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Journal : JOIN (Jurnal Online Informatika)

Enhancement of White Blood Cells Images using Shock Filtering Equation for Classification Problem Gregorius Vito; Putu Harry Gunawan
JOIN (Jurnal Online Informatika) Vol 6 No 2 (2021)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v6i2.739

Abstract

Medical image processing has developed rapidly in the last decade. The autodetection and classification of white blood cells (WBC) is one of the medical image processing applications. The analysis of WBC images has engaged researchers from medical also technology fields. Since WBC detection plays an essential role in the medical field, this paper presents a system for distinguishing and classifying WBC types: eosinophils, neutrophils, lymphocytes, and monocytes, using K-Nearest Neighbor (K-NN) and Logistic Regression (LR). This study aims to find the best accuracy of pre-processing images using original grayscale, shock filtering, and thresholding grayscale. The highest average accuracy in classifying WBC images in the conducting research is 43.54% using the LR algorithm from 2103 images. It is obtained from the combination of thresholding grayscale image and shock filtering equation to enhance the quality of an image. Overall, using two algorithms, KNN and LR, the classification accuracy can increase up to 12%.
Long Short-Term Memory Approach for Predicting Air Temperature In Indonesia Putu Harry Gunawan; Devi Munandar; Anis Zainia Farabiba
JOIN (Jurnal Online Informatika) Vol. 5 No 2 (2020)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v5i2.551

Abstract

Air temperature is one of the main factors for describing the weather behaviour in the earth. Since Indonesia is located on and near equator, then monitoring the air temperature is needed to determine either global climate change occurs or not. Climate change can have an impact on biological growth in various fields. For instance, climate change can affect the quality of production and growth of animal and plants. Therefore, air temperature prediction is important to meteorologists and Indonesian government to provide information in many sectors. Various prediction algorithms have been used to predict temperature and produce different accuracy. In this study, the deep learning method with Long Short-Term Memory (LSTM) model is used to predict air temperature. Here, the results show that LSTM model with one layer and Adaptive Moment Estimation (ADAM) optimizer produce accuracy which is 32% of , 0.068 of MAE and 0.99 of RMSE. Moreover, here, ADAM optimizer is found better than Stochastic Gradient Descent (SGD) optimizer.
Long Short-Term Memory Approach for Predicting Air Temperature In Indonesia Gunawan, Putu Harry; Munandar, Devi; Farabiba, Anis Zainia
JOIN (Jurnal Online Informatika) Vol. 5 No 2 (2020)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v5i2.551

Abstract

Air temperature is one of the main factors for describing the weather behaviour in the earth. Since Indonesia is located on and near equator, then monitoring the air temperature is needed to determine either global climate change occurs or not. Climate change can have an impact on biological growth in various fields. For instance, climate change can affect the quality of production and growth of animal and plants. Therefore, air temperature prediction is important to meteorologists and Indonesian government to provide information in many sectors. Various prediction algorithms have been used to predict temperature and produce different accuracy. In this study, the deep learning method with Long Short-Term Memory (LSTM) model is used to predict air temperature. Here, the results show that LSTM model with one layer and Adaptive Moment Estimation (ADAM) optimizer produce accuracy which is 32% of , 0.068 of MAE and 0.99 of RMSE. Moreover, here, ADAM optimizer is found better than Stochastic Gradient Descent (SGD) optimizer.
Enhancement of White Blood Cells Images using Shock Filtering Equation for Classification Problem Vito, Gregorius; Gunawan, Putu Harry
JOIN (Jurnal Online Informatika) Vol 6 No 2 (2021)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v6i2.739

Abstract

Medical image processing has developed rapidly in the last decade. The autodetection and classification of white blood cells (WBC) is one of the medical image processing applications. The analysis of WBC images has engaged researchers from medical also technology fields. Since WBC detection plays an essential role in the medical field, this paper presents a system for distinguishing and classifying WBC types: eosinophils, neutrophils, lymphocytes, and monocytes, using K-Nearest Neighbor (K-NN) and Logistic Regression (LR). This study aims to find the best accuracy of pre-processing images using original grayscale, shock filtering, and thresholding grayscale. The highest average accuracy in classifying WBC images in the conducting research is 43.54% using the LR algorithm from 2103 images. It is obtained from the combination of thresholding grayscale image and shock filtering equation to enhance the quality of an image. Overall, using two algorithms, KNN and LR, the classification accuracy can increase up to 12%.
Co-Authors Abi Rafdhi Hernandy Abi Rafdhi Hernandy Adam Ichwanul Ichsan Ade Romadhony Aditya Firman Ihsan Adrin, Athaya Fatharani Afrahtama, Ariiq Agung Ferdiana Agung Toto Wibowo Ahmad Lubis Ghozali Aniq Atiqi Rohmawati Anis Zainia Farabiba Annisa Aditsania Aprianti Putri Sujana Aquarini, Narita Ardhito Utomo Ardhito Utomo Ari Satrio Arnanti Primiana Yuniati Bagus Gigih Adisalam Bambang Ari Wahyudi Bambang Pudjoatmodjo Bambang Pudjotatmodjo Bedy Purnama Conny Tria Shafira Dede Tarwidi Deni Saepudin Devi Munandar Devi Munandar, Devi Didit Adytia Dinda Fitri Irandi Djoko Murdowo Dodi Wisaksono Sudiharto Eka Ismantohadi Ema Rachmawati Ema Rachmawati Ema Rachmawati Fadhil Lobma Fakhrudin, Abdul Daffa Farabiba, Anis Zainia Fat'hah Noor Prawira Fat’hah Noor Prawira Fat’hah Noor Prawira Fazmah Arif Yulianto Fenty Alia Fityanul Akhyar Friska Fristella Friska Fristella Gloria Flourin Maitimu Gregorius Vito Hamonangan, Ricardo Hasbi Rabbani Hasna Aqila Raihana I Gde Made Bagus Nurseta Wijaya Indwiarti Irandi, Dinda Fitri Irma Palupi Iryanto Iryanto Jondri Jondri Lazuardy Azhari Bacharuddin Noor Ledya Novamizanti Lukman Nurwahidin M. Sofyan Bahrum Juniardi Mahmud Imrona Muhammad Arzaki Muhammad Daffa Dhiyaulhaq Muhammad Hablul Barri Muhammad Ilyas Muhtar, Na'il Muta'aly Muthi, Muhammad Ariq Naila Al Mahmuda Narita Aquarini Nur Nining Aulia Nurul Ikhsan Panuluh, Bagus Patria, Widya Yudha Prabasworo, Bhanu Pratama, Aditya Nur Pratama, Rezqie Hardi Prawita, Fat’hah Noor Pudjoadmojo, Bambang Rachmad Ryan Feryal Rajib Sainan Zulkifli Ramadhan Aditya Ratri Wulandari Revandi, Tyo Rifki Wijaya Rikman Aherliwan Rudawan Rimba Whidiana Ciptasari Rita Purnamasari Satria Mandala Selly Meliana Seraphina, Yessica Anglila Siti Fitria Yonalia Solin, Chintya Annisah Sri Soedewi Tb Dzulfiqar Alhafidh Tjokorda Agung Budi Wirayuda Tora Fahrudin Vina Putri Damartya Vito, Gregorius Wicaksono, Candra Kus Khoiri Wirayudha, Tjokorda Agung Budi Yoreza Mandala Putra ZK Abdurahman Baizal