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All Journal International Journal of Electrical and Computer Engineering Jurnal Pengabdian Kepada Masyarakat (Indonesian Journal of Community Engagement) PROtek : Jurnal Ilmiah Teknik Elektro Journal of Applied Information, Communication and Technology (JAICT) Madiun Spoor : Jurnal Pengabdian Masyarakat Jurnal Polimesin
Sahrin, Alfin
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Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Energy Engineering Materials Science & Nanotechnology Mechanical Engineering Social Sciences

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Enhanced accuracy estimation model energy import in on-grid rooftop solar photovoltaic Sahrin, Alfin; Abadi, Imam; Musyafa, Ali
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 5: October 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i5.pp5970-5983

Abstract

Installing rooftop solar photovoltaic (PV) with an on-grid system benefits consumers because it can reduce imports of electrical energy from the grid. This study aims to model the estimation of energy imports generated from on-grid rooftop solar PV systems. This estimation model was carried out in 20 provincial capitals in Indonesia. The parameters used are weather conditions, orientation angle, and energy generated from the on-grid rooftop solar PV system. The value of imported energy is divided into three combinations based on the azimuth angle direction, which describes the type and shape of the roof of the building (one-direction, two-directions, and three-directions). Modeling was done using machine learning with neural network (NN), linear regression, and support vector machine. A comparison of the machine learning algorithm results is NN produces the smallest root mean square error (RMSE) value of the three. Model enhancement uses a grid search cross-validation (GSCV) to become the GSCV-NN model. The RMSE results were enhanced from 53.184 to 44.389 in the one-direction combination, 145.562 to 141.286 in the two-direction combination, and 81.442 to 76.313 in the three-direction combination. The imported energy estimation model on the on-grid rooftop solar PV system with GSCV-NN produces a more optimal and accurate model.
TEKNOLOGI ENERGI BARU TERBARUKAN DAN KONSERVASI ENERGI: PEMBERDAYAAN LAHAN DENGAN SISTEM KETAHANAN PANGAN TERPADU TERBARUKAN “SAPTA” Faza Rifàti, Eva; Utami, Erna; Sahrin, Alfin; Sutanto, Agus; Sunardi, Sunardi
Madiun Spoor : Jurnal Pengabdian Masyarakat Vol 4 No 1 (2024): April 2024
Publisher : Politeknik Perkeretaapian Indonesia Madiun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37367/jpm.v4i1.329

Abstract

Salah satu sumber energi baru terbarukan terbaik, aman lingkungan dengan biaya operasional cukup tinggi, yaitu Pembangkit Listrik Tenaga Surya. Dikenal intensif dalam menghasilkan energi listrik. Nanosolar, dapat menekan biaya produksi dari $3 per watt sampai 30 sen per watt selama operasional sel Power sheet tersebut. Panel surya dapat mengoptimalkan transfer sinar matahari yang diubah menjadi listrik dan harus ditempatkan secara kontak langsung dengan cahaya matahari tanpa terhalangi oleh benda atau obyek lainnya. Aplikasi panel surya ini diterapkan melalui teknologi SAPTA, merupakan suatu sistem yang menggabungkan pertanian dan peternakan dengan tujuan adalah untuk menggunakan lahan secara optimal. Rancangannya adalah menggabungkan unsur kolam ikan, kandang ayam dan pertanian hidroponik yang dibuat secara bertingkat dengan bantuan panel surya sebagai sumber energinya. Dengan menciptakan suatu lingkungan yang optimal diharapkan melalui SAPTA dapat memperkecil penggunaan lahan dan memperbesar omset dari pelaku usaha. SAPTA dilengkapi dengan sinar UV yang akan mempercepat pertumbuhan tanaman. Air hidroponik berasal dari kolam ikan yang banyak mengandung unsur organik sebagai pupuk tanaman. Selain itu, tanaman juga menyerap amonia yang berlebih dari kolam ikan. Ikan juga memakan kotoran ayam dan memperkecil limbah hasil peternakan. Hal tersebut membangun suatu lingkungan integrasi yang saling memenuhi kebutuhan satu sama lain.
Rancang Bangun Sistem Proteksi Dan Monitoring Kebocoran Gas Hidrokarbon Berbasis Fuzzy Sugeno Oktavianto, Rinaldi; Wardhana, Asepta Surya; Sahrin, Alfin
PROtek : Jurnal Ilmiah Teknik Elektro Vol 9, No 1 (2022): Protek : Jurnal Ilmiah Teknik Elektro
Publisher : Program Studi Teknik Elektro Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/protk.v9i1.3365

Abstract

One of the risks in the oil industry is leakage of gases that are toxic or flammable. Fire and Gas System (FGS) used to detect the release of hazardous gases then carry out mitigation actions which can be alarms, indicators, or shutdown systems. This study aims to make a simple prototype of Fire and Gas System in the manifold area with three pipelines (Line-A, Line-B, and Line-C). The output of the system includes indicator, alarm, and shutdown system (closing gas flow and activate the exhaust fan). The system is integrated with Delphi and Arduino. The decision making based on Sugeno fuzzy. Based on the results, it was found that the suitability of fuzzy system reached 100%. The monitoring is displayed in graphical form. While the system response is appropriate, but there is a delay of about 1.5 seconds. Protection system is able to normalize conditions in about 77.5 seconds.
Buck boost converter control to accelerate cooling in hydrogen system coolers Adi, Wasis Waskito; Akhiriyanto, Novan; Alson, Adi; Gunawan, Yohanes; Sahrin, Alfin; Utami, Erna
Jurnal Polimesin Vol 22, No 6 (2024): December
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jpl.v22i6.5610

Abstract

The electrolysis process involves decomposing water (H₂O) into hydrogen gas (H₂) and oxygen gas (O₂), requiring substantial electrical power. This study utilized an electrolyzer with a maximum capacity of 7V and 40A, demanding 280 watts of power. Therefore, it requires a voltage of less than 7V but a high current of up to 40A, as the critical parameter for the electrolyzer in producing hydrogen is the electric current flowing through it. A buck-boost converter was implemented to adjust the voltage to operate a Thermoelectric Cooler (TEC) for temperature regulation. Over time, as the electrolyzer operates and consumes a high current, there is an increase in its temperature. The system successfully maintained the electrolyzer temperature below 35°C by adjusting the output voltage between 10-14V, with an input range of 21.62-21.65V. The cooling system achieved a temperature reduction of 1.06°C, demonstrating its effectiveness in stabilizing the electrolyzer’s performance, thus optimizing hydrogen production efficiency.
Electrical Power Prediction of Polycrystalline Solar Panels based on LSTM Model with environmental influence Sahrin, Alfin; Utami, Erna; Shoffiana, Nur; Abadi, Imam
JAICT Vol. 11 No. 02 (2025): JAICT
Publisher : Politeknik Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Solar energy is one of the most promising renewable energy sources that can support the sustainable energy transition. However, the electrical power produced by photovoltaic (PV) panels is greatly influenced by environmental conditions such as irradiation, temperature, humidity, and wind speed, making them volatile and difficult to predict. This study aims to develop a prediction model based on Long Short-Term Memory (LSTM) to estimate the power output of polycrystalline panels. Environmental data is collected in real-time, processed through the normalization stage, and then used as input in several model variants, namely pure LSTM, CNN-LSTM, LSTM-Autoencoder, and GWO-LSTM with metaheuristic optimization. Evaluation was conducted using R², RMSE, and MAPE metrics. The results showed that the pure LSTM model provided good accuracy (R² = 0.95; MAPE = 6.2%), while CNN-LSTM and LSTM-AE improved performance with R² reaching 0.97 and 0.96, respectively. The best model is GWO-LSTM, with R² = 0.98, RMSE = 0.31 kW, and MAPE = 4.3%. These findings prove that metaheuristic optimization in LSTM can increase the reliability of PV power prediction and support a more efficient energy management system.
QREEN Application to Address Water Supply Challenges in Blora Regency Sahrin, Alfin; Akhiriyanto, Novan; Utami, Erna; Handoko, Susilo
Jurnal Pengabdian kepada Masyarakat (Indonesian Journal of Community Engagement) Vol 11, No 4 (2025): December
Publisher : Direktorat Pengabdian kepada Masyarakat Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jpkm.105656

Abstract

Seasonal dry periods in Blora Regency routinely lead to drought conditions, which make it difficult for communities to secure clean water for daily use and for agricultural irrigation. This community service initiative aimed to deliver a rapid energy-based solution by implementing the Quick Response Energy (QREEN) system to support water distribution and environmental lighting in Ledok, Temengeng, and Joho Villages. The program followed a community based participatory approach with five stages, namely problem identification grounded in field data, technology solution design, site selection, implementation coordination, and program evaluation. Using a mixed methods design, data were collected through direct observation, semi structured interviews, and quantitative surveys administered to selected users. The results indicated high user satisfaction, including improved ease of access to clean water (79 to 85%) and time savings (75 to 83%), as well as increased farming yields (72 to 80%) among users who manage agricultural land. Overall, the findings suggest that QREEN implementation can strengthen local water security, although the magnitude of impact varies across contexts. Sustained, cross sector collaboration is recommended to support long term operation and enable program expansion.
Co-Authors Adi, Wasis Waskito Agus Sutanto Akhiriyanto, Novan Ali Musyafa Alson, Adi Faza Rifàti, Eva Handoko, Susilo Imam Abadi Oktavianto, Rinaldi Shoffiana, Nur Sunardi Sunardi Utami, Erna Wardhana, Asepta Surya Yohanes Gunawan, Yohanes