Article Per Year (5 Year)
p-Index From 2021 - 2026
0.61
P-Index
This Author published in this journals
All Journal JOIV : International Journal on Informatics Visualization Jurnal Begawe Teknologi Informasi
Wedashwara, Wirarama
Unknown Affiliation
Computer Science & IT Decision Sciences, Operations Research & Management Engineering

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
INSTALASI IRIGASI TETES BERTENAGA SURYA PADA PERTANIAN LAHAN KERING DESA GUMANTAR KABUPATEN LOMBOK UTARA: Solar-Powered Drip Irrigation Installation On Dryland Farms In Gumantar Village, North Lombok District Zubaidi, Ariyan; Wedashwara, Wirarama; Jatmika, Andy Hidayat; Mardiansyah, Ahmad Zafrullah; Wijayanto, Heri
Jurnal Begawe Teknologi Informasi (JBegaTI) Vol. 5 No. 2 (2024): JBegaTI
Publisher : Program Studi Teknik Informatika, Fakultas Teknik Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jbegati.v5i2.1271

Abstract

Desa Gumantar, yang terletak di Kabupaten Lombok Utara, menghadapi tantangan besar dalam sektor pertanian karena kondisi lahan yang kering dan cuaca panas ekstrem. Rendahnya curah hujan dan distribusi air yang terbatas mengakibatkan kesulitan dalam pengelolaan sumber daya air, yang berdampak negatif pada produktivitas pertanian. Untuk mengatasi permasalahan ini, teknologi irigasi hemat air seperti sistem irigasi tetes sangat diperlukan untuk memaksimalkan penggunaan air secara efisien. Selain itu, pemanfaatan tenaga surya sebagai sumber energi alternatif dapat mendukung keberlanjutan pertanian dengan mengurangi ketergantungan pada bahan bakar fosil. Dalam kegiatan pengabdian masyarakat ini, dilakukan instalasi sistem irigasi tetes yang digerakkan oleh tenaga surya pada lahan pertanian di Desa Gumantar. Sistem ini menggunakan panel surya untuk menggerakkan pompa air yang menyalurkan air melalui pipa langsung ke akar tanaman. Hasil implementasi menunjukkan pengurangan biaya operasional yang signifikan, khususnya dalam pengeluaran solar, serta peningkatan produktivitas tanaman tomat dan cabai. Teknologi ini tidak hanya meningkatkan efisiensi penyiraman tetapi juga memberikan pengetahuan dan keterampilan baru kepada petani mengenai teknologi irigasi berkelanjutan yang ramah lingkungan dan efisien.
Text Classification Using Genetic Programming with Implementation of Map Reduce and Scraping Wedashwara, Wirarama; Irmawati, Budi; Wijayanto, Heri; Arimbawa, I Wayan Agus; Widartha, Vandha Pradwiyasma
JOIV : International Journal on Informatics Visualization Vol 7, No 2 (2023)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.7.2.1813

Abstract

Classification of text documents on online media is a big data problem and requires automation. Text classification accuracy can decrease if there are many ambiguous terms between classes. Hadoop Map Reduce is a parallel processing framework for big data that has been widely used for text processing on big data. The study presented text classification using genetic programming by pre-processing text using Hadoop map-reduce and collecting data using web scraping. Genetic programming is used to perform association rule mining (ARM) before text classification to analyze big data patterns. The data used are articles from science-direct with the three keywords. This study aims to perform text classification with ARM-based data pattern analysis and data collection system through web-scraping, pre-processing using map-reduce, and text classification using genetic programming. Through web scraping, data has been collected by reducing duplicates as much as 17718. Map-reduce has tokenized and stopped-word removal with 36639 terms with 5189 unique terms and 31450 common terms. Evaluation of ARM with different amounts of multi-tree data can produce more and longer rules and better support. The multi-tree also produces more specific rules and better ARM performance than a single tree. Text classification evaluation shows that a single tree produces better accuracy (0.7042) than a decision tree (0.6892), and the lowest is a multi-tree(0.6754). The evaluation also shows that the ARM results are not in line with the classification results, where a multi-tree shows the best result (0.3904) from the decision tree (0.3588), and the lowest is a single tree (0.356).
Solar Powered Vibration Propagation Analysis System using nRF24l01 based WSN and FRBR Wedashwara, Wirarama; Yadnya, Made Sutha; Sudiarta, I Wayan; Arimbawa, I Wayan Agus; Mulyana, Tatang
JOIV : International Journal on Informatics Visualization Vol 7, No 1 (2023)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.7.1.1592

Abstract

Prevention of the effects caused by natural disasters such as earthquakes and landslides requires analysis of vibration propagation. In outdoor applications, internet sources such as WIFI are not always available, so it requires alternative data communications such as nRF24l01. The system also requires a portable power source such as solar power. This research aims to develop a vibration propagation analysis system based on the nRF24l01 wireless sensor network and solar power by implementing the fuzzy rule-based regression (FRBR) algorithm. The system consists of two piezoelectric and nrf24l01 vibration sensors. The system also uses a third node equipped with temperature and soil moisture sensors, air temperature and humidity, and light intensity as environmental variables. The evaluation results show the Quality of Services (QoS) results with a throughput of 99.564%, PDR 99.675%, and a delay of 0.0073s. The Fuzzy Association Rule (FAR) extraction results yield nine rules with average support of 0.319 and confidence of 1 for vibration propagation. The availability of solar power was evaluated with an average current value of 0.250A and a voltage of 3.266V. The results of FRBR are based on the propagation of the vibration that propagated and produced a mean square error (MSE) of 0.141 and a mean absolute error (MAE) of 0.165. The correlation matrix and FAR results show that only soil moisture has a major effect on the magnitude and duration of propagation. However, other variables can regress soil moisture with MSE 0.232 and MAE 0.287.
Co-Authors Budi Irmawati Heri Wijayanto I Wayan Agus Arimbawa, I Wayan Agus I Wayan Sudiarta Jatmika, Andy Hidayat Made Sutha Yadnya Mardiansyah, Ahmad Zafrullah Tatang Mulyana Vandha Pradwiyasma Widartha Zubaidi, Ariyan