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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

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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.
Perbandingan Tingkat Akurasi Prediksi Peningkatan Kasus Positif Covid-19 antara Metode Neural Network Backpropagation dan Long Short Term Memory (LSTM) Agus Alwi Mashuri; Eko Riyanto
Jurnal Informatika Upgris Vol 8, No 2: Desember 2022
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/jiu.v8i2.13513

Abstract

The COVID-19 (Coronavirus) pandemic is likely to be one of the most serious globalproblems in the past year. Countries do not have similar experiences with the spreadof the virus and its effects from various fields. Estimating the number of previous casesof COVID-19 can help make decisions in the form of actions and plans to prevent thevirus. This study aims to provide a forecasting model that predicts confirmed COVID-19 cases in the city of Semarang. This study applies a machine learning algorithm,namely the Recurrent Neural Network (RNN) to predict COVID-19 cases in the city ofSemarang. The process of fine-tuning each model is described in this study andnumerical comparisons between the two models are concluded using differentevaluation measures; mean sequence error (MSE).
SMART HYDROPONIC BERBASIS ANDROID DI SMKN 6 KENDAL Muhammad Aji Saputra; Eko Riyanto; Solikhin
Journal of Information System and Computer Vol. 2 No. 1 (2022): Juli 2022
Publisher : Universitas Islam Nahdlatul Ulama Jepara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34001/jister.v2i1.266

Abstract

The rapid development of technology makes people innovate to make new things and leave old ways to simplify and save time a job. One example is monitoring the value of pH, PPM, room temperature and humidity as well as water temperature of hydroponic plants that used to still use conventional tools, now switching to Android-based IoT technology (Smart Hydroponics), especially at SMKN 6 Kendal. IoT is a way of connecting the Arduino sensor modules needed for hydroponic cultivation, where the results of sensor readings will be actually sent to the user's Android smartphone. The Arduino sensors are pH, TDS, DHT 11, ds1820 sensors. With this smart hydroponics, it is hoped that it can help hydroponic cultivators in the SMKN 6 Kendal environment to monitor their gardens anywhere and anytime and control the hydroponic temperature to be maintained below 30 degrees. From the reading of the value of the smart hydroponic sensor, it works well with existing standards and through MAPE calculations with a value below 10%.
PEMANFAATAN SISTEM INFORMASI KOPERASI DALAM MENINGKATKAN KEPERCAYAAN DAN LOYALITAS MASYARAKAT KOPERASI LEMBAGA KEUANGAN MIKRO AGRIBISNIS ( LKM A ) BERKAH MLATI MULYO PETEAN KENDAL Eko Riyanto; Agus Alwi Mashuri; Mahmudi Mahmudi
Jurnal Abdimas Bina Bangsa Vol. 5 No. 1 (2024): Jurnal Abdimas Bina Bangsa
Publisher : LPPM Universitas Bina Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46306/jabb.v5i1.696

Abstract

The benefits of the LKMA Cooperative are felt by the local community because with this cooperative farmers can continue to produce their agricultural land without fear of lack of capital. Currently, the number of members has reached 105 customers, where transactions have reached 180,000,000. This makes both administrative and financial processes very important in serving members. Currently, the bookkeeping carried out by cooperatives is computer-based using Microsoft Excel, but it is not yet efficient because cooperative administrators can only carry out transactions at certain times, such as monthly meetings, which results in long and time-consuming transaction process queues. Apart from that, the recording process still uses a card which is proof that the customer has paid the instalments, but manual recording has many weaknesses, including being left behind, damaged and even lost. Under current conditions, technology is needed to help cooperative administrators manage their cooperatives effectively and efficiently. The STMIK Himsya Semarang community service team saw an opportunity to assist LKMA cooperative administrators in managing cooperative finances using Cooperative Information System technology. This web-based cooperative information system application is made easier both from the admin and customer side because it uses the internet which can be accessed anytime and anywhere. All transactions carried out will be recorded in the database and can be seen in real-time, such as loans, payments, deposits and withdrawals.and publisher requirements. Abstracts are typically sectioned logically as an overview of what appears in the paper
Co-Authors Agus Alwi Mashuri Ana Soraya Mahmudi Mahmudi Muhammad Aji Saputra Solikhin Solikhin