Aplikasi Pengolahan Citra: Kombinasi Edge Detection dan LBPH (Local Binary Pattern Histogram) Untuk Pengenalan Daun Herbal

Penelitian ini bertujuan untuk sistem pengenalan daun herbal dengan menggunakan teknologi pengolahan citra. Penelitian ini menghitung akurasi sistem pengenalan daun yang mengkombinasikan Edge Detection untuk mendeteksi dan LBPH untuk mengklasifikasikan daun herbal. Pengujian dilakukan terhadap 40 daun yang dikelompokkan menjadi 5 jenis daun herbal. Pengelompokan berdasarkan jenis daun yang paling mudah ditemukan di Indonesia. Pengujian dilakukan menggunakan metode confusion matriks. Dari hasil pengujian diperoleh kesimpulan bahwa kombinasi antara edge detection dan LBPH kurang baik untuk mengenali daun herbal

A MACHINE LEARNING APPROACH TO EYE BLINK DETECTION IN LOW-LIGHT VIDEOS

Inadequate lighting conditions can harm the accuracy of blink detection systems, which play a crucial role in fatigue detection technology, transportation and security applications. While some video capture devices are now equipped with flashlight technology to enhance lighting, users occasionally need to remember to activate this feature, resulting in slightly darker videos. Consequently, there is a pressing need to improve the performance of blink detection systems to detect eye accurately blinks in low light videos. This research proposes developing a machine learning-based blink detection system to see flashes in low-light videos. The Confusion matrix was conducted to evaluate the effectiveness of the proposed blink detection system. These tests involved 31 videos ranging from 5 to 10 seconds in duration. Involving male and female test subjects aged between 20 and 22. The accuracy of the proposed blink detection system was measured using the confusion matrix method. The results indicate that by leveraging a machine learning approach, the blink detection system achieved a remarkable accuracy of 100% in detecting blinks within low-light videos. However, this research necessitates further development to account for more complex and diverse real-life situations. Future studies could focus on developing more sophisticated algorithms and expanding the test subjects to improve the performance of the blink detection system in low light conditions. Such advancements would contribute to the practical application of the system in a broader range of scenarios, ultimately enhancing its effectiveness in fatigue detection technology

LEAF DISEASE DETECTION IN TOMATO PLANTS USING XCEPTION MODEL IN CONVOLUTIONAL NEURAL NETWORK METHOD

This study aims to detect leaf diseases in tomato plants by applying the Xception model in the Convolutional Neural Network (CNN) method. The study categorizes tomato conditions into three main categories: Early Blight, Late Blight, and Healthy. Early Blight is generally infected by specific pathogens that cause spots and damage in the early stages of plant growth, while Late Blight is infected by pathogens in the later stages of the growing season. Meanwhile, the healthy category indicates normal conditions without disease symptoms. The dataset used consists of 300 tomato images, with each category having 100 images. In the model training phase using the fit method in TensorFlow, 17 epochs were performed to teach the model to recognize patterns in tomato leaf disease images in the training dataset. The model testing results on 30 tomato leaf images showed an accuracy rate of 85.84%. This result indicates a positive indication that the developed CNN model performs well in detecting and classifying tomato leaf conditions. Thus, this research can contribute to improving the understanding and management of leaf diseases in tomato plants to support more productive and sustainable agriculture

Introduction Internet of Things Design for Students in SMKs Darul Ulum Layoa Bantaeng

Abstract. IoT (Internet of Things) technology is currently experiencing very rapid development. Several innovative and creative applications, most IoT-based, have been found. IoT underlies the existence of smart home technology. One of the advantages of smart home technology is that homeowners can control conditions and monitor home security using only one device. Unfortunately, at SMKs Darul Ulum Layoa, Bantaeng, Sulawesi Selatan (South Sulawesi), learning about IoT still needs to be improved. It becomes the basis for why we hold a community service activity. This activity provided understanding and training on the Internet of Things, which 40 teachers and students attended. Pretest and posttest methods are used to determine the activity's success level. Both results were processed using the SPSS (Statistical Package for the Social Sciences) method. SPSS is a statistical software used to perform data analysis, including descriptive and inferential analysis. By utilizing the Wilcoxon Signed Rank Test, an analysis of the data revealed a Z value of -5.026 and a p-value of 0.000. These findings indicate a significant difference between the pretest and posttest groups or a significant increase in scores between the pretest and posttest. Therefore, the intervention had a positive effect on the outcome being measured

Pelatihan teknologi informasi pada kantor kelurahan Barrang Caddi Kepulauan Sangkarrang

As a public service provider, the sub-district office plays a crucial role in the issuance of referral letters and certificates. In this era of digitalization, effective and efficient administrative services are demanded, necessitating the improvement of staff knowledge and skills in information technology literacy. Hence, this community engagement activity aims to enhance the quality of administrative services by empowering human resources to operate computers and office applications at the Barrang Caddi Sub-district Office. The training program spans 3 days, encompassing Microsoft Word and Excel tutorials, as well as E-Mail usage. Enthusiasm was evident among the participants, which consisted of 7 sub-district office staff and 4 residents, as they actively engaged in the activities and completed the assigned tasks. The evaluation results demonstrate that the participants have comprehended and effectively applied the knowledge imparted during the training. The training materials have assisted the participants in optimizing their information technology knowledge and skills, such as efficiently managing administrative documents using Microsoft Office, operating E-Mail, and understanding the essential tools in Excel. This training validates the significance of information technology literacy efforts in sub-district office settings, particularly in areas with limited access to information. It is hoped that this community engagement initiative will continue and provide sustained benefits in enhancing administrative services and human resources quality at the Barrang Caddi Sub-district OfficeSebagai penyedia layanan umum, kantor kelurahan memiliki tugas penting dalam pembuatan surat pengantar dan surat keterangan. Di era digitalisasi saat ini, pelayanan administrasi yang efektif dan efisien menjadi tuntutan, yang memerlukan peningkatan pengetahuan dan keterampilan staf dalam literasi teknologi informasi. Oleh karena itu, kegiatan pengabdian ini bertujuan untuk meningkatkan kualitas pelayanan administrasi kantor dengan meningkatkan kemampuan sumber daya manusia dalam mengoperasikan komputer dan aplikasi perkantoran di Kantor Kelurahan Barrang Caddi. Kegiatan pelatihan berlangsung selama 3 hari, yang mencakup materi Microsoft Word dan Excel, serta penggunaan E-Mail. Para peserta pelatihan, termasuk 7 staf kantor kelurahan dan 4 warga sekitar, menunjukkan antusiasme dalam mengikuti rangkaian kegiatan dan berhasil menyelesaikan tugas-tugas yang diberikan. Hasil evaluasi kegiatan menunjukkan bahwa para peserta telah memahami dan menerapkan dengan baik apa yang diajarkan selama pelatihan. Materi pelatihan membantu peserta dalam mengoptimalkan pengetahuan dan keterampilan teknologi informasi, seperti mengelola dokumen administrasi dengan lebih efisien menggunakan Microsoft Office, mengoperasikan E-Mail, dan memahami penggunaan alat-alat penting dalam aplikasi Excel. Pelatihan ini membuktikan pentingnya upaya literasi teknologi informasi di lingkungan kantor kelurahan, terutama di daerah-daerah dengan minim informasi. Diharapkan bahwa kegiatan pengabdian ini dapat berlanjut dan memberikan manfaat yang berkelanjutan bagi peningkatan pelayanan administrasi dan kualitas sumber daya manusia di Kantor Kelurahan Barrang Caddi

Deteksi Mata di Video Smartphone Menggunakan Mediapipe Python

Teknologi deteksi mata digunakan untuk mengenali dan menganalisis fitur-fitur unik pada mata seseorang sebagai cara untuk mengidentifikasi atau mengautentikasi identitas seseorang. Teknologi ini dapat digunakan dalam berbagai aplikasi, seperti pengenalan pola, sistem biometrik, sistem pengawasan, dan lainnya. Kebanyakan aplikasi memerlukan ketepatan dalam mendeteksi mata, sehingga diperlukan metode deteksi mata yang cepat dan andal. Dalam penelitian ini, diajukan metode deteksi mata yang menggunakan library Python OpenCV dan MediaPipe, yang menawarkan akurasi yang lebih baik dibandingkan solusi yang sudah ada. Kedua pustaka tersebut diimplementasikan dalam bahasa pemrograman Python, yang populer di kalangan pengembang perangkat lunak karena kemampuan pemrograman berorientasi objek, kemampuan untuk memanipulasi dan memproses data dengan mudah, serta pustaka dan modul yang tersedia dalam berbagai bidang seperti kecerdasan buatan. Pengujian sistem dilakukan dengan menggunakan video yang diambil menggunakan telepon pintar. Meskipun video diambil dalam kondisi kurang optimal, yaitu dengan pencahayaan yang tidak sempurna, pengujian dilakukan pada 56 video yang memiliki kualitas cukup baik dengan durasi sekitar 5-10 detik. Hasil yang diperoleh menunjukkan tingkat akurasi yang mencapai 100%. Selain itu, sistem yang dibuat mampu membedakan antara kondisi mata terbuka dan tertutup, yang akan memudahkan penelitian selanjutnya dalam mendeteksi kedipan mata. Kesimpulan yang dapat diambil adalah model yang telah dibuat mampu mendeteksi mata dengan tingkat akurasi yang sangat tingg