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PROTOTIPE AUTOMATIC FEEDER DENGAN MONITORING IoT UNTUK PERIKANAN BIOFLOK LELE MASYARAKAT DUKUH PRAYUNAN Maghfiroh, Hari; Hermanu, Chico; Adriyanto, Feri
Jurnal Abdimas Vol 24, No 1 (2020): June
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat (LP2M), Universitas Negeri Semarang

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

The Industrial Revolution 4.0 has brought many changes both positive and negative. The positive aspect is that there has been much use of automation and robots in the industrial world so that production can increase rapidly. While the negative angle, more and more human work is replaced by machines so that it reduces job opportunities. The existence of the industrial revolution 4.0 also brought a gap between the technology literacy group and the technology stutterer group (gaptek). Villagers are a large group from the second class. For this reason, a new business opportunity that can be carried out by the village community with secondary education level is urgently needed. Then the catfish bio-floc fisheries program was chosen. A touch of automation technology and the Internet of Things (IoT) is given to increase productivity and make people literate about the technological development of the industrial revolution era 4.0.

PROTOTIPE AUTOMATIC FEEDER DENGAN MONITORING IoT UNTUK PERIKANAN BIOFLOK LELE MASYARAKAT DUKUH PRAYUNAN Maghfiroh, Hari; Hermanu, Chico; Adriyanto, Feri
Jurnal Abdimas Vol 24, No 1 (2020): June 2020
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/abdimas.v24i1.20636

The Industrial Revolution 4.0 has brought many changes both positive and negative. The positive aspect is that there has been much use of automation and robots in the industrial world so that production can increase rapidly. While the negative angle, more and more human work is replaced by machines so that it reduces job opportunities. The existence of the industrial revolution 4.0 also brought a gap between the technology literacy group and the technology stutterer group (gaptek). Villagers are a large group from the second class. For this reason, a new business opportunity that can be carried out by the village community with secondary education level is urgently needed. Then the catfish bio-floc fisheries program was chosen. A touch of automation technology and the Internet of Things (IoT) is given to increase productivity and make people literate about the technological development of the industrial revolution era 4.0.

Making an Electric Vehicle Charging System as a learning tool for the community About Electric Vehicles Adriyanto, Feri; Nizam, Muhammad; Anwar, Miftahul; Ramelan, Agus; Warindi, Warindi; Saputro, Joko Slamet; Inayati, Inayati
Jurnal Abdimas Vol 27, No 2 (2023): December 2023
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/abdimas.v27i2.48670

The purpose of this service program is to introduce coomunity in Magetan Regency to electric vehicle technology. The material presented is basic material covering the meaning, benefits, and components of electric vehicles using developing charging system prototipe. people who visit the Refugia Garden are asked to immediately try the electric vehicle and after completion are asked to carry out the charging process themselves. By observing and trying it directly, it is hoped that the community's main set of electric vehicles will be formed as a way to reduce carbon emissions.The purpose of this service program is to introduce coomunity in Magetan Regency to electric vehicle technology. The material presented is basic material covering the meaning, benefits, and components of electric vehicles using developing charging system prototipe. people who visit the Refugia Garden are asked to immediately try the electric vehicle and after completion are asked to carry out the charging process themselves. By observing and trying it directly, it is hoped that the community's main set of electric vehicles will be formed as a way to reduce carbon emissions.

Design of intelligent cruise control system using fuzzy-PID control on autonomous electric vehicles prototypes Saputro, Joko Slamet; Anwar, Miftahul; Adriyanto, Feri; Ramelan, Agus; Yusuf, Putra Maulana; Irsyadi, Fakih; Firmansyah, Rendra Dwi; Putri, Tri Wahyu Oktaviana
Journal of Mechatronics, Electrical Power, and Vehicular Technology Vol 15, No 1 (2024)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/j.mev.2024.877

Electric vehicles provide a solution for using alternative fuels, namely, electricity. Electric vehicles are used for short distances and intercity travel over long distances, increasing the risk of accidents. Cruise Control is a technology embedded in vehicles to maintain stable speeds; this system will automatically adjust the vehicle's speed when motion changes cause changes in vehicle speed. This study aims to apply lidar sensors to detect distance in the Intelligent Cruise Control (ICC) system using the Fuzzy-PID control method. Testing results were obtained at safe distance inputs of 5, 6, and 7 meters with various object distances. All the tests were carried out; the response systems were obtained with an average settling time of 5 seconds and an average overshoot of 1.53%. Therefore, the proposed Fuzzy-PID method works well for controlling Intelligent Cruise Control systems in autonomous electric vehicle prototypes.

Application of Sentiment Analysis as an Innovative Approach to Policy Making: A review Firdaus, Asno Azzawagama; Saputro, Joko Slamet; Anwar, Miftahul; Adriyanto, Feri; Maghfiroh, Hari; Ma'arif, Alfian; Syuhada, Fahmi; Hidayat, Rahmad
Journal of Robotics and Control (JRC) Vol 5, No 6 (2024)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v5i6.22573

This literature review comprehensively explains the role of sentiment analysis as a policymaking solution in companies, organizations, and individuals. The issue at hand is how sentiment analysis can be effectively applied in decision making. The solution is to integrate sentiment analysis with the latest NLP trends. The contribution of this research is the assessment of 100-200 recent studies in the period 2020-2024 with a sample of more than 5,000 data, as well as the impact of the resulting policy recommendations. The methods used include evaluation of techniques such as Deep Learning, lexicon-based, and Machine Learning, using evaluation matrices such as F1-score, precision, recall, and accuracy. The results showed that Deep Learning techniques achieved an average accuracy of 93.04%, followed by lexicon-based approaches with 88.3% accuracy and Machine Learning with 83.58% accuracy. The findings also highlight the importance of data privacy and algorithmic bias in supporting more responsive and data-driven policymaking. In conclusion, sentiment analysis is reliable in areas such as e-commerce, healthcare, education, and social media for policy-making recommendations. However, special attention should be paid to challenges such as language differences, data bias, and context ambiguity which can be addressed with models such as mBERT, model auditing, and proper tokenization.

Prototype Perancangan dan Implementasi Alat Perontok dan Pengering Padi Otomatis dengan Konsep Teknologi Pembangkit Listrik Tenaga Surya untuk Meningkatkan Produktivitas Hasil Pertanian Sulistyo, Meiyanto Eko; Apribowo, Chico Hermanu Brillianto; Adriyanto, Feri
Jurnal Bumigora Information Technology (BITe) Vol 3 No 1 (2021)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/bite.v3i1.1305

Dewasa ini pemanfaatan teknologi untuk meningkatkan hasil pertanian tumbuh pesat. Salah satu bentuk pemanfaatannya adalah dengan menggunakan energi terbarukan untuk meningkatkan produktivitas hasil pertanian. Energi terbarukan yang implementasinya sudah sangat banyak adalah Pembangkit Listrik Tenaga Surya (PLTS). Pengunaan PLTS sebagai sumber energi alternatif yang digunakan untuk pengerak alat perontok dan pengering padi otomatis. Petani selalu kesulitan saat musim penghujan maupun kemarau kering tiba-tiba dan sinar matahari tidak dapat mencapai intensitas maksimal saat digunakan untuk mengeringkan padi secara konvensional, oleh karena itu alat perontok dan pengeringan padi otomatis tenaga PLTS sebagai alternatif solusi. Tujuan penelitian ini adalah untuk memberi wawasan dan pengetahuan akan pembuatan dan prinsip kerja dari alat perontok dan pengeringan padi otomatis tenaga PLTS sebagai alternatif solusi untuk meningkatkan padi secara teknologi, dengan demikian diharapkan masyarakat mendapatkan manfaat lebih cepat dalam pengeringan padi dan menghemat biaya untuk pengeluaran memanen padi, sehingga dapat meningkatkan produktivitas hasil pertanian.

Project-Based Learning Approach in Autonomous Vehicle Course During Pandemic Outbreak: A Study Case Saputro, Joko Slamet; Adriyanto, Feri; Anwar, Miftahul; Ibrahim, Sutrisno; Latifan, Syaifullah Filard
Journal of Education Technology Vol. 8 No. 3 (2024): August
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/jet.v8i3.76342

The COVID-19 pandemic has had a major impact on the education sector, including universities, which must immediately switch from classical learning to online learning. In the Electrical Engineering study program at Sebelas Maret University, one of the main challenges is achieving the learning output targets set in the courses, especially in the Autonomous Vehicles course. This study aims to examine the implementation of the Project-Based Learning (PBL) approach in the Autonomous Vehicles course during the pandemic, as well as to understand students' perceptions of the learning methods applied, including through online learning with blended learning. The study used a case study approach, where students were divided into three groups to work on an autonomous vehicle simulation project using Webots software. Each group faced different challenges, such as avoiding obstacles, overtaking other vehicles, and self-parking. A questionnaire was used to collect data on students' perceptions of the implementation of PBL. The results showed that PBL was successfully implemented well in the Autonomous Vehicles course, although there were several challenges, especially related to the duration of the project. Overall, students felt that this method was effective in improving their technical and soft skills, such as critical thinking, problem solving, and teamwork.

Application of Sentiment Analysis as an Innovative Approach to Policy Making: A review Firdaus, Asno Azzawagama; Saputro, Joko Slamet; Anwar, Miftahul; Adriyanto, Feri; Maghfiroh, Hari; Ma'arif, Alfian; Syuhada, Fahmi; Hidayat, Rahmad
Journal of Robotics and Control (JRC) Vol. 5 No. 6 (2024)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v5i6.22573

This literature review comprehensively explains the role of sentiment analysis as a policymaking solution in companies, organizations, and individuals. The issue at hand is how sentiment analysis can be effectively applied in decision making. The solution is to integrate sentiment analysis with the latest NLP trends. The contribution of this research is the assessment of 100-200 recent studies in the period 2020-2024 with a sample of more than 5,000 data, as well as the impact of the resulting policy recommendations. The methods used include evaluation of techniques such as Deep Learning, lexicon-based, and Machine Learning, using evaluation matrices such as F1-score, precision, recall, and accuracy. The results showed that Deep Learning techniques achieved an average accuracy of 93.04%, followed by lexicon-based approaches with 88.3% accuracy and Machine Learning with 83.58% accuracy. The findings also highlight the importance of data privacy and algorithmic bias in supporting more responsive and data-driven policymaking. In conclusion, sentiment analysis is reliable in areas such as e-commerce, healthcare, education, and social media for policy-making recommendations. However, special attention should be paid to challenges such as language differences, data bias, and context ambiguity which can be addressed with models such as mBERT, model auditing, and proper tokenization.

Concerns of Ethical and Privacy in the Rapid Advancement of Artificial Intelligence: Directions, Challenges, and Solutions Furizal, Furizal; Ramelan, Agus; Adriyanto, Feri; Maghfiroh, Hari; Ma'arif, Alfian; Kariyamin, Kariyamin; Masitha, Alya; Fawait, Aldi Bastiatul
Journal of Robotics and Control (JRC) Vol. 5 No. 6 (2024)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v5i6.24090

AI is a transformative technology that emulates human cognitive abilities and processes large volumes of data to offer efficient solutions across various sectors of life. Although AI significantly enhances efficiency in many areas, it also presents substantial challenges, particularly regarding ethics and user privacy. These challenges are exacerbated by the inadequacy of global regulations, which may lead to potential abuse and privacy violations. This study provides an in-depth review of current AI applications, identifies future needs, and addresses emerging ethical and privacy issues. The research explores the important roles of AI technologies, including multimodal AI, natural language processing, generative AI, and deepfakes. While these technologies have the potential to revolutionize industries such as content creation and digital interactions, they also face significant privacy and ethical challenges, including the risks of deepfake abuse and the need for improved data protection through platforms like PrivAI. The study emphasizes the necessity for stricter regulations and global efforts to ensure ethical AI use and effective privacy protection. By conducting a comprehensive literature review, this research aims to provide a clear perspective on the future direction of AI and propose strategies to overcome barriers in ethical and privacy practices.

Robust SVM optimization using PSO and ACO for accurate lithium-ion battery health monitoring Putra, Mufti Reza Aulia; Nizam, Muhammad; Mujianto, Agus; Adriyanto, Feri; Santoso, Henry Probo; Afandi, Arif Nur; Gunadin, Indar Chaerah
Mechanical Engineering for Society and Industry Vol 5 No 1 (2025)
Publisher : Universitas Muhammadiyah Magelang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31603/mesi.12280

The increasing demand for reliable lithium-ion battery in various applications is focused on the need for accurate State of Health (SOH) predictions to prevent performance degradation and potential safety risks. Therefore, this research aimed to improve the accuracy of SOH prediction by integrating Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) with Support Vector Machine (SVM) to overcome the overfitting problem in traditional machine learning models. The dataset used consisted of data from 1000 cycles of lithium-ion battery, collected under laboratory conditions. Data from lithium-ion battery cycles were analyzed using optimized PSO-SVM and ACO-SVM models. These models were evaluated using Mean Square Error (MSE) and Root Mean Square Error (RMSE) metrics, showing significant improvements in prediction accuracy and model generalization. The results showed that although both optimized models were superior to the baseline SVM, PSO-SVM had higher generalization performance during testing. The higher performance was due to the effective balance between exploring the search space and exploiting optimal solutions, making it more suitable for real-world applications. In comparison, ACO-SVM showed superior performance in training data accuracy but was more prone to overfitting, suggesting the potential for scenarios prioritizing high training accuracy. These results could be applied to extend the lifespan of lithium-ion battery, contributing to enhanced reliability and cost-effectiveness in applications.

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