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All Journal CESS (Journal of Computer Engineering, System and Science) InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Jurnal Infomedia KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) Journal of Computer System and Informatics (JoSYC) Bulletin of Information Technology (BIT) Prosiding Snastikom Jurnal Sistim Informasi dan Teknologi Prosiding Seminar Nasional Teknik UISU (SEMNASTEK)
Herdianto Herdianto
Dosen Sistem Komputer Universitas Pembangunan Panca Budi Medan Jl Gatot Subroto KM 4,5, Medan
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Library & Information Science

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Journal : prosiding snastikom

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PERANCANGAN PEMBANGKIT GELOMBANG ULTRASONIC VARIABEL MENGGUNAKAN MIKROKONTROLER ATMEGA 16 Herdianto; Adisastra Pengalaman Tarigan
SEMINAR NASIONAL TEKNOLOGI INFORMASI & KOMUNIKASI Vol. 1 No. 1 (2020): PROSIDING SNASTIKOM 2020
Publisher : Universitas Harapan Medan

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Abstract

One of the factors causing the decline in national rice production is the attack of pests on rice. Based on data obtained from the agricultural department which has been processed by local data, it is known that there are 6 types of pests that attack rice plants in Indonesia, namely brown planthoppers, rats, rice stem borer, blast, kresek leaves and tungro. One method that can be used to repel pests in rice is by utilizing ultrasonic waves but is still limited to a range of only 4 meters in intensity. Therefore, a research aimed at generating ultrasonic waves will be carried out with the intensity of the ultrasonic wave range reaching 20 meters. The stages of research carried out include collecting data, analyzing data, designing circuit design, implementing circuit design, testing circuit design implementation and testing circuit design implementation. The ultrasonic wave generator designed in this study consists of 2 parts, namely a frequency generator of 20 - 50Khz and an amplifier of the output amplitude. Tests carried out in the research are still on the frequency generator section and the results show that the frequency variation of 20 - 50Khz can be produced properly by the ATMEGA 16 microcontroller.
Klasifikasi Objek Menggunakan Metode Convolutional Neural Network (CNN) H Herdianto
SNASTIKOM Vol. 1 No. 01 (2022): SEMINAR NASIONAL TEKNOLOGI INFORMASI & KOMUNIKASI (SNASTIKOM) 2022
Publisher : Unit Pengelola Jurnal Universitas Harapan Medan

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Abstract

Objects can be interpreted as all inanimate and living things that have various shapes and sizes. For humans to determine the presence of objects, to classify and estimate the distance of objects around them is not difficult. But for a computer to do the work mentioned above with an accuracy level that reaches up to greater than 90% is not easy. Object detection is important in the field of computer vision because it is used to monitor and track objects, while robots that use cameras as sensors are used to avoid obstacles, follow objects, classify and so on. Therefore the purpose of this study was to determine the level of accuracy of the CNN method in classifying objects, especially handwriting. The steps used to complete this research were literature study, collecting digital image data, determining training and testing data, designing the CNN program, conducting training and testing. From the results of testing the CNN method that has been carried out, it is known that the level of accuracy in classifying handwritten forms reaches 90%.            
Co-Authors Adisastra Pengalaman Tarigan Amin, Muhammad Ari Pratama Aulia Manurung Ayu Nuriana Sebayang Chairul Rizal Darmeli Nasution Dewi Mahrani Rangkuty Fery Anugrah Hidayati Purnama Lubis Mita Mutiara Zora Muhammad Hasanuddin Munadi Munadi Mursyidah . Rusli Rusli Silvia Anggraini Ucmariance