27 research outputs found
Buku Panduan Aplikasi Monitoring Kandang Closed House Berbasis Mobile
Get PDFPatent dengan jenis: Buku Panduan/Petunjuk, Berjudul Buku Panduan Aplikasi Monitoring Kandang Closed House Berbasis Mobile, yang ditulis oleh: Mahar Faiqurahman, Merinda Lestandy, Novendra Setyawan, Basri Noor Cahyadi, Lailis Syafa’ah, dan Zulfatman
Pengembangan Adaptive Particle Swarm Optimization (PSO) Dan Aplikasinya Pada Perencanaan Jalur Mobile Robot Dengan Halangan Dinamis
Get PDFKunci sukses dari navigasi sebuah mobile robot bergantung pada
pembangkitan trajektori atau perencanaan jalur. Perencanaan jalur berbasis metode
optimasi heuristik dikembangkan untuk menyederhanakan permasalaahan
perencanaan jalur menjadi permasalahan optimasi. Salah satu metode optimasi
heuristik yang sering digunakan dalam perencanaan jalur adalah Particle Swarm
Optimization (PSO) karena kesederhanaan pada algoritmanya, mudah
diimplementasikan dan memiliki sedikit parameter untuk diatur. Akan tetapi pada
permasalahan perencanaan jalur yang kompleks dengan lingkungan dinamis,
algoritma dasar PSO tidak dapat menjamin menemukan solusi optimal (local
optimum) dikarenakan konvergensi prematur yang menyebabkan terjadi tumbukan
dengan halangan dan jalur yang lebih panjang.
Pada penelitian ini setelah perilaku pencarian PSO dianalisa, PSO adaptif
dikembangkan dengan menggunakan fungsi Gaussian dalam pengaturan nilai
parameter pada PSO untuk mempercepat konvergensi dan reinisialisai partikel
dilakukan untuk mencegah terjadinya konvergensi prematur.
Simulasi dan perbandingan dengan algoritma Adaptif Inertia (AIW) PSO
dan standard PSO menunjukan algoritma yang diusulkan dapat menemukan solusi
optimal lebih cepat dengan konvergensi kurang dari 150 iterasi pada halangan statis
dan 200 iterasi pada halangan bergerak. Selain itu algoritma yang diusulkan
memiliki 3% panjang lintasan yang lebih pendek, 10% lebih smooth dan lebih
terjamin terhindar dari tumbukan.
========================================================================
The
success
key
in mobile robot
navigation
depends on trajectory
generation or
path
planning. Path planning based on heuristic optimization method
is developed to simplify the path planning issues into optimization problems. One
of the heuristic optimization methods used in path planning is the Pa
rticle Swarm
Optimization (PSO) that is often used because of its simplicity, easy to implement
and has few parameters to set. However, in the case of complex path planning with
dynamic environments, the PSO basic algorithm can not guarantee finding the
op
timum solution (local optimum) due to premature convergence that causes
collisions
,
with longer obstacles and paths.
In the proposed method, the Gaussian parameter updating rule use to
speed up the convergence by maintaining exploration and exploitation o
f the
particle. Then, particle re
-
initialization is proposed after analyzing the behavior of
PSO algorithm to prevent premature convergence.
Simulation result shows in benchmark test with Adaptive Inertia (AIW)
PSO and standard PSO that proposed PSO algor
ithm
can find optimal solution
faster than the other algorithm which can convergence in less than 150 iteration in
static obstacle and 200 iteration in dynamic obstacle.
Proposed PSO algorithm with
particle
re
-
initialization
can
guarantee to find optimal solution with resulting path
3% more shortest, 10% more
smooth
and g
uaranteed to collision
free path
Sick and Dead Chicken Detection System Based on YOLO Algorithm
No full textThe poultry industry faces significant challenges in maintaining the health and welfare of chickens, with early detection of sick or dead birds being crucial for effective management and disease control. This paper presents a novel Sick and Dead Chicken Detection System leveraging the YOLO (You Only Look Once) algorithm, a state-of-the-art object detection framework. Our system employs YOLO's real-time image processing capabilities to identify and classify sick and deceased chickens from video feeds or images with high accuracy and speed. Currently chicken farmers are still unable to develop their farms to be able to keep up with increasing needs, this is due to the many chicken farming systems that have not been maximized in the development of their livestock systems, as one example is controlling sick chickens which are still being checked manually. system utilizes YOLO's real-time image processing capabilities to identify and classify sick and deceased chickens by paying attention to symptoms of disease including the movement of chickens by utilizing image processing with the YOLO algorithm, there are several stages in implementing YOLO, namely dataset collection and annotation, preprocessing, dataset division, label file creation, validation and hyperparameter setup, training and model application. We trained our model on a dataset comprising 435 annotated images of chickens exhibiting various health conditions. The proposed system enhances operational efficiency, minimizes human error, and supports timely interventions. Results indicate a significant improvement in detection accuracy and response time compared to traditional methods. The performance of the model applied using the confusion matrix method, so that good results are obtained by applying the YOLOv8 algorithm with an F1 rate of 94%, Precision 100%, Confidence 89.2%, Recall-Confidence of 100%, and Precision-Recall by 97% [email protected]. Each variable obtained an accuracy of 71.25% for dead chickens, 98.25% for sick chickens and healthy chickens
Klasifikasi Golongan Darah Menggunakan Artificial Neural Networks Berdasarkan Histogram Citra
Get PDF Blood type in the medical world can be divided into 4 groups, namely A, B, AB and O. To be able to find out the blood type, a blood type test must be done. So far, human blood type detection is still done manually to observe the agglutination process. This research applies a blood type identification process using image processing. This system works by reading the blood type card image that has been filled with blood samples, then it will be processed through a histogram process to get the minimum and maximum RGB values and pixel locations which are then classified by Artificial Neural Networks (ANN) to determine the blood type from the training results and data matching. From the test results using 12 samples, it was found that the average error in blood type identification was 16.67%
Pemantauan Physical Distance Pada Area Umum Menggunakan YOLO Tiny V3
No full textCoronavirus disease in 2019 (Covid-19) is a phenomenon that become to the world concern because almost all countries experience the outbreak. One of attention to preventing the spread of Covid-19 is the physical distance in public areas. This study proposes human detection in public spaces by using image processing. The application of physical distance is intended to monitor the distance between people in public places. In this study, a human detection system is done by using the YOLO Tiny V3 method and the Euclidean algorithm to be developed to detect distances between humans. There are several stages in the research process: data collection, data preprocessing, data training, and physical distance detection. The system that has been designed can detect by getting an accuracy result of 78.43% for detecting human objects and an accuracy result of 87.82% for detecting distances between humans.Penyakit Coronavirus 2019 (Covid-19) merupakan fenomena yang menjadi perhatian dunia karena hampir semua negara mengalami wabah tersebut. Salah satu bentuk perhatian untuk mencegah penyebaran Covid-19 adalah dengan penereapan dan pengawasan terhadap physical distancing di tempat umum. Penelitian ini mengusulkan pendeteksian manusia di ruang publik dengan menggunakan pengolahan citra. Penerapan physical distance dimaksudkan untuk memantau jarak antar orang di tempat umum. Pada penelitian ini sistem deteksi objek citra manusia dengan menggunakan metode YOLO Tiny V3 dan algoritma Euclidean yang akan dikembangkan untuk mendeteksi jarak antar manusia. Ada beberapa tahapan dalam proses penelitian: pengumpulan data, preprocessing data, pelatihan data, dan deteksi jarak fisik. Sistem yang telah dirancang dapat mendeteksi dengan mendapatkan hasil akurasi sebesar 78,43% untuk mendeteksi objek manusia dan hasil akurasi sebesar 87,82% untuk mendeteksi jarak antar manusia
Hybrid Fuzzy-PID Design Based on Flower Pollination Algorithm for Frequency Control of Micro-Hydro Power Plant
Get PDFMicro-Hydro Power (MHP) Plant System is the renewable energy resource that utilizes water potential energy. In MHP, the energy flows depend on the rotation speed of the generator which cause instability and nonlinearity in the frequency of electrical power. It is also supported by the fluctuation on the electricity load. Therefore, this study used Fuzzy Logic Controller combined with FPA-tuned PID to control the power frequency of the load. This test consisted of 4 stages, namely testing the system without a controller, testing the system using PID, testing the MHP system with a PID controller tuned to the Flower Pollination Algorithm, and testing the system using a Fuzzy PID tuned by the Flower Pollination Algorithm. Based on these tests, the Micro-Hydro Power Plant system response using a Fuzzy PID-tuned FPA controller performed best, especially in accelerating the time to a steady state, reducing overshoot and undershoot with the fastest rise time. As for the output signal from the controller used in the MHP, optimizing the Flower Pollination Algorithm for the Kp, Ki, and Kd parameters is effective and smooth in improving all elements in the Micro-Hydro Power Plant frequency stabilization. Meanwhile, the role of the fuzzy logic controller (FLC) is not very significant, and there is relatively a lot of noise in the output signal of the Fuzzy PID controller itself in terms of stabilizing the load frequency on the Micro-Hydro Power Plant
Kontrol Tegangan Self-Excited Induction Generator dengan Electronic Load Controller Terkontrol PID-GA
Get PDFInduction generator operation requires reactive power with external contactor. One of induction generator types, SEIG reactive power supplied by capacitor bank connected to generator terminal. SEIG is alternative energy conversion in small area or rural, SEIG has the main disadvantage of poor voltage regulation under various load conditions. ELC combine PID control which is optimized using Genetic Algorithm in order to maintain the stability of the voltage when the load varies. The result shows the SEIG system using ELC with PID-GA control worked to stable voltage in accordance with the standard with voltage tolerance of 10% when load change. The addition of GA to determine the value of the PID parameter where response system better with difference overshoot value start is 70.48%, when decrease load in 5 second by 44.3% and in the 10 second when increase load of 2 kW is 5.96% compared system with PID control without GA optimization
STRATEGI BISNIS PADA CAFE JINGGO SURABAYA
Get PDFSmall business which is one of the pillars of national economy, lately got a lot of
attention. This is due to its ability to survive in the face of economic crisis and absorbing
the workforce is very helpful for the sustainability of the wheels of the economy in
Indonesia. Because small businesses are considered to be able to create new jobs for
people in the informal sector, people start thinking to run small businesses that have
innovation in running their small business activities.
The continued development of the business world in all sectors types of certainly
singers will impact the business world the level of competition is getting tight. it forced
the company to review singer more attention to environment can be affecting the
company, that the company knows what the business strategy development and how
should the company implemented hearts. Consumeragainst Café more increased
especially in big cities. by therefore author examines development business strategy on
Café Jinggoin Rungkut -Surabaya.
In research singer writer using method qualitative descriptive with SWOT, to review
reached conclusions SWOT and knowing development of alternative strategies right
onCaféJinggo then the author analysis environmental with using IFAS that covers
regarding strengths and weaknesses companies and EFAS covers about opportunities and
threats for company.
In this study, resulting in the analysis of IFAS strengths and weaknesses with a
score of 1.90 with a score of 1.05 was the analysis results with a score of 1.50 EFAS
opportunities and threats with a score of 1.35. it can be concluded in the diagram position
SOWT Café Jinggo are in first quadrant where the position is to explain that Café
Jinggohas the opportunity and the power that can take advantage of existing
opportunities. The strategy should be applied in these circumstances is to support
aggressive growth policy (growth-oriented strategy).
Keywords: SWOT Analysis, EFAS, IFAS, Business Strateg
Active Fault Tolerance Control For Sensor Fault Problem in Wind Turbine Using SMO with LMI Approach
No full textNavigasi Robot Sepak Bola Beroda Menggunakan Particle Filter Localization
Get PDF"Dimana saya?" adalah pertanyaan utama, yang merupakan representasi lokalisasi atau penentuan psisi, dimana hal tersebut adalah permasalahan yang harus dijawab oleh robot sepak bola beroda. Deadreconing adalah metode paling populer yang digunakan dalam pergerakan robot beroda. Namun, kesalahan posisi yang meningkat adalah topik utama dari metode deadreconing. Selanjutnya dalam makalah ini diusulkan lokalisasi sepak bola beroda menggunakan filter partikel melalui Omnivision. Model sensor dan model gerak dari filter partikel juga dibahas, dimana model sensor diperoleh dari segmentasi dan ekstraksi ciri landmark lapangan sepak bola. Hasil eksperimen menunjukkan bahwa metode yang diusulkan memperkirakan posisi robot secara akurat dengan kesalahan 15%.Â
