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All Journal International Journal of Electrical and Computer Engineering JOIV : International Journal on Informatics Visualization GUYUB: Journal of Community Engagement Sewagati Jurnal Rekayasa elektrika The Indonesian Journal of Computer Science
Gunawan, Agus Indra
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Inovasi Teknologi dalam Budidaya Udang: Penggunaan Water Quality Meter untuk Meningkatkan Produktivitas Udang di Sidoarjo Gunawan, Agus Indra; Ariwibowo, Teguh Hady; Nurmaida, Firnanda Pristiana; Ariyanto, Ferry; Kamaluddin, Muhammad Wafiq; Sanaba, Utari; Habibulloh, Muhamad Aldino; Tambunan, Orlando Pratama
Sewagati Vol 8 No 3 (2024)
Publisher : Pusat Publikasi ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j26139960.v8i3.982

Abstract

Pengabdian masyarakat ini bertujuan untuk meningkatkan kualitas lingkungan perairan yang vital bagi petani udang di Sidoarjo. Dengan memberikan water quality meter kepada para petani, kami berupaya meningkatkan pemahaman mereka terhadap parameter-parameter kritis dalam air yang berpengaruh pada pertumbuhan udang. Melalui serangkaian pelatihan dan bimbingan, petani diberi pengetahuan tentang cara menggunakan alat ini untuk memantau kualitas air secara mandiri. Selain itu, kami juga menyediakan informasi dan panduan praktis dalam mengelola kualitas air secara optimal. Metode yang digunakan dalam pengabdian masyarakat ini melibatkan pendekatan partisipatif, di mana kami bekerja sama dengan komunitas petani udang untuk menentukan kebutuhan mereka dan menyusun strategi yang sesuai. Kami juga melakukan pemantauan berkala untuk mengevaluasi efektivitas alat ini dalam membantu petani mengelola kualitas air secara lebih efisien. Hasil dari pengabdian masyarakat ini menunjukkan peningkatan signifikan dalam pemahaman petani tentang faktor-faktor yang memengaruhi kualitas air untuk budidaya udang. Para petani juga melaporkan peningkatan produksi dan kesehatan udang setelah menerapkan pengetahuan yang didapat dari penggunaan alat ini. Kesimpulannya, pemberian water quality meter dan pendidikan yang terkait membantu petani udang dalam meningkatkan pemantauan dan manajemen kualitas air secara mandiri. Langkah ini dapat berpotensi meningkatkan produktivitas serta keberlanjutan usaha budidaya udang di komunitas ini.
Implementasi Modul Water Quality Meter pada Komunitas Petani Udang Vaname Jawa Timur Nurmaida, Firnanda Pristiana; Gunawan, Agus Indra; Ariwibowo, Teguh Hady; Ariyanto, Ferry; Sanaba, Utari; Habibulloh, Muhamad Aldino; Tambunan, Orlando Pratama; Kamaluddin, Muhammad Wafiq
GUYUB: Journal of Community Engagement Vol 5, No 1 (2024)
Publisher : Universitas Nurul Jadid

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33650/guyub.v5i1.7942

Abstract

Vannamei shrimp is one of the leading commodities in fisheries aquaculture, due to its competitive price and the ability to be mass-produced with high stocking densities. Many coastal communities in East Java capitalize on this opportunity by engaging in vannamei shrimp cultivation. However, most shrimp farmers still measure pond water quality using conventional methods and record water quality parameters on paper, which is highly inefficient. With this issue in mind, the author sought to engage in community service by inviting representatives from the East Java vannamei shrimp farming community. The method involved delivering lectures and interactive discussions with shrimp farmers to understand their perceptions and insights regarding pond water quality, followed by the handover of modules, and subsequently evaluating the modules' usage by the shrimp farmers. As a result of this community service, we introduced a tool to assist traditional shrimp pond farmers in monitoring water quality, in the form of a "Water Quality Meter" module integrated with a website accessible via smartphones and laptops. The "Water Quality Meter" module was designed with a system to portable monitor pond water quality using Internet of Things (IoT) technology, where data obtained by microcontrollers is transmitted to a database to determine the quality value of pond water. Evaluation results indicate that farmers can use the module effectively, and data collected on the website shows that pond water quality for the farmers remains within normal ranges. Shrimp farmers directly benefit from using the module, as the shrimp pond monitoring process becomes more practical and accurate. 
Algae content estimation utilizing optical density and image processing method Kamaluddin, Muhammad Wafiq; Gunawan, Agus Indra; Setiawardhana, Setiawardhana; Dewantara, Bima Sena Bayu; Insivitawati, Era; Asmarany, Anja; Pratama, Ariesa Editya
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 6: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i6.pp6248-6257

Abstract

One of the factors that influence shrimp cultivation is the presence of algae. Precise knowing algae content in the pond is essential for effective management. Most research in the field of algae species carried out by researchers were observing Chlorella Sp. more than the other algae species, with a particular emphasis on substance concentrations. This study proposed non-invasive techniques for quantifying algae abundance, utilizing optical density (OD) and image processing (IP) methods. Three different algae species are frequently found in Indonesia i.e., Chlorella Sp., Thalassiosira Sp., and Skeletonema Sp. are used as sample. Those samples are cultured and prepared in a certain volume with a certain quantity. For experimental and observation purposes, those samples are then diluted into water based on percentage value. The experimental results provided RGB values, which were then used to establish polynomial equations. To verify these equations, two approaches were employed: synthetic image analysis and evaluation using additional data. The mean average error (MAE) was found to be 3.467 for IP method and 3.513 for OD method. It shows that IP method give better result compared to OD method in this study. However, it is very possible that the two methods will complement each other.
Minimizing Total Harmonic Distortion of 7-Level Packed U-Cell Multilevel Inverter Using Whale Optimization Algorithm Ebrahimi, Faizulddin; Windarko, Novie Ayub; Gunawan, Agus Indra
The Indonesian Journal of Computer Science Vol. 12 No. 6 (2023): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v12i6.3507

Abstract

This paper presents an innovative study introducing a novel design for a single-phase, 7-level inverter. The design combines the modified pulse width modulation (MPWM) technique with the compact packed U-cell (PUC) topology. We evaluate this inverter's performance through comprehensive simulations in the MATLAB Simulink software. Multi-level inverter (MLI) technology is crucial for high-power, medium-voltage energy control. However, using numerous semiconductor switches in traditional MLI setups poses challenges at higher voltage levels, including increased size, costs, and losses. To address these issues, our study proposes a transformative approach, emphasizing reducing active switches within the multi-level inverter architecture. Consequently, we introduce an innovative 7-level PUC-MLI design. This configuration not only reduces harmonic distortion but also addresses cost concerns. Strategically manipulating semiconductor switch sequences significantly enhances the inverter's operational efficiency. A notable contribution is our inventive method to reduce total harmonic distortion (THD) in the inverter's output voltage, achieved through a whale optimization algorithm (WOA). Implementing this algorithm substantially lowers THD levels. Importantly, this approach's effectiveness extends to various inverter topologies and levels, offering a substantial THD reduction without additional expenses.
Optimalisasi Kualitas Air pada Tambak Udang Vannamei Menggunakan Modul IoT Gunawan, Agus Indra; Setiawardhana, Setiawardhana; Gunawan, M Wisnu; Alam, Daffa Syah; Suasono, Zaikhul Sulthon; Hamida, Silfiana Nur
GUYUB: Journal of Community Engagement Vol 6, No 1 (2025): Maret
Publisher : Universitas Nurul Jadid

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33650/guyub.v6i1.10581

Abstract

Indonesian has great potential in the fisheries sector, with vaname shrimp as a leading commodity due to its competitive price and efficient cultivation. However, many shrimp farmers in Keputih Village, Surabaya City still lack an understanding of the importance of monitoring and managing pond water quality. In response to this, the Master of Applied Electrical Engineering and Master of Applied Informatics and Computer Engineering teams at Politeknik Elektronika Negeri Surabaya (PENS) introduced an IoT-based Water Quality Meter module. This program not only provides real-time water quality monitoring technology that can be accessed via smartphone or laptop, but also provides training and assistance to pond farmers in adopting this technology. Evaluation results show that pond farmers can operate the module well to monitor water quality parameters, making it easier to monitor ponds accurately and practically. The community service program is expected to increase yields, strengthen collaboration between academics and communities, and encourage the adoption of modern technology in shrimp farming.
Cloud Computing-based Shrimp Pond Water Quality Prediction Intelligent Service System Suasono, Zaikhul Sulthon; Setiawardhana, Setiawardhana; Winarno, Idris; Gunawan, Agus Indra
JOIV : International Journal on Informatics Visualization Vol 9, No 4 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.4.2862

Abstract

Maintaining water quality is an essential factor in the success of shrimp farming, particularly in conventional and semi-intensive methods in Indonesian. Poor water quality will affect shrimp's survival, reproduction, development, and harvest yield. In order to furnish data regarding future water quality conditions, This research aims to create an intelligent cloud-based water quality prediction system for shrimp ponds that can provide accurate predictions regarding future water quality conditions. The system utilizes the WQI dataset gathered from four different shrimp farming sites, totaling 408 samples, each location exhibiting a different set of values. The model will be trained using four parameters: pH, DO, salinity, and temperature. The WQI dataset will be pre-processed to address missing data, outliers, and standardization. The water quality prediction model uses three machine learning algorithms: SVM, ANN, and MLR. The model's performance results are evaluated using MAE, RMSE, and R². The results indicate that the ANN model is the most effective, achieving an MAE: 0.4023, RMSE: 0.5336, and R²: 0.7178 for temperature predictions, and an MAE: 0.4080, RMSE: 0.5942, and R²: 0.5997 for salinity. The SVM model had mixed results for temperature, with an MAE: 0.3645 and RMSE: 0.4823, but it performed poorly for DO, as evidenced by a negative R² of -0.2428. The MLR model provided reasonable temperature predictions MAE: 0.4953, RMSE: 0.6370, R²: 0.5602. Subsequent research endeavors should prioritize the augmentation of the dataset size and the incorporation of temporal dimensions in order to enhance the precision of predictive outcomes.
A Low-Cost Salinity Meter Based On Ultrasonic Wave Gunawan, Agus Indra; Hendriawan, Akhmad; Taufiqurrahman, Taufiqurrahman; Nurmaida, Firnanda Pristiana
Jurnal Rekayasa Elektrika Vol 21, No 3 (2025)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17529/jre.v21i3.43940

Abstract

Monitoring the quality of shrimp pond water is crucial for shrimp growth, with salinity being one of the most significant parameters. Currently, salinity sensors for pond water are designed for momentary measurements, which are unsuitable for continuous monitoring. This study introduces a method for continuous salinity measurement using ultrasonic signals. The proposed approach utilizes a measuring chamber equipped with ultrasonic sensors to determine the Time-of-Flight (ToF). To ensure accuracy, four ToF methods were compared, with the cross-correlation method identified as the most accurate. This method was subsequently used to calculate the ToF, which was then applied to determine the acoustic speed. Since the acoustic speed in water is influenced by salinity, temperature, and pressure, changes in salinity cause detectable changes in the acoustic speed. The acoustic speed was further used as input for the modified Del Grosso equation to derive the salinity. Experimental results showed an average error of 4.83% for saline solutions and 1.81% for shrimp pond water. These findings demonstrate that the proposed method provides sufficient accuracy for water salinity measurement.
Co-Authors Alam, Daffa Syah Ariyanto, Ferry Asmarany, Anja Bima Sena Bayu Dewantara Ebrahimi, Faizulddin Gunawan, M Wisnu Habibulloh, Muhamad Aldino Hamida, Silfiana Nur Hendriawan, Akhmad Idris Winarno Insivitawati, Era Kamaluddin, Muhammad Wafiq Novie Ayub Windarko Nurmaida, Firnanda Pristiana Pratama, Ariesa Editya Sanaba, Utari Setiawardhana, Setiawardhana Suasono, Zaikhul Sulthon Tambunan, Orlando Pratama Taufiqurrahman Taufiqurrahman Teguh Hady Ariwibowo