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Analisa Pemanfaatan Daya Generator Set Sebagai Energi Listrik Cadangan Di AKN Aceh Barat Sya'rani Denk, Teuku Mizan; Saputra, Herdian; Firnanda, Ary; Pandria, T. M. Azis; Daili, Cut; Hidayat, Afrilia
VOCATECH: Vocational Education and Technology Journal Vol 6, No 1 (2024): October
Publisher : Akademi Komunitas Negeri Aceh Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38038/vocatech.v6i1.191

AbstractThe quality of electrical energy is a crucial requirement for the Akademi Komunitas Negeri (AKN) Aceh Barat. Electrical outages negatively impact performance, as equipment cannot be utilized during these times. A generator set is a machine that produces electrical energy and serves as a backup when the electrical supply from PLN is interrupted. Currently, AKN Aceh Barat has a generator set with a capacity of 7,800 watts, which is insufficient to meet the academy's power demands. The average monthly energy consumption from April to September 2024 is 5,199.83 kWh. To overcome the lack of power from the generator set, priority loads have been designated based on the importance of different rooms that facilitate essential services, ensuring that teaching and learning activities can proceed effectively. The generator's backup energy primarily supports a load of 6,290 watts, reaching an operational loading percentage of 81%. The electrical energy distribution from the generator to these priority rooms is managed through a new installation known as the Automatic Transfer Switch (ATS) panel, which activates automatically when the electrical supply from PLN is disrupted.Keywords:Power; Electrical; Distribution; Generator; EfficiencyAbstrakKualitas energi listrik menjadi kebutuhan utama bagi Akademi Komunitas Negeri Aceh Barat, pemadaman energi listrik berdampak buruk terhadap kinerja yang disebabkan peralatan tidak dapat digunakan. Generator set adalah mesin generator yang mampu menghasilkan energi listrik yang digunakan sebagai energi cadangan bila suplai energi listrik dari PLN terputus. pada AKN Aceh Barat generator set yang tersedia memiliki daya sebesar 7.800 watt dan tidak mampu memenuhi kebutuhan daya yang diperlukan oleh AKN Aceh Barat, rata-rata pemakaian beban AKN Aceh Barat dari bulan april sampai bulan September tahun 2024 mencapai 5.199,83 kWh per bulanya. Untuk mengatasi kekurangan daya dari generator set sebagai energi cadangan maka dipilih beban prioritas berdasarkan ruang prioritas yang berfungsi untuk pelayanan sehingga kegiatan belajar mengajar berjalan dengan baik. besar beban prioritas yang distribusi oleh daya generator sebagai energi cadangan sebesar 6.290 watt dengan persentase pembebanan mencapai 81%. Distribusi energi listrik dari genset ke ruang prioritas sebagai energi cadangan terhubung dengan instalasi baru yaitu panel ATS yang hidup secara automatis bila suplai energi listrik dari PLN terputus.Kata kunci:Daya; Distribusi; Listrik; Generator; Efisiensi

Enhancing the Accuracy of Diabetes Prediction Using Feedforward Neural Networks: Strategies for Improved Recall and Generalization Setiawan, Herry; Firnanda, Ary; Khair, Ummul
Brilliance: Research of Artificial Intelligence Vol. 4 No. 1 (2024): Brilliance: Research of Artificial Intelligence, Article Research May 2024
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v4i1.3888

This study explores the development and evaluation of a neural network model for predicting diabetes based on clinical data. The model was built using the Keras API with TensorFlow backend. Key steps included data preprocessing, such as feature scaling with `StandardScaler` and splitting the data into training and testing sets. The neural network architecture consisted of an input layer, two hidden layers with ReLU activation functions, and an output layer with a sigmoid activation function, optimized using the Adam optimizer and binary crossentropy loss function. The model was trained over 50 epochs with a batch size of 10, incorporating a validation split of 20% to monitor performance on unseen data during training. The results demonstrated a high accuracy of approximately 97% on the test set, indicating the model's efficacy in predicting diabetes. Further analysis using a confusion matrix revealed a high count of true positives and true negatives, alongside minimal false positives and false negatives, confirming the model's robustness. These findings suggest that neural networks can be effectively employed for diabetes prediction, offering significant potential for integration into clinical decision support systems. However, further validation with larger and more diverse datasets, alongside considerations for data imbalance and model interpretability, is recommended to ensure generalizability and practical application in real-world healthcare settings.

Implementation of The Internet of Things on Monitoring and Control Tools Hydroponic System Ilham, Dirja Nur; Setiawan, Herry; Harahap, Muhammad Khoiruddin; Firnanda, Ary; Budiansyah, Arie
PERFECT: Journal of Smart Algorithms Vol. 1 No. 1 (2024): PERFECT: Journal of Smart Algorithms, Article Research January 2024
Publisher : LEMBAGA KAJIAN PEMBANGUNAN PERTANIAN DAN LINGKUNGAN (LKPPL)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62671/perfect.v1i1.6

This Hydroponics is a way of growing crops without using soil. Soil that is actually a place for plants to grow can be supported with sand, husk charcoal and rockwool. In a hydroponic system, nutrients and the pH value of water are absolutely necessary for plant development, every plant that requires different levels of nutrients and pH values of the air, if the nutrient levels are lacking then the plant will not grow as well as if the nutrient content is more then the plant will be poisoned. nutrients, water nutrients will continue to decrease along with the development of the plant itself. Therefore, a measuring tool for nutrient levels in hydroponic plant irrigation systems with android monitoring is made so that humans can monitor hydroponic plants. The tool used by Arduino nano as a microprocessor that is integrated into the TDS sensor works to measure nutrient levels and the pH sensor works to measure the pH value of the air, ESP8266 wifi module on NodeMCU as a gateway that aims to be a liaison from Arduino nano to the web server, Using websites and android applications that act as remote controls for nutrient pumps, pH up, pH down and hydroponic water pumps.

Enhancing the Accuracy of Diabetes Prediction Using Feedforward Neural Networks: Strategies for Improved Recall and Generalization Setiawan, Herry; Firnanda, Ary; Khair, Ummul
Brilliance: Research of Artificial Intelligence Vol. 4 No. 1 (2024): Brilliance: Research of Artificial Intelligence, Article Research May 2024
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v4i1.3888

This study explores the development and evaluation of a neural network model for predicting diabetes based on clinical data. The model was built using the Keras API with TensorFlow backend. Key steps included data preprocessing, such as feature scaling with `StandardScaler` and splitting the data into training and testing sets. The neural network architecture consisted of an input layer, two hidden layers with ReLU activation functions, and an output layer with a sigmoid activation function, optimized using the Adam optimizer and binary crossentropy loss function. The model was trained over 50 epochs with a batch size of 10, incorporating a validation split of 20% to monitor performance on unseen data during training. The results demonstrated a high accuracy of approximately 97% on the test set, indicating the model's efficacy in predicting diabetes. Further analysis using a confusion matrix revealed a high count of true positives and true negatives, alongside minimal false positives and false negatives, confirming the model's robustness. These findings suggest that neural networks can be effectively employed for diabetes prediction, offering significant potential for integration into clinical decision support systems. However, further validation with larger and more diverse datasets, alongside considerations for data imbalance and model interpretability, is recommended to ensure generalizability and practical application in real-world healthcare settings.

Influence of Online Transportation on Mandatory and Maintenance Activities in Banda Aceh Novriza, Ferdiansyah; Agusmaniza, Roni; Firnanda, Ary; Zarita, Santi Septiana; Yusra, Cut Liliiza
International Journal of Engineering, Science and Information Technology Vol 5, No 4 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i4.1482

Online transportation has experienced significant growth and has become a vital element in the daily activities in Banda Aceh. Services such as Maxim, Grab, Kururio, Mr. Delivery, Sidoom, and Umma offer convenient access to transportation, goods delivery, and food services, illustrating the growing integration of digital technology into daily urban mobility and lifestyle patterns. In the context of fast-paced urban life, these platforms significantly influence the mobility patterns of the community, both in mandatory activities (such as working and studying) and maintenance activities (such as shopping, picking up children from school, and others). This study highlights the significance of examining how online transportation influences community life. It aims to assess its social, economic, and environmental impacts, identify key determinants of user preferences, and evaluate its overall contribution to improving quality of life within the evolving dynamics of urban mobility. This study employed a mixed-methods approach by integrating quantitative and qualitative techniques, with surveys serving as the primary instrument for data collection. The results indicate that the use of online transportation is influenced by factors such as income, travel time, age, gender, and household size. In terms of service preferences, Food and goods delivery dominates usage (42.9%), followed by motorcycle ride-hailing (38.1%) and cars (19%). These findings underscore the increasing significance of online transportation services in meeting daily needs and enhancing urban mobility, particularly in the areas of goods and food delivery. The results also indicate that public perceptions of the environmental impacts of online transportation remain balanced. While respondents value the improved accessibility and convenience offered by online transit, they are aware of its negative externalities, particularly its role in exacerbating traffic congestion and air pollution.

Career understanding, motivation, and students' decision-making to choose vocational high school (SMK) in non-industrial area MS, Hery Wiharja; Firnanda, Ary
Jurnal Pendidikan Teknologi Kejuruan Vol 4 No 2 (2021): Regular Issue
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/jptk.v4i2.20923

This study aims to measure and describe students' decision-making to choose Vocational High School (SMK) in terms of their career understanding and motivation. The subjects of this study were 135 Year 9 students in five SMK throughout Southwest Aceh Regency. The total sampling method was used to choose the subjects from the entire population. Furthermore, the data were analysed using correlation analysis between variables partially and simultaneously with ANOVA (F test). The results of the partial correlation analysis show that the career understanding variable has a significant influence on students' decision-making to choose SMK with rcount = 0.411 at a significance level of 0.05. In addition, the motivation variable also has a significant influence on decision-making to choose SMK with rcount = 0.375. Simultaneously, career understanding and motivation significantly affect choosing SMK with Fcount = 19.850 and Ftable = 3.06 (Fcount > Ftable). This study results indicate that career understanding variables consist of work planning, work exploration and knowledge of the world of work. In contrast, the motivation variables consist of intrinsic and extrinsic motivation, which could be the basis for students' decision making

Effectiveness of Implementing PCC Load Balancing, Failover, and Time Scheduler Methods for Internet Quality at AKN Aceh Barat Fauza, Rial; Firnanda, Ary
International Journal of Multidisciplinary Sciences and Arts Vol. 5 No. 1 (2026): International Journal of Multidisciplinary Sciences and Arts, Article January 2
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/ijmdsa.v5i1.7749

The internet network configuration at the Akademi Komunitas Negeri Aceh Barat uses MikroTik CCR2116-12G-4S+ router devices with two Internet Service Provider (ISP) connections, implementing the load balancing method Per Connection Classifier (PCC), failover, and time scheduler. MikroTik CCR2116-12G-4S+ is a high-performance Cloud Core Router ideal for multi-ISP load balancing like PCC and failover setups in this research. Its ARM-based architecture eliminates CPU bottlenecks in 10G environments. The PCC method is used to distribute network traffic based on connections consistently to maintain internet access stability. The failover mechanism is implemented through routing settings and gateway checks to ensure service continuity during ISP disruptions. Meanwhile, the time scheduler is used to manage network policies based on operational hours. The study results show that the combination of these methods is highly effective in improving connection stability, bandwidth utilization, and reliability of the multi-ISP network, making it suitable for application in network environments with high internet access demands, such as higher education institutions.

Penentuan Sudut Kemiringan Optimal Instalasi Panel Surya Untuk Memaksimalkan Energi Output: Sistematic Literatur Review Pandria, T. M. Azis; Sya'rani Denk, Teuku Mizan; Tripoli, Bambang; Firnanda, Ary; Saputra, Herdian; Opirina, Lissa
VOCATECH: Vocational Education and Technology Journal Vol 7, No 2 (2025): December
Publisher : Akademi Komunitas Negeri Aceh Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38038/vocatech.v7i2.273

AbstractThis paper presents a systematic literature review on determining the optimal tilt angle (OTA) for photovoltaic solar panel installation. The research method uses a systematic literature review approach by analyzing 30 scientific articles published between 2013 and 2025 from the IEEE Xplore, ScienceDirect, MDPI, and Springer databases. The analysis results show that geographic latitude is the dominant factor in determining OTA, with tropical regions requiring an angle of 5°-15° and mid-high latitude regions requiring 30°-60°. The research methodology has evolved from a simple empirical approach to the use of machine learning and artificial intelligence with a prediction accuracy of R² 0.95. For equatorial regions such as Indonesia, the optimal angle ranges from local latitude ± 5° with low sensitivity to deviation (±5° only affects output 3%). The study also identified that seasonal adjustment provides a 6-15% increase in output for mid-latitude regions, but is not cost-effective for tropical regions. The conclusions of this study provide practical recommendations based on geographic zones and identify research gaps related to climate change impacts, optimization for bifacial technology, and development of economically adaptive systems. Keywords:Solar panels; optimal tilt angle; energy optimization; systematic literature review AbstrakNaskah ini menyajikan tinjauan literatur sistematis tentang penentuan sudut kemiringan optimal (optimal tilt angle/OTA) untuk instalasi panel surya fotovoltaik. Metode penelitian menggunakan pendekatan systematic literature review dengan menganalisis 30 artikel ilmiah yang dipublikasikan antara tahun 2013 hingga 2025 dari database IEEE Xplore, ScienceDirect, MDPI, dan Springer. Hasil analisis menunjukkan bahwa lintang geografis merupakan faktor dominan dalam penentuan OTA, dengan wilayah tropis memerlukan sudut 5°-15° dan wilayah lintang menengah-tinggi memerlukan 30°-60°. Metodologi penelitian telah berkembang dari pendekatan empiris sederhana menuju penggunaan machine learning dan artificial intelligence dengan akurasi prediksi R² 0.95. Untuk wilayah ekuatorial seperti Indonesia, sudut optimal berkisar antara lintang lokal ± 5° dengan sensitivitas rendah terhadap deviasi (±5° hanya mempengaruhi output 3%). Penelitian juga mengidentifikasi bahwa penyesuaian musiman memberikan peningkatan output 6-15% untuk wilayah lintang menengah, namun tidak cost-effective untuk wilayah tropis. Simpulan penelitian ini memberikan rekomendasi praktis berbasis zona geografis dan mengidentifikasi gap penelitian terkait dampak perubahan iklim, optimalisasi untuk teknologi bifacial, dan pengembangan sistem adaptif yang ekonomis.Kata Kunci: Panel surya; sudut kemiringan optimal; optimalisasi energi; Sistematic Literature Review

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