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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Rekam Medis dan Informasi Kesehatan Jurnal Listrik, Instrumentasi, dan Elektronika Terapan Jurnal Informatika: Jurnal Pengembangan IT
Dinar Nugroho Pratomo
Department Of Electrical Engineering And Informatics, Universitas Gadjah Mada, Yogyakarta
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering Health Professions

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Perancangan Prototipe Aplikasi e-Incident Berbasis Android di Rumah Sakit PKU Muhammadiyah Gamping Dian Herawati; Nia Fararid Askar; Dinar Nugroho Pratomo
Jurnal Rekam Medis dan Informasi Kesehatan Vol 5, No 1 (2022): Maret 2022
Publisher : Poltekkes Kemenkes Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (236.37 KB) | DOI: 10.31983/jrmik.v5i1.8403

Abstract

Recording and reporting of accidents and occupational diseases is a part of health information system that must be owned by the hospital. One of the efforts to achieve zero accidents is to take advantage of information technology such as android in increasing the effectiveness of recording and reporting OHS incident. The purpose of the study was to analyze the needs and create a prototype of an android based application. This research is qualitative with research and development design. The results show that it is necessary to add an incident reporting component related to hazardous and toxic substances. The application can answers the problems such as the delay in manual reporting and the documents are still fragmented. An e-incident application has a menu for reporting incidents, occupational diseases, and hazardous toxic substances. The menus have been made in accordance with OHS incident reporting standards in hospitals. The conclusion is that an android based e-incident application prototype has been made and can be accepted by users because it provides convenience and accuracy of data in OHS reporting in hospitals.
Desain dan Implementasi Sistem Navigasi pada Automated Guided Vehicle (AGV) Fakih Irsyadi; Dinar Nugroho Pratomo; Sugeng Julianto; Muhammad Shofuwan Anwar; Alfonzo Aruga Paripurna Barus
Jurnal Listrik, Instrumentasi, dan Elektronika Terapan Vol 2, No 1 (2021)
Publisher : Departemen Teknik Elektro dan Informatika Sekolah Vokasi UGM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/juliet.v2i1.64830

Abstract

This research aims to build mechanical system of Automated Guided Vehicle (AGV) and navigation system for AGV.  The navigation system consists of RFID reader and rotary encoder. The testing result show that mechanical system of AGV was successfully finished. There is a mechanical problem on drive system of AGV. Each part of navigation system works well according to design. Line sensor can be used for path detection with the given threshold values. Encoder can be used to measure the speed of AGV with the maximum error accuracy less than 2 rpm. This result shows that every part of AGV is ready to run localization and navigation algorithm, even though, it needs to do some improvement on driving parts.
Expert System for Identification of Skin Disease in Humans using Naive Bayes Classifier Method on Web Dinar Nugroho Pratomo; Diyah Utami Kusumaning Putri
Jurnal Informatika: Jurnal Pengembangan IT Vol 7, No 1 (2022): JPIT, Januari 2022
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v7i1.3098

Abstract

Expert System Identification of Skin Disease in Human is an application that adopts expert knowledge, in this case, a dermatologist, to identify skin diseases in humans found in Indonesia. This expert system is constructed using a naive bayes classifier. To make the system interface more dynamic and easy to access by anyone, this system is made based on the web. Through this web application, users can consult with a system like an expert to know the skin disease that occurs to the human and find the correct treatment to solve the problems.
Hybrid convolutional neural networks-support vector machine classifier with dropout for Javanese character recognition Diyah Utami Kusumaning Putri; Dinar Nugroho Pratomo; Azhari Azhari
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 21, No 2: April 2023
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v21i2.24266

Abstract

This research paper explores the hybrid models for Javanese character recognition using 15600 characters gathered from digital and handwritten sources. The hybrid model combines the merit of deep learning using convolutional neural networks (CNN) to involve feature extraction and a machine learning classifier using support vector machine (SVM). The dropout layer also manages overfitting problems and enhances training accuracy. For evaluation purposes, we also compared CNN models with three different architectures with multilayer perceptron (MLP) models with one and two hidden layer(s). In this research, we evaluated three variants of CNN architectures and the hybrid CNN-SVM models on both the accuracy of classification and training time. The experimental outcomes showed that the classification performances of all CNN models outperform the classification performances of both MLP models. The highest testing accuracy for basic CNN is 94.2% when using model 3 CNN. The increment of hidden layers to the MLP model just slightly enhances the accuracy. Furthermore, the hybrid model gained the highest accuracy result of 98.35% for classifying the testing data when combining model 3 CNN with the SVM classifier. We get that the hybrid CNN-SVM model can enhance the accuracy results in the Javanese characters recognition.
Co-Authors Alfonzo Aruga Paripurna Barus Azhari Azhari Dian Herawati Diyah Utami Kusumaning Putri Diyah Utami Kusumaning Putri Fakih Irsyadi Muhammad Shofuwan Anwar Nia Fararid Askar Sugeng Julianto