ahmad Zainul Fanani Akmaludin Akbar Akner Yosha Ade Saputra Alvin, Fris Alzami, Farrikh Ardytha Luthfiarta Ashraf Alomoush Astuti, Yani Parti Azzahra, Tarissa Aura Catur Supriyanto Danny Oka Ratmana Danny Oka Ratmana Dewi Pergiwati Dhani, Iqbal Djaka, Thesa Permatasari Djaka Dwi Puji Prabowo, Dwi Puji Egia Rosi Subhiyakto, Egia Rosi Eko Hari Rachmawanto Epiphany Shavna Gracia Erlin Dolphina Etika Kartikadarma Fafaza, Safira Alya Fakhrurrozi Fakhrurrozi, Fakhrurrozi Filmada Ocky Saputra Filmada Ocky Saputra Fitriyani, Shelomita Guruh Fajar Shidik Hamid, Maulana As’an Ika Novita Dewi Ilmi, Nur Aqliah Imam Prayogo Pujiono Kartika, Gita Kurniawan, Defri Kusumawati, Yupie Mardiantara, Naya Alifiah az Azar Putri Miranti Alysha Zulia Larasati Moh Adzka Fawaid Muhammad Syaifur Rohman Muhammad Syaifur Rohman Mulyanto, Edy Najwa Ratu Afi Naufal Fawwazi Purwanto Purwanto Raihatuzzahra, Farah Rama Aria Megantara Ramadhan Rakhmat Sani Ramadhani, Irfan Wahyu Ratmana, Danny Oka Ricardus Anggi Pramunendar Rohman, Muhammad Syaifur Romadhoni, Mellynda Noor Saputra, Filmada Ocky Saraswati, Galuh Wilujeng Satria Andromeda, Rayhan Sekar Wangi, Sari Asih Septian Enggar Sukmana Sindhu Rakasiwi Sutrisno, Hendra Utomo, Danang Wahyu Wibowo, Alrico Rizki Yani Parti Astuti Yani Parti Astuti Zainal Arifin Hasibuan