Claim Missing Document
Check
Articles

Found 5 Documents
Search

Objective Video Quality Assessment of Direct Recording and Datavideo HDR-40 Recording System Nofia Andreana; Arif Nursyahid; Eni Dwi Wardihani
JAICT Vol 1, No 1 (2016)
Publisher : Politeknik Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (428.16 KB) | DOI: 10.32497/jaict.v1i1.422

Abstract

Digital Video Recorder (DVR) is a digital video recorder with hard drive storage media. When the capacity of the hard disk runs out. It will provide information to users and if there is no response, it will be overwritten automatically and the data will be lost. The main focus of this paper is to enable recording directly connected to a computer editor. The output of both systems (DVR and Direct Recording) will be compared with an objective assessment using the Mean Square Error (MSE) and Peak Signal to Noise Ratio (PSNR) parameter. The results showed that the average value of MSE Direct Recording dB 797.8556108, 137.4346100 DVR MSE dB and the average value of PSNR Direct Recording and DVR PSNR dB 19.5942333 27.0914258 dB. This indicates that the DVR has a much better output quality than Direct Recording. 
Nutrient Film Technique (NFT) Hydroponic Monitoring System Helmy Helmy; Arif Nursyahid; Thomas Agung Setyawan; Abu Hasan
JAICT Vol 1, No 1 (2016)
Publisher : Politeknik Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (2745.355 KB) | DOI: 10.32497/jaict.v1i1.425

Abstract

Plant cultivation using hydroponic is very popular today. Nutrient Film Technique (NFT) hydroponic system is commonly used by people. It can be applied indoor or outdoor. Plants in this systemneed nutrient solution to grow well. pH, TDS and temperature of the nutrient solution must be check to ensure plant gets sufficient nutrients. This research aims todevelop monitoring system of NFT hydroponic. Farmer will be able to monitor pH, TDS and temperature online. It will ease farmer to decide which plant is suitable to be cultivated and time to boost growth.Delay of the system will be measured to know system performance. Result shows that pH is directly proportional with TDS. Temperature value has no correlation with pH and TDS. System has highest delay during daylight and afternoon but it will decline in the night and morning. Average of delay in the morning is 11 s, 28.5 s in daylight, 32 s in the afternoon and 17.5 s in the night. 
Pemantauan dan Pengendalian Parameter Akuaponik Menggunakan Representational State Transfer Application Programming Interface Helmy; Athadhia Febyana; Agung Al Rasyid; Arif Nursyahid; Thomas Agung Setyawan; Ari Sriyanto Nugroho
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 9 No 4: November 2020
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1444.277 KB) | DOI: 10.22146/jnteti.v9i4.594

Abstract

Aquaponics is a combination of aquaculture and hydroponics. One of the hydroponic systems is a drip system. Parameters that need to be considered in aquaponic culture include the acidity of nutrient solution (pH), water temperature, and nutrient solution showed by Total Dissolved Solids (TDS). Plant nutrition is obtained from fish manure which contains nitrogen. Therefore, monitoring pH, TDS, and temperature in realtime and controling soil moisture in aquaponic plants are needed so the plants do not lack nutrients. Representational State Transfer Application Programming Interface (REST API) is used to receive threshold values by farmers through the website and also sends soil moisture values and aquaponics parameters of pH, temperature, and TDS to server. Delay test of the monitoring and controling system is needed to determine the device’s reliability of transmission data. Notification by email is sent to farmer if the soil moisture value is less than the threshold. The result shows that the system can send notification by email to farmer when the soil moisture value was less than the threshold, the average delay of the node-gateway monitor is 6.01 s, while the average delay of gateway-server monitor 10.02 s, and the average delay of server-gateway control is 92.55 s.
Analisis Kinerja Aplikasi Pemantauan dan Pengendalian Smart Agriculture Berbasis Android Helmy; Fenny Rahmasari; Arif Nursyahid; Thomas Agung Setyawan; Ari Sriyanto Nugroho
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 11 No 1: Februari 2022
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1390.956 KB) | DOI: 10.22146/jnteti.v11i1.3379

Abstract

The ever-evolving digital era leads to an industrial revolution in the internet of things (IoT)-based smart agriculture and smart farm. Of many uses is the use of an Android-based app that monitors and controls parameters in the cultivation process in this digital era. An unstable internet connection can interfere with the monitoring process. For this reason, a system integration into a single app running even in an offline condition is needed; therefore, the user can monitor and control the Android-based smart agriculture app in two modes, namely online and offline. A performance analysis is also necessary to know the app's reliability in sending and receiving data. This system integration used two modes of operation, i.e. online and offline, wherein the online mode, the app will communicate with the server when connected with the internet using representational state transfer application programming interface (REST API). Meanwhile, the app will communicate directly with the system through a local access point in the offline mode. This app interacts with the system with the MQTT protocol where the app acts as an MQTT client. The performance analysis was conducted in the black box test, load activity test, and app performance test from the Android profiler. The acquired test from the app functionality test (black box) showed that the user could monitor and control the smart agriculture in online and offline mode through the app. The average load time for all the activities was 3.507 seconds with a network bandwidth of 4.54 Mbps. At the same time, the average load time in a network bandwidth of 35.35 Mbps was 1.4 seconds. The system performance test indicated the app was relatively light as the CPU usage for the app was 31%, with a memory usage of 453.8 MB.
Pemantauan dan Pengendalian Kepekatan Larutan Nutrisi Hidroponik Berbasis Jaringan Sensor Nirkabel Helmy Helmy; Aji Rahmawati; Syahrul Ramadhan; Thomas Agung Setyawan; Arif Nursyahid
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 7 No 4: November 2018
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1208.613 KB)

Abstract

Nutrient Film Technique (NFT) is one of hydroponic plant cultivation models. Most of hydroponic farmers are using NFT model to raise the productivity of crops. NFT hydroponic farmers usually use more than one hydroponic table in order to fulfill market needs. Harvest failures can happen when farmers do not have suficient information on monitoring and controlling the nutrition solution concentration. This can be overcome with the existence of monitoring and controlling system of nutrition solution concentration. This paper aims to build and examine system reliability using two NFT hydroponic tables based on wireless sensor network. Each table is installed with monitoring and controlling of nutrition solution concentration devices which transmit the data to server throughwireless sensor network. The result shows that electrical conductivity meter which is used to read nutrition solution concentration has 3.92% of error rate. Node 2 has faster threshold data transmission than node 1, with 34.68 second of node 2 delay and 40.01 second of node 1 delay. Node 1 has better accuracy of nutrition solution concentration control for 96.12% than node 2 which has 92.79% nutrition solution concentration accuracy.