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Parallel Processing Implementation on Weather Monitoring System for Agriculture Dwi Susanto; Kudang Boro Seminar; Heru Sukoco; Liyantono Liyantono
Indonesian Journal of Electrical Engineering and Computer Science Vol 6, No 3: June 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v6.i3.pp682-687

Abstract

Weather monitoring and forecasting are very important in agricultural sectors. There are several data need to be collected in real-time to support weather monitoring and forecasting systems, such as temperature, humidity, air pressure, wind speed, wind direction, and rainfall. The purpose of this research to develop a real-time weather monitoring system using a parallel computation approach and analyze the computational performance (i.e., speed up and efficiency) using the ARIMA model. The developed system wireless has been implemented on sensor networks (WSN) platform using Arduino and Raspberry Pi devices and web-based platform for weather visualization and monitoring. The experimental data used in our research work is a set of weather data acquired and collected from January until March 2017 in Bogor area. The result of this research is that the speed up of the using eight processors computation three times faster than using a single processor, with the efficiency of 50%.
MOBILE INTERNET-BASED LEARNING TO CULTIVATE STUDENTS’ SPEAKING SKILL DURING CORONAVIRUS PANDEMIC Ida Ayu Made Sri Widiastuti; Ida Bagus Nyoman Mantra; Heru Sukoco
International Journal of Applied Science and Sustainable Development (IJASSD) Vol. 2 No. 1 (2020): International Journal of Applied Science and Sustainable Development (IJASSD)
Publisher : Unmas Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (147.923 KB)

Abstract

Coronavirus pandemic has been spreading in Indonesia and influences the way of Indonesian life. In the education sector, the coronavirus pandemic has forced teachers to conduct all the learning activities from home. The present study dealt with teaching speaking skill through mobile internet-based learning during the coronavirus pandemic where all students had to learn from their own home. The present online learning conducted in two cyclic sessions by making use of pre-test and post-test research design with descriptive and quantitative analysis to collect the required data. The grand mean figures for the first cycle and second cycle showed convincing findings since the mean figure of the initial reflection is much lower than the corresponding mean figures obtained for each session. Therefore mobile internet-based learning is considered to be an effective way of learning during coronavirus pandemic in Indonesia.
Sistem Akuisisi Data Multi Node untuk Irigasi Otomatis Berbasis Wireless Sensor Network Chaerur Rozikin; Heru Sukoco; Satyanto Krido Saptomo
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 6 No 1: Februari 2017
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1568.473 KB)

Abstract

Watering plants is one of farmer’s activities. Most of Indonesian farmers use traditional watering method to water plants. It causes water productivity unmanaged properly and soil moisture level can not be monitored. To resolve these problems, an automatic watering system is developed. This system uses soil moisture sensors which provide real-time data. Data from multiple sensor node will be transmitted through wireless sensor network. LED in actuator node will turn on or off based on lower and upper set point values transmitted from coordinator node. Soil moisture sensors are calibrated using groundwater level to obtain correlation between sensor and groundwater level. Delay, throughput, and packet loss ratio are measured and result 0.2 seconds, 1.6 kbps, and 1.6%, respectively. These values showed that all automatic watering system were well implemented.
Alignment of English as a foreign language teachers’ understanding of classroom assessment practices Ida Ayu Made Sri Widiastuti; Katie Weir; Heru Sukoco; Gunadi Harry Sulistyo
International Journal of Evaluation and Research in Education (IJERE) Vol 12, No 4: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijere.v12i4.25492

Abstract

A comprehensive understanding of classroom assessment is essential for improving students’ learning and teachers’ professionalism. This study was conducted to gain better information about teachers’ understanding of classroom assessment compared to their classroom practices. Semi-structured interviews and classroom observations were employed to collect the data. The collected data were then analyzed comprehensively using comparative and argumentative methods. The results were then presented descriptively to establish the findings. The findings showed that some teachers’ classroom assessment practices were consistent with their assessment understanding, while others were inconsistent. The findings suggest that different contextual factors may influence teachers’ classroom practices. Furthermore, English as a foreign language (EFL) teachers need to be re-trained on comprehending the influencing contextual factors to utilize their understanding of assessment in the classroom effectively.
Metadata Modeling of LoRa Based Payload Information for Precision Agriculture Tea Plantation Eddy Prasetyo Nugroho; Taufik Djatna; Imas Sukaesih Sitanggang; Irman Hermadi; Agus Mulyana; Sri Wahjuni; Heru Sukoco
Scientific Journal of Informatics Vol 10, No 2 (2023): May 2023
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v10i2.43432

Abstract

Purpose: The purpose of this study is to model the metadata of Payload Information on Agriculture Drones which consists of the results of images computational and the Onboard system of the Drone.Methods: The stages of the research were carried out with the process of forming Payload information metadata from the Agriculture Drone with sensors/actuators based on the architecture and computing with Image Processing or Computer Vision on the camera captures. This study describes the metadata modeling process formed from the Internet of Things system with Drone and GCS communication based on the Long Range or Long-Range Wide Area Network protocols with Payload information consisting of drone data and image computation results. Result: The result obtained is the formation of Payload information from LoRa-based Drones with a frame size of 142 bytes. Novelty: Payload information is formed into a metadata model indicator with the formation scheme being part of the tea plantation dataset. The metadata model will be test expected to obtain field data on Drones and GCS communication in the LoRaWAN Network in tea plantations which are rural environments.