Garuda - Garba Rujukan Digital

The architecture social media and online newspaper credibility measurement for fake news detection Rakhmat Arianto; Harco Leslie Hendric Spits Warnars; Edi Abdurachman; Yaya Heryadi; Ford Lumban Gaol
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 17, No 2: April 2019
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v17i2.11779

Social media is one of the communication media favored by people in the world, especially in Indonesia. This is evidenced by the results of the APJII survey which shows that the majority of Indonesians use social media in their daily activities. One of the advantages of social media is the dissemination of information faster than conventional media so that the quality of information disseminated is lower than conventional media due to the process of disseminating information not through the filter process. By measuring the level of credibility of the online newspaper based on the time credibility, website credibility, and message credibility factors and measuring the level of credibility on social media based on the time credibility, Social Media Credibility, and Message Credibility factors with different levels of weight, it will produce a news likelihood level it's fake news or facts.

Weather Forecasting Using Merged Long Short-term Memory Model Afan Galih Salman; Yaya Heryadi; Edi Abdurahman; Wayan Suparta
Bulletin of Electrical Engineering and Informatics Vol 7, No 3: September 2018
Publisher : Institute of Advanced Engineering and Science

Over decades, weather forecasting has attracted researchers from worldwide communities due to itssignificant effect to global human life ranging from agriculture, air trafic control to public security. Although formal study on weather forecasting has been started since 19th century, research attention to weather forecasting tasks increased significantly after weather big data are widely available. This paper proposed merged-Long Short-term Memory for forecasting ground visibility at the airpot using timeseries of predictor variable combined with another variable as moderating variable. The proposed models were tested using weather timeseries data at Hang Nadim Airport, Batam. The experiment results showedthe best average accuracy for forecasting visibility using merged Long Short-term Memory model and temperature and dew point as a moderating variable was (88.6%); whilst, using basic Long Short-term Memory without moderating variablewasonly (83.8%) respectively (increased by 4.8%).

Weather Forecasting Using Merged Long Short-term Memory Model Afan Galih Salman; Yaya Heryadi; Edi Abdurahman; Wayan Suparta
Bulletin of Electrical Engineering and Informatics Vol 7, No 3: September 2018
Publisher : Institute of Advanced Engineering and Science

Over decades, weather forecasting has attracted researchers from worldwide communities due to itssignificant effect to global human life ranging from agriculture, air trafic control to public security. Although formal study on weather forecasting has been started since 19th century, research attention to weather forecasting tasks increased significantly after weather big data are widely available. This paper proposed merged-Long Short-term Memory for forecasting ground visibility at the airpot using timeseries of predictor variable combined with another variable as moderating variable. The proposed models were tested using weather timeseries data at Hang Nadim Airport, Batam. The experiment results showedthe best average accuracy for forecasting visibility using merged Long Short-term Memory model and temperature and dew point as a moderating variable was (88.6%); whilst, using basic Long Short-term Memory without moderating variablewasonly (83.8%) respectively (increased by 4.8%).

Weather Forecasting Using Merged Long Short-term Memory Model Afan Galih Salman; Yaya Heryadi; Edi Abdurahman; Wayan Suparta
Bulletin of Electrical Engineering and Informatics Vol 7, No 3: September 2018
Publisher : Institute of Advanced Engineering and Science

Over decades, weather forecasting has attracted researchers from worldwide communities due to itssignificant effect to global human life ranging from agriculture, air trafic control to public security. Although formal study on weather forecasting has been started since 19th century, research attention to weather forecasting tasks increased significantly after weather big data are widely available. This paper proposed merged-Long Short-term Memory for forecasting ground visibility at the airpot using timeseries of predictor variable combined with another variable as moderating variable. The proposed models were tested using weather timeseries data at Hang Nadim Airport, Batam. The experiment results showedthe best average accuracy for forecasting visibility using merged Long Short-term Memory model and temperature and dew point as a moderating variable was (88.6%); whilst, using basic Long Short-term Memory without moderating variablewasonly (83.8%) respectively (increased by 4.8%).

Aplikasi Informasi Kesehatan dan Diagnosa Penyakit Jantung Berbasis Android Raymond Bahana; Indrajani Indrajani; Raymond Kosala; Yaya Heryadi
Seminar Nasional Teknologi Informasi Komunikasi dan Industri 2018: SNTIKI 10
Publisher : UIN Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (400.861 KB)

Tujuan dari penelitian ini adalah merancang dan membangun aplikasi yang memberikan informasi sepuluh jenis penyakit paling sering menjadi penyebab kematian di Indonesia. Informasi yang diberikan seperti informasi kesehatan, artikel, video, info rumah sakit terdekat yang dapat di-tracking oleh pengguna, serta gambaran dan penjelasan kepada pengguna, untuk mendiagnosa lebih dini penyakit jantung berdasarkan gejala-gejala atau penyebab yang ada dengan cepat dan tepat. Hasil penelitian ini dapat memberikan gambaran mengenai penyakit jantung yang dialami dan memberikan pengetahuan tentang jenis-jenis penyakit jantung dan gejala-gejala, penyebab disertai tindakan yang harus diambil untuk pencegahannya sebagai langkah awal dalam mengantisipasi penyakit jantung. Pembuatan aplikasi berbasis android ini menggunakan teknologi Java, JSON, PHP, Web hosting. Dari kesimpulan, pada diagnosa penyakit jantung dengan menggunakan machine learning dengan hasil prediksi penyakit menggunakan ROC, mendapat tingkat akurasi sebesar 82%; menggunakan model k-NN (k = 7).

CHATBOT IMPLEMENTATION TO SUPPORT MOBILE LEARNING DURING NCOVID19 PANDEMIC Putri Sakinah; Yaya Heryadi
Jurnal Ipteks Terapan (Research Of Applied Science And Education ) Vol. 14 No. 3 (2020): Re Publish Issue
Publisher : Lembaga Layanan Pendidikan Tinggi Wilayah X

This paper presents the results of chatbot implementation to support mobile learning in higher education. Thegoal of the chatbot implementation in this study, among others, is to address high interest of higher educationin Indonesia toward online learning support mainly during the resent NCOVID19 pandemic in which most oflearning process are implemented using online learning mode. The proposed chatbot prototype has been testedin the University of Andalas, Sumatera, Indonesia. The chatbot is designed using standard softwareengineering method and implemented using Android-based mobile application flatform. Respondents for thechatbot evaluation are chosen based on purposive random sampling among students of Department ofSociology as sampling population. The data collecting is implemented using survey method with selfadministered questionnaires. The overall evaluation results showed that the designed and implementation hasmet the students’ expectation. Interestingly most of the respondents showed their interest to use the chatbot

CHATBOT IMPLEMENTATION TO SUPPORT MOBILE LEARNING DURING NCOVID19 PANDEMIC Putri Sakinah; Yaya Heryadi
Jurnal Ipteks Terapan Vol. 14 No. 3 (2020): Re Publish Issue
Publisher : Lembaga Layanan Pendidikan Tinggi Wilayah X

This paper presents the results of chatbot implementation to support mobile learning in higher education. Thegoal of the chatbot implementation in this study, among others, is to address high interest of higher educationin Indonesia toward online learning support mainly during the resent NCOVID19 pandemic in which most oflearning process are implemented using online learning mode. The proposed chatbot prototype has been testedin the University of Andalas, Sumatera, Indonesia. The chatbot is designed using standard softwareengineering method and implemented using Android-based mobile application flatform. Respondents for thechatbot evaluation are chosen based on purposive random sampling among students of Department ofSociology as sampling population. The data collecting is implemented using survey method with selfadministered questionnaires. The overall evaluation results showed that the designed and implementation hasmet the students’ expectation. Interestingly most of the respondents showed their interest to use the chatbot

Teknologi Baru Pada Pendidikan Tinggi Menuju Revolusi Industri 4.0: Studi Kasus Indonesia dan Malaysia Dina Fitria Murad; Silvia Ayunda Murad; Rosilah Hassan; Yaya Heryadi; Bambang Dwi Wijanarko; Titan Titan
JSINBIS (Jurnal Sistem Informasi Bisnis) Vol 11, No 2 (2021): Volume 11 Nomor 2 Tahun 2021
Publisher : Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21456/vol11iss2pp139-145

IoT with E-learning is intended to support data collection from devices and share to other devices in use for effective E-learning applications from Smart Campus. This study aims to conduct studies related to online learning models by utilizing Internet of Everything (IoE) technology to support Revolution 4.0. This study aims to support the latest communication paradigm in which the objects of everyday life will be equipped with a series of appropriate protocols and enable them to communicate well with each other as part of the internet. IoE will help improve learning by leveraging the large subject data generated by these objects to provide dynamic services to educators, learners, and even content developers. Using qualitative research methods This research uses a questionnaire to find out the views and assessments of the community in this case online learners regarding online learning as one of the impacts of the Covid-19 pandemic and produces an online learning model that is supported by an integrated system between learning media such as LMS and devices. others use IoE. The results of this study support the implementation of Smart campuses that allow the use of IoE methodologies to make them always ready in certain network areas.

End-to-End Steering Angle Prediction for Autonomous Car Using Vision Transformer Ilvico Sonata; Yaya Heryadi; Antoni Wibowo; Widodo Budiharto
CommIT (Communication and Information Technology) Journal Vol. 17 No. 2 (2023): CommIT Journal
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/commit.v17i2.8425

The development of autonomous cars is currently increasing along with the need for safe and comfortable autonomous cars. The development of autonomous cars cannot be separated from the use of deep learning to determine the steering angle of an autonomous car according to the road conditions it faces. In the research, a Vision Transformer (ViT) model is proposed to determine the steering angle based on images taken using a front-facing camera on an autonomous car. The dataset used to train ViT is a public dataset. The dataset is taken from streets around Rancho Palos Verdes and San Pedro, California. The number of images is 45,560, which are labeled with the steering angle value for each image. The proposed model can predict steering angle well. Then, the steering angle prediction results are compared using the same dataset with existing models. The experimental results show that the proposed model has better accuracy regarding the resulting MSE value of 2,991 compared to the CNN-based model of 5,358 and the CNN-LSTM combination model of 4,065. From the results of this experiment, the ViT model can replace the existing model, namely the CNN model and the combination model between CNN and LSTM, in predicting the steering angle of an autonomous car.

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