Article Per Year (5 Year)
p-Index From 2020 - 2025
0.659
P-Index
This Author published in this journals
All Journal Jurnal Informatika Upgris Jurnal Abdimas Bina Bangsa Journal of Information System and Computer
Eko Riyanto
STMIK Himsya Semarang
Computer Science & IT Education Languange, Linguistic, Communication & Media Mathematics Social Sciences Other

Published : 5 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search
Journal : Jurnal Informatika Upgris

 1 
PERAMALAN HARGA SAHAM MENGGUNAKAN JARINGAN SYARAF TIRUAN SECARA SUPERVISED LEARNING DENGAN ALGORITMA BACKPROPAGATION Eko Riyanto
Jurnal Informatika Upgris Vol 3, No 2: Desember (2017)
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/jiu.v3i2.1899

Abstract

Stock price prediction is useful for investors to see how the prospects of a company's stock investment in the future. Stock price prediction can be used to anticipate the deviation of stock prices. It can also helps investors in decision making. Artificial Neural Networks do not require mathematical models but data from problems to be solved. Information is conveyed through the data, and the Artificial Neural Network filters the information through training. Therefore, Artificial Neural Network is appropriate to solve the problem of stock price prediction.            Learning method that will be used to predict stock price is Supervised Learning with Backpropagation algorithm. With this algorithm, networks can be trained using stock price data from the previous time, classify it and adjust network link weight as new input and forecast future stock prices. By using ANN, time series prediction is more accurate. After analyzing the problem of stock price movement system, the writer can know the pattern of what variables will be taken for further insert into the stock price forecasting system.            This application can be used for stock price forecasting technique, so it will be useful for beginner investor as well as advanced investor as reference to invest in capital market. Implementing supervised learning backpropagation method will get accurate forecasting results more than 98%.Keyword - artificial neural network, stock, backpropagation.
SISTEM KEAMANAN RUMAH BERBASIS ANDROID DENGAN RASBERRY Pi Eko Riyanto
Jurnal Informatika Upgris Vol 5, No 1: Juni (2019)
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/jiu.v5i1.3214

Abstract

Smart Home is one of the tools that is developed for ease of automation of smart home management from the start of address, security, comfort, savings, through automation with Android. In designing a micro home security system controller using raspberry pi 3 and Android smartphones that can reduce the number of criminal acts of burglary door. This tool consists of an electro magnetic door lock called a solenoid door lock.This solenoid key is placed on the door of the house for security. The design of this home door security system utilizes Raspberyy pi b + as a control device from near and far by utilizing the wifi network and sms gateway to control opening and closing the home door lock that is controlled via an android mobile. Through web bootstrap that will display the results captured by the camera to provide a home situation every time someone enters.This house door security system that has been successfully built and tested with the working principle if there is someone who forces or breaks the house door in a closed condition, the system will activate a warning or alarm by sounding the buzzer¸ because there is an LDR sensor connected to one switch connected to the solenoid key that results, if the key is opened with a security system then the LDR sensor will turn off and there will be no alarm, but if it is forced to break the LDR sensor will activate and read the movement of the door so that the reaction occurs and the buzzer alarm will sound. This security system is a solution to increase the level of home security ¸ besides this sophisticated system is very easy to use and integrated with android smartphones
APLIKASI PRESENSI DENGAN BARCODE SCANNER DAN RASPBERRY PI TERINTEGRASI BOT TELEGRAM Ana Soraya; Eko Riyanto; - Solikhin
Jurnal Informatika Upgris Vol 6, No 2: Desember (2020)
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/jiu.v6i2.6567

Abstract

In this research, the presence of students' attendance at the Taruna Bulu Vocational School has been observed where the system used is still manual so it requires a computerized system so that archiving is efficient and the homeroom teacher and student guardian can control student attendance.In conducting research, the author uses two sources of data, namely primary data which includes all data obtained by the author directly from sources obtained from the Head of Vocational School Hair Training and secondary data which includes all information obtained from other data that can be used as a support and related to the research theme. These data sources are documents concerning the student attendance information system procedures. In designing the system, it is made based on the needs of SMK Taruna Bulu which is then implemented using the PHP My SQL programming language and integrated Telegram Bot so that it can later be implemented on Taruna Bulu Vocational School.
Co-Authors Agus Alwi Mashuri Ana Soraya Mahmudi Mahmudi Muhammad Aji Saputra Solikhin Solikhin