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All Journal ComEngApp : Computer Engineering and Applications Journal Jurnal Manajemen Terapan dan Keuangan Statistika Media Kesehatan Masyarakat Indonesia Jurnal Ilmu Lingkungan Jurnal Pendidikan Jurnal Floratek Jurnal Diskursus Islam Jurnal Online Mahasiswa (JOM) Bidang Teknik dan Sains Jurnal Online Mahasiswa (JOM) Bidang Ilmu Hukum Jurnal Online Mahasiswa (JOM) Bidang Keguruan dan Ilmu Pendidikan FIAT JUSTISIA: Jurnal Ilmu Hukum Hukum Islam ICON-CSE AJIE (Asian Journal of Innovation and Entrepreneurship) Jurnal Ilmiah Mahasiswa Pendidikan Jasmani, Kesehatan dan Rekreasi Jurnal Pendidikan Teknik Mesin Al-Kimia JUSIM (Jurnal Sistem Informasi Musirawas) Perada: Jurnal Studi Islam Kawasan Melayu Jurnal Teknik Mesin JURNAL PENELITIAN SEJARAH DAN BUDAYA

Firdaus Firdaus

Unknown Affiliation

Author-ID : 470485

Religion Arts Humanities Automotive Engineering Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Public Health Social Sciences Other

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Title

A Deep Learning Approach to Integrate Medical Big Data for Improving Health Services in Indonesia Bambang Tutuko; Siti Nurmaini; Muhammad Naufal Rachmatullah; Annisa Darmawahyuni; Firdaus Firdaus
Computer Engineering and Applications Journal Vol 9 No 1 (2020)
Publisher : Universitas Sriwijaya

Medical Informatics to support health services in Indonesia is proposed in this paper. The focuses of paper to the analysis of Big Data for health care purposes with the aim of improving and developing clinical decision support systems (CDSS) or assessing medical data both for quality assurance and accessibility of health services. Electronic health records (EHR) are very rich in medical data sourced from patient. All the data can be aggregated to produce information, which includes medical history details such as, diagnostic tests, medicines and treatment plans, immunization records, allergies, radiological images, multivariate sensors device, laboratories, and test results. All the information will provide a valuable understanding of disease management system. In Indonesia country, with many rural areas with limited doctor it is an important case to investigate. Data mining about large-scale individuals and populations through EHRs can be combined with mobile networks and social media to inform about health and public policy. To support this research, many researchers have been applied the Deep Learning (DL) approach in data-mining problems related to health informatics. However, in practice, the use of DL is still questionable due to achieve optimal performance, relatively large data and resources are needed, given there are other learning algorithms that are relatively fast but produce close performance with fewer resources and parameterization, and have a better interpretability. In this paper, the advantage of Deep Learning to design medical informatics is described, due to such an approach is needed to make a good CDSS of health services.

Cloud-based ECG Interpretation of Atrial Fibrillation Condition with Deep Learning Technique Bambang Tutuko; Rossi Passarella; Firdaus Firdaus; Muhammad Naufal Rachmatullah; Annisa Darmawahyuni; Ade Iriani Sapitri; Siti Nurmaini
Computer Engineering and Applications Journal Vol 10 No 1 (2021)
Publisher : Universitas Sriwijaya

The prevalent type of arrhythmia associated with an increased risk of stroke and mortality is atrial fibrillation (AF). It is a known priority to identify AF before the first complication occurs. No previous studies have explored the feasibility of conducting AF screening using a deep learning (DL) algorithm (integrated cloud-computing) telehealth surveillance system. Hence, we address this problem. The goal of this research was to determine the feasibility of AF screening using an embedded cloud-computing algorithm in nonmetropolitan areas using a telehealth surveillance system. By using a single-lead electrocardiogram (ECG) recorder, we performed a prospective AF screening study. Both ECG measurements were evaluated and interpreted by the cloud-computing algorithm and a cardiologist on the telehealth monitoring system. The proposed cloud-computing based on Convolutional Neural Network (CNN) algorithm for AF detection had an accuracy of 99% sensitivity of 98%, and specificity of 99%. The overall satisfaction performance for the process of AF screening, and it is feasible to conduct AF screening by using a telehealth monitoring system containing an embedded cloud-computing algorithm.

Wireless Controlling for Garbage Robot (G-Bot) Nyayu Latifah Husni; Robi Robi; Ekawati Prihatini; Ade Silvia Handayani; Sabilal Rasyad; Firdaus Firdaus
Computer Engineering and Applications Journal Vol 10 No 2 (2021)
Publisher : Universitas Sriwijaya

This paper presents one of the solutions in overcoming the garbage problems. The people sometimes feel too lazy to throw the garbage into proper place due to their habit that has been grown since little kids. In this research, A G-Bot, a robot that has function as the garbage container is offered. By using an Internet of Things (IoT) application, the users can control the motion of the G-Bot wirelessly, so that it can move to the users’ desired location. In addition, the covers of the G-Bot can also be opened using smart phones that connected to the G-Bot. A Blynk that acts as the IoT Application is used in order to set up the G-Bot communication. From the experimental result, it can be concluded that the proposed research has been successful to be implemented. The users can move the G-Bot to the targeted location wirelessly, and they can also open and close the G-Bot’s lids wirelessly trough the mobile phones.

Identification of Indonesian Authors Using Deep Neural Networks Firdaus Firdaus; Irvan Fahreza; Siti Nurmaini; Annisa Darmawahyuni; Ade Iriani Sapitri; Muhammad Naufal Rachmatullah; Suci Dwi Lestari; Muhammad Fachrurrozi; Mira Afrina; Bayu Wijaya Putra
Computer Engineering and Applications Journal Vol 11 No 1 (2022)
Publisher : Universitas Sriwijaya

Author Name Disambiguation (AND) is a problem that occurs when a set of publications contains ambiguous names of authors, i.e. the same author may appear with different names (synonyms) in other published papers, or author (authors) who may be different who may have the same name (homonym). In this final project, we will design a model with a Deep Neural Network (DNN) classifier. The dataset used in this final project uses primary data sourced from the Scopus website. This research focuses on integrating data from Indonesian authors. Parameters accuracy, sensitivity and precision are standard benchmarks to determine the performance of the method used to solve AND problems. The best DNN classification model achieves 99.9936% Accuracy, 93.1433% Sensitivity, 94.3733% Precision. Then for the highest performance measurement, the case of Non Synonym-Homonym (SH) has 99.9967% Accuracy, 96.7388% Sensitivity, and 97.5102% Precision.

Co-Authors , Dasrol Abd. Wahid Wahab Abdul Kodir Jailani Achmad Abubakar Ade Iriani Sapitri Ade Silvia Handayani Ahmad Rifai Ahmad Zabidi Aldo Virgiansyah Alfian Rusdy Anggi Fitri Annisa Darmawahyuni Annisa Desria Utami Arbi Wahyu Ardiyansyah Ardiyansyah Ari Gustia Warman Ario Putra Arni Novi Sihombing Arrahman Arsista Audesti Nindya Azet Purnama Bambang Tutuko Bayu Wijaya Putra Bustamam Bustamam Citra Rahmawati Lubis Davit Rahmadan Dedek S Lumban Gaol Dessy Artina Dian Yayan Sukma, Dian Yayan Dini Azani Edy Ervianto Efri Diah Utami Ekawati Prihatini Ela Aprida Nafliana Emilda Firdaus Erdianto Erdianto Ewa Kukuh juwanda Fahrul Rhozi Fauzi Fauzi Feranita Feranita Fikri Al Mansur Fitratul Mubaraq Gladysha Indahcantika Mazalio Haniva Rahmadani Hasianna Nopina Situmorang Hasnah Hasnah Hayatul Ismi Hendri Agustin Sibarani Hendri Marhadi Hergo Afrizon Husni Husni Husni, Nyayu Latifah Ifwandi Ifwandi Iga S. Syahri Ilham Rijab Irfan Hamdani Irvan Fahreza Ishak Erawadi Barutu Ivan Ryian Ewaldo Juni Kardi Kamaluddin Abu Nawas Katrin Roosita Khoerudin Khoerudin Ledy Diana Leo Valentino Lukman Hakim M Aldion Rinaldi M Iqbal Nasir M Putra Nurjanah M. Dahlan M M. Wahyu Nugraha Maming Maming Martadinata, A. Taqwa Maryati Bachtiar Mira Afrina Mohd Yogi Yusuf Muhamad Al Khausar Muhammad Fachrurrozi Muhammad Farqi Muhammad Fathra Fahasta Muhammad Galib Muhammad Ibrahim MUHAMMAD ILHAM Muhammad Naufal Rachmatullah Muhammad Sayuthi Muhammad Sholeh Nasriadi Dali Nazri Nazri Niky Sudarmantoro Nota Effiandi Noveri L M Novia Fatriyani Nur Rabiah Mardatila Nurhalim Nurhalim Prima Prima Pusaka, Semerdanta Rahmayani Indrasari Rakiman Rakiman Reski Hidayat Retnaningsih Retnaningsih Reza Al Mattin Reza Novia Restita Ridho Hanif Farza Riko Simalango Rimbawan , Riska Fitriani Rizky Johari Robby Dhavitra Robi Robi Rossi Passarella Sabilal Rasyad Sandi Firman Nanda Sarah Nanda Jelita Siti Hafsah Siti Nurmaini Sri Anna Marliyati Sri Fitri Sri Yani Yolanda Suci Dwi Lestari Sukim Sukim Sutri Lasdienti Syafiqa Tiara Ayunda Syahri Ramadhan Syahrilfuddin Syahrilfuddin Thamrin Thamrin TJUT CHAMZURNI Togi Sugiono Torang Harison Tumpak Dolok Stepan Simarmata Ulfia Hasanah Upasana Narang Wildaniati Wildaniati Winner Inra Jefferson Batubara Wita Ananda Chikita Yudhi Fasrah Ilahi Yuli Yetri Yundri Akhyar Yusuf Ridho Surya Dharma Nainggolan Zalisman Zalisman Zikri Afdal Zuyasna Zuyasna

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