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Advanced Instance Segmentation of Aeroponics Tissue Culture-Based Seeds Potatoes Based on Improved YOLOv8l-small Avisyah, Gisnaya Faridatul; Kurnianingsih, Kurnianingsih; Hidayat, Sidiq Syamsul
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.9.4.3085

Abstract

To improve agricultural production, this study develops an advanced instance segmentation system for aeroponic tissue culture-based potato seedlings. We present an IoT system that integrates multiple sensors for humidity, temperature, pH, and turbidity to enable real-time monitoring. Additionally, we adapt the YOLOv8l-small computer vision model, an optimized version of YOLOv8, designed explicitly for efficient potato leaf disease detection and segmentation, even in resource-constrained IoT environments. YOLOv8 is a significant advancement in the YOLO series, for instance, segmentation, combining better accuracy, efficiency, and flexibility. YOLOv8 outperforms previous methods in generating precise segmentation masks while maintaining real-time performance. These innovations make YOLOv8 a robust choice for a variety of computer vision tasks, including instance segmentation, in both research and practical applications. When tested on a custom dataset of potato leaf pictures, the suggested model produced mask mAP50 of 0.842 and mAP50-95 of 0.566, with a model size of 36.1 MB and an inference duration of 9.3 ms. These outcomes are similar to those of the original YOLOv8l model, which had a slower inference time of 11.0 ms and a much larger model size of 92.3 MB, albeit at the expense of a somewhat higher mAP50 of 0.843. The study concludes that the proposed model provides similar accuracy with greater computational efficiency, making it ideal for IoT-based agricultural systems. Future research will explore additional aspects, while practical experiments aim to reduce labor costs.
Design of Temperature Monitoring and Control System in Smart Hen Coop Based on Internet of Things Parandy, La Mema; Hidayat, Sidiq Syamsul; Robby, Muhammad; Azhar, Rachael Al; Mujahidin, Irfan; Prabowo, M. Cahyo Ardi
Journal of Information System, Technology and Engineering Vol. 2 No. 2 (2024): JISTE
Publisher : Yayasan Gema Bina Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61487/jiste.v2i2.68

Abstract

Every temperature error detected by the system would be notified to users by the Blynk application, and the system would attempt to stabilize the temperature in hen coop with a lamp and fan. Notification from the Blynk application is set to stop until the temperature returns to an ideal. The Blynk application is equipped with a reset button to reset the chicken age counter. This system used temperature and humidity sensors DHT22 to sense the temperature, which the data from the sensor output read by Arduino Uno. The data that Arduino Uno reads is sent to NodeMCU. Afterward, NodeMCU sent the data to the Blynk server; therefore, the Blynk application displayed the temperature and humidity data on the Blynk dashboard. This system is expected to facilitate users/breeders in monitoring the temperature in the hen coop. Therefore, users/breeders do not need to worry about chickens dying due to heat or cold stress. The waterfall method is used in this design of the system. This system was tested in a 70 x 70 x 130 cm sized hen coop and entirely tested the system each minute for 35 minutes.
Monitoring System for Website-Based Micro Hydro Power Plant using Firebase Hidayat, Sidiq Syamsul; Mulyaman, Heri Bertus; Basuki, Budi; Mujahidin, Irfan; Prabowo, M. Cahyo Adi; Lestari, Melisa Yufit; Rakhman, Fikri Arif
Jurnal Informatika: Jurnal Pengembangan IT Vol 9, No 2 (2024)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v9i2.6542

Abstract

The use of electrical energy is a basic need for everyone. Micro Hydro Power Plant is one of the technologies that has developed recently. This technology has little adverse impact on the environment. This plant utilizes flowing water, discharge from water, and water pressure. The highlands or mountainous areas where there is flowing water. This water flow can be used as a driving force to drive a turbine, which is the driving force for this power plant because the generator uses a generator that requires motion power to generate electricity. Because this plant utilizes flowing water as a power source to drive a turbine and turn a generator. So basically, where there is running water, there is electricity. Moreover, micro Hydro does not need to build large reservoirs like hydropower. The purpose of making this system is to make it easier to check the condition of the MHP equipment and record the data obtained from the sensors that have been installed. This Website was successfully implemented using HTML, PHP, Firebase Database, CSS, JavaScript, JSON, etc. This Website will use the waterfall method, which consists of observation and needs analysis, system design, modeling, implementation and coding, testing, and maintenance
Real-Time Web-Based Monitoring System for Temperature, Humidity, and Solar Panels in Ramie Drying Facilities Hidayat, Sidiq Syamsul; Shabiya, Kiara Izzatus; Kadiran, Sri Anggraeni; Mujahidin, Irfan; Prabowo, M. Cahyo Ardi; Nursyahid, Arif; Wasito, Endro; Helmy, Helmy
Scientific Journal of Informatics Vol 11, No 1 (2024): February 2024
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v11i1.47234

Abstract

Purpose: To address the manual monitoring challenges in processing ramie fibers, especially during drying. The purpose is to create a monitoring system that oversees room temperature, humidity, and the status of solar panels, crucial factors in ramie productivity.Methods: Real-time web-based system development that monitors room temperature, humidity, and the performance of solar panels in a ramie drying room using the Internet of Things architecture ESP32 with communication through GSM SIM 800L in rural areas.Results: The system can display real-time information such as temperature data, humidity, and electrical energy parameters derived from the solar panel's utilization in the ramie drying room. By doing so, users gain efficiency and effectiveness in obtaining information, significantly enhancing ramie fiber productivity.Novelty:  Integration of sensor instruments, low-power ESP32 microcontrollers, GSM Telecommunication, Solar Cell Energy as a power source, and a real-time web-based Monitoring Information System implemented in a ramie drying dome. This simplifies the monitoring process and optimizes limited resources such as space, energy, telecommunications, and human resources, which are typically constrained infrastructure in the ramie fiber agricultural system.
Penerapan Dan Pendampingan Sistem Nutrisi Otomatis Berbasis Iot Untuk Meningkatkan Produktivitas Pembenihan Hortikultura Di Screen House Yayasan Wadah Jalinan Dermawan, Gunungpati, Semarang Mujahidin, Irfan; Hidayat, Sidiq Syamsul; Hasanah, Siti
Patria Artha Journal of Community (PKM) Vol 5, No 2 (2025): Patria Artha Journal of Community
Publisher : Universitas Patria Artha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33857/pajoco.v5i2.1011

Abstract

Pengabdian masyarakat ini bertujuan untuk meningkatkan pemahaman masyarakat terhadap penggunaan, operasional, dan perawatan sistem nutrisi otomatis berbasis Internet of Things (IoT) dalam rangka mendukung produktivitas pembenihan hortikultura di screen house Yayasan Wadah Jalinan Dermawan, Gunungpati, Semarang. Metode pelaksanaan dilakukan melalui penerapan sistem teknologi, pendampingan intensif, serta evaluasi berbasis instrumen kuesioner yang mencakup 10 pertanyaan pokok terkait aspek teknis maupun praktis penggunaan sistem. Analisis data menggunakan pendekatan deskriptif dengan menghitung frekuensi, persentase, nilai rata-rata, serta standar deviasi untuk memotret tingkat pemahaman responden. Hasil survei menunjukkan adanya peningkatan signifikan, di mana rata-rata pemahaman masyarakat yang semula berada pada kisaran 30% meningkat hingga mencapai 72% setelah kegiatan pendampingan. Peningkatan ini mencakup aspek keterampilan mengoperasikan perangkat, memahami prinsip kerja sensor dan aktuator, serta kemampuan melakukan perawatan preventif sistem IoT. Secara inferensial, uji perbandingan menunjukkan adanya perbedaan nyata sebelum dan sesudah intervensi, yang menegaskan efektivitas kegiatan pengabdian. Selain itu, visualisasi data dalam bentuk grafik batang dan lingkaran memperjelas persepsi responden terhadap kemudahan penggunaan dan kebermanfaatan sistem. Dengan demikian, penerapan teknologi nutrisi otomatis berbasis IoT terbukti mampu mendorong kemandirian mitra dalam pengelolaan screen house sekaligus meningkatkan kapasitas pengetahuan masyarakat lokal. Program ini tidak hanya relevan untuk peningkatan kualitas pembenihan hortikultura, tetapi juga menjadi model penerapan teknologi tepat guna dalam sektor pertanian modern berbasis digital.
Analisis Kebutuhan dan Prediksi Parkir menggunakan Metode Regresi Linier Lady, Rienisti Ellen; Suharjono, Amin; Hidayat, Sidiq Syamsul
TELKA - Telekomunikasi Elektronika Komputasi dan Kontrol Vol 11, No 3 (2025): TELKA
Publisher : Jurusan Teknik Elektro UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/telka.v11n3.389-398

Abstract

Kebutuhan fasilitas parkir rumah sakit merupakan bagian penting mengingat fasilitas parkir merupakan bagian yang tak bisa dipisahkan dari sistem transportasi. Selain itu, bagi suatu rumah sakit, kebutuhan tempat parkir akan selalu meningkat seiring dengan perkembangan fasilitas layanan kesehatan yang ada di rumah sakit tersebut. Penelitian  ini bertujuan untuk menentukan kebutuhan lahan parkir melalui nilai Indeks Parkir dan prediksi jumlah kendaraan parkir di RS Mardi Rahayu, Kudus. Metode perhitungan Indeks Parkir dilakukan dengan perhitungan volume parkir, durasi parkir, angka pergantian parkir dan prediksi jumlah kendaraan menggunakan metode Regresi Linier. Pengambilan data dilakukan pada bulan Januari-Maret 2023. Hasil penelitian menunjukkan secara umum volume maksimal kendaraan, baik motor maupun mobil, terjadi pada hari Selasa hingga Kamis antara minggu pertama hingga minggu ketiga setiap bulan. Berdasarkan hasil analisis angka pergantian parkir dan indeks parkir, petak parkir yang ada saat penelitian ini dilakukan tidak cukup untuk melayani volume kendaraan para pengunjung karena memiliki nilai Indeks Parkir lebih dari 100%. Hasil analisis regresi linier mendapati bahwa kendaraan terbanyak diprediksi setelah 120 menit dan lonjakan kendaraan diprediksi terjadi pada menit ke 30. Penelitian ini merekomendasikan penambahan petak parkir kendaraan motor sejumlah 13 petak dan untuk kendaraan mobil 5 petak. Alternatif lain selain penambahan petak dapat dilakukan dengan memperluas lahan parkir. Hospital parking facilities are crucial, as parking is an integral part of the transportation system. Furthermore, the need for parking spaces for hospitals continues to increase along with the development of healthcare facilities. This study aims to determine parking space requirements through the Parking Index value and predict the number of parked vehicles at Mardi Rahayu Hospital, Kudus. The Parking Index calculation method involves calculating parking volume, parking duration, parking turnover rate, and predicting the number of vehicles using the Linear Regression method. Data collection was conducted between January and March 2023. The results indicate that the maximum vehicle volume, both motorcycles and cars, generally occurs on Tuesdays through Thursdays between the first and third weeks of each month. Based on the analysis of parking turnover rates and the parking index, the existing parking spaces at the time of this study were insufficient to accommodate the volume of visitors, as the Parking Index value exceeded 100%. The linear regression analysis found that the highest number of vehicles was predicted to arrive after 120 minutes, with a predicted surge in traffic occurring at the 30th minute. This study recommends adding 13 parking spaces for motorcycles and 5 parking spaces for cars. Another alternative besides adding plots is to expand the parking area.
Determining the Rice Seeds Quality Using Convolutional Neural Network Hidayat, Sidiq Syamsul; Rahmawati, Dwi; Prabowo, Muhamad Cahyo Ardi; Triyono, Liliek; Putri, Farika Tono
JOIV : International Journal on Informatics Visualization Vol 7, No 2 (2023)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.7.2.1175

Abstract

Seed inspection is crucial for plant nurseries and farmers as it ensures seed quality when growing seedlings. It is traditionally accomplished by expert inspectors filtering samples manually, but there are some challenges, such as cost, accuracy, and large numbers. Speed and accuracy were the main conditions for increasing agricultural productivity. Machine learning is a sub-science of Artificial Intelligence that can be applied in research on the classification of rice seed quality. The pipeline of a machine learning system is dataset collection, training, validation, and testing. Model making begins with taking data on the characteristics of rice seeds based on physical parameters in the form of seed shape and color. The dataset used is two thousand images divided into two categories, namely superior seeds and non-superior seeds. Training and Validation was conducted using the Convolutional Neural Network (CNN) algorithm with the concept of cross-validation on Google Collaboratory notebooks. The ratio split of train data and validation data in modeling from a dataset is 80:20. The result of the model formed is a model with the development of a Deep Convolutional Neural Network (Deep CNN) that can classify the digital image data of rice seeds from the results of data calls uploaded into the system. The results of the experiment conducted on 30 test data can be analyzed so that the system can classify superior and non-superior seeds with a precision value of 93% and a recall of 95%.