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All Journal International Journal of Electrical and Computer Engineering Jurnal Teknologi Informasi dan Ilmu Komputer EMITTER International Journal of Engineering Technology Briliant: Jurnal Riset dan Konseptual JOIV : International Journal on Informatics Visualization Jurnal Pendidikan Matematika (Kudus) GUYUB: Journal of Community Engagement Sewagati Jurnal Rekayasa elektrika The Indonesian Journal of Computer Science

Gunawan, Agus Indra

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Author-ID : 1118061

Religion Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Mechanical Engineering Public Health Social Sciences Other

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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

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

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

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.

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

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

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

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.

Algoritma Deep Learning-LSTM untuk Memprediksi Umur Transformator Ningrum, Ayu Ahadi; Syarif, Iwan; Gunawan, Agus Indra; Satriyanto, Edi; Muchtar, Rosmaliati
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 8 No 3: Juni 2021
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2021834587

Kualitas dan ketersediaan pasokan listrik menjadi hal yang sangat penting. Kegagalan pada transformator menyebabkan pemadaman listrik yang dapat menurunkan kualitas layanan kepada pelanggan. Oleh karena itu, pengetahuan tentang umur transformator sangat penting untuk menghindari terjadinya kerusakan transformator secara mendadak yang dapat mengurangi kualitas layanan pada pelanggan. Penelitian ini bertujuan untuk mengembangkan aplikasi yang dapat memprediksi umur transformator secara akurat menggunakan metode Deep Learning-LSTM. LSTM adalah metode yang dapat digunakan untuk mempelajari suatu pola pada data deret waktu. Data yang digunakan dalam penelitian ini bersumber dari 25 unit transformator yang meliputi data dari sensor arus, tegangan, dan suhu. Analisis performa yang digunakan untuk mengukur kinerja LSTM adalah Root Mean Squared Error (RMSE) dan Squared Correlation (SC). Selain LSTM, penelitian ini juga menerapkan algoritma Multilayer Perceptron, Linear Regression, dan Gradient Boosting Regressor sebagai algoritma pembanding. Hasil eksperimen menunjukkan bahwa LSTM mempunyai kinerja yang sangat bagus setelah dilakukan pencarian komposisi data, seleksi fitur menggunakan algoritma KBest dan melakukan percobaan beberapa variasi parameter. Hasil penelitian menunjukkan bahwa metode Deep Learning-LSTM mempunyai kinerja yang lebih baik daripada 3 algoritma lain yaitu nilai RMSE= 0,0004 dan nilai Squared Correlation= 0,9690. AbstractThe quality and availability of the electricity supply is very important. Failures in the transformer cause power outages which can reduce the quality of service to customers. Therefore, knowledge of transformer life is very important to avoid sudden transformer damage which can reduce the quality of service to customers. This study aims to develop applications that can predict transformer life accurately using the Deep Learning-LSTM method. LSTM is a method that can be used to study a pattern in time series data. The data used in this research comes from 25 transformer units which include data from current, voltage, and temperature sensors. The performance analysis used to measure LSTM performance is Root Mean Squared Error (RMSE) and Squared Correlation (SC). Apart from LSTM, this research also applies the Multilayer Perceptron algorithm, Linear Regression, and Gradient Boosting Regressor as a comparison algorithm. The experimental results show that LSTM has a very good performance after searching for the composition of the data, selecting features using the KBest algorithm and experimenting with several parameter variations. The results showed that the Deep Learning-LSTM method had better performance than the other 3 algorithms, namely the value of RMSE = 0.0004 and the value of Squared Correlation = 0.9690.

Studi Analisi Konsentrasi Warna Pada Cairan Pewarna Makanan Dengan Metode Pengukuran Optical Density Meiyanto, Onie; Gunawan, Agus Indra; Bayu Dewantara, Bima Sena
BRILIANT: Jurnal Riset dan Konseptual Vol 6 No 4 (2021): Volume 6 Nomor 4, November 2021
Publisher : Universitas Nahdlatul Ulama Blitar

Metode Image Processing banyak diimplementasikan untuk mengidetifikasi suatu bentuk atau perubahan pada gambar untuk mendapatkan hasil identifikasi suatu percobaan. Dalam penelitian ini perpaduan Image Processing, optical density(OD) dan sensor rgb untuk menentukan kualitas campuran air yang didapatkan nilai komposisi cairan warna. Karakteristik warna dari sampel air diperoleh dari histogram pada gambar yang tertangkap oleh mikroskop digital, dari histogram warna dapat diperoleh nilai max dan mean dan hasil gambar dari difraksi oleh kamera digital serta nilai output sensor rgb. Dengan metode tersebut diperoleh hasil setiap sampel yang telah di encerkan memiliki karakteristik warna yang berbeda-beda, hal ini dapat dilihat dari setiap kanal warna dari output sensor. Pengolahan data dengan metode histogram untuk dilakukan proses pengambilan nilai rata-rata(mean) dan nilai maksimum(Max) diperoleh model untuk memprediksi jenis dan konsentrasi dari sampel, pengujian yang telah dilakukan, didapatkan hasil grafik yang sigifikan sesuai dengan komposisi kualitas air dengan pewarna makanan

The Enhancement of 3 MHz Ultrasonic Echo Signal for Conversion Curve Development for Acoustic Impedance Estimation by Using Wavelet Transform Prastika, Edo Bagus; Gunawan, Agus Indra; Bayu Dewantara, Bima Sena; Hozumi, Naohiro; Prianto, Chandra Edy
EMITTER International Journal of Engineering Technology Vol 6 No 1 (2018)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Ultrasonic technology has already been used for many applications. Most of them are mainly used for object measurement. Some techniques have been widely applied to particular measurement by utilizing a very specific component. In this research, the previous technique to develop a conversion curve to obtain the acoustic impedance of the target is adopted. Then, we propose a 3 MHz concave shaped ultrasonic transducer for measuring liquids and a confirmation is needed to confirm if the system used is correct. Therefore, several saline solutions which property has been known are used. A low voltage of 10 Volt pulse is used to trigger the transducer. The ultrasonic wave is then transmitted through the multilayered mediums, which is pure water, clear acrylic, and the target. The echo from the interface between the acrylic and the target is then received by the same transducer. Some parameters such as peak and RMS are used to develop the conversion curve. A peak detection and comparison between the original echo and the processed one by using Wavelet transform (UWT and DWT) is then performed. Some analysis of the echo signal by using multiresolution and time-frequency analysis is also proposed. The result obtained from the measurement is then compared to that from the theoretical calculation. Based on the result, in terms of developing the calibration graph, only the RMS value (UWT) which has the closest trend to the result of the calculation, with the mean percentage error of 0.65512%, which is the smallest value among all parameters.

Design and Implementation of Embedded Water Quality Control and Monitoring System for Indoor Shrimp Cultivation Natan, Oskar; Gunawan, Agus Indra; Dewantara, Bima Sena Bayu
EMITTER International Journal of Engineering Technology Vol 7 No 1 (2019)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Maintaining the water quality of a pond is one of the main issues on aquaculture management. Water quality represents the condition of a pond based on several water parameters such as dissolved oxygen (DO), temperature, pH, and salinity. All of these parameters need to be strictly supervised since it affects the life-sustainability of cultivated organisms. However, DO is said to be the main parameter since it affects the growth and survival rate of the shrimp. Therefore, a water quality control and monitoring system is needed to maintain water parameters at acceptable value. The system is developed on a mini-PC and microcontroller which are integrated with several sensors and actuator forming an embedded system. Then, this system is used to collect water quality data that is consisting of several water parameters and control the DO as the main parameter. In accordance with the stability needs against the sensitive environment, a fuzzy logic-based controller is developed to maintain the DO rate in the water. This system is also equipped with SIM800 module to notice the farmer by SMS, built-in wifi module for web-based data logging, and improved with Android-based graphical user interface (GUI) to perform user-friendly monitoring. From the experiment results, a fuzzy controller that is attached to the system can control the DO at the acceptable value of 6 ppm. The controller is said to have high robustness since its deviation for long-time use is only 0.12 ppm. Another test shows that the controller is able to overcome the given disturbance and easily adapt when the DOâ€™s set point is changed. Â Finally, the system is able to collect and store the data into cloud storage periodically and show the data on a website.

Co-Authors Alam, Daffa Syah Ariyanto, Ferry Asmarany, Anja Bima Sena Bayu Dewantara Ebrahimi, Faizulddin Edi Satriyanto Gunawan, I Putu Adi Surya Gunawan, M Wisnu Habibulloh, Muhamad Aldino Hamida, Silfiana Nur Hendriawan, Akhmad Hozumi, Naohiro Idris Winarno Insivitawati, Era iwan Syarif Kamaluddin, Muhammad Wafiq Meiyanto, Onie Ningrum, Ayu Ahadi Novie Ayub Windarko Nurmaida, Firnanda Pristiana Nurtiyasari, Devi Oskar Natan Prastika, Edo Bagus Pratama, Ariesa Editya Prianto, Chandra Edy Riyanto Sigit, Riyanto Rosmaliati, Rosmaliati Sanaba, Utari Setiawardhana, Setiawardhana Suasono, Zaikhul Sulthon Sukiyanto, Sukiyanto Tambunan, Orlando Pratama Taufiqurrahman Taufiqurrahman Teguh Hady Ariwibowo

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