Robot Classifying of Gas using Support Vector Machine Method

Fires often happen in the environment of industrial chemical plant caused by harmful gases. To minimize the incident that can be triggered by the gas it takes a tool capable of classifying gases are in the environment industry. The purpose of this research is to know the success in classifying gas on a fire that was triggered by the dangerous gases. We offer solutions in design and build a mobile robot that can classify objects contain hazardous gases by using the method of pattern recognition, the age of the SVM is still relatively young. Nevertheless, the advantages of SVM compared to another method lies in its ability to find the best hyperplane that separates the two class. Based on the results of testing data can classify SVM managed in accordance with the class. The degree of accuracy achieved SVM in classifying reached 86.66 %

Analysis Kinerja Pembangkit Listrik Tenaga Bayu (PLTB) Sebagai Resource Reserve Pada Pembibitan Ayam Pedaging Berbasis Internet Of Things (IoT)

Abstrak Pembangkit Listrik Tenaga Bayu (PLTB) merupakan pembangkit listrik yang rama lingkungan dan menggunakan sumber energi terbarukan dengan memanfaatkan sumber angin sebagai penggerak. Pembangkit Listrik Tenaga Bayu (PLTB) ini menggunakan system Internet Of Things (I0T) untuk memonitoring atau pemantauan kinerja dari PLTB dengan menggunakan mikrokontroler nodemcu ESP32 untuk menyimpan data dari Wind Speed Sensor Anemometer dan sensor Pzem-017. Tujuannya untuk mempermudah pemantauan dan mengetahui kinerja dari PLTB dari jarak jauh secara realtime. Hasil pengujian yang telah diambil dari pembacaan sensor Pzem-017 pada kecepatan angin maksimal yaitu 15 m/s yang diukur menggunakan Wind Speed Sensor Anemometer dan tegangan yang dihasilkan 8,92V. Dan untuk hasil perbandingan pembacaan sensor Pzem-017 dan multimeter sudah sesuai dengan alat PLTB berbasis Internet Of Things (I0T). Abstract  Wind Power Plants (WPP/PLTB) are environmentally friendly electricity generators that utilize renewable energy sources by harnessing wind as the driving force. These Wind Power Plants employ Internet of Things (IoT) systems for monitoring and assessing the performance of the plants. They utilize the NodeMCU ESP32 microcontroller to store data from the Wind Speed Sensor Anemometer and the Pzem-017 sensor. The objective is to facilitate remote real-time monitoring and gain insights into the performance of the Wind Power Plants.The test results obtained from the Pzem-017 sensor readings indicate a maximum wind speed of 15 m/s, as measured by the Wind Speed Sensor Anemometer, and a corresponding voltage output of 8.92V. The readings from the Pzem-017 sensor, when compared to those obtained from a multimeter, align with the IoT-based Wind Power Plants system

Pemanfaatan Sensor Jarak dan Sensor Warna pada Proses Penanaman Benih Menggunakan Smart Mini Robot Agriculture

Indonesia adalah negara agraris yang memiliki potensi alam di bidang pertanian. Pada saat ini, sebagian besar petani masih menanam benih dengan menggunakan metode konvesional yang membutuhkan banyak tenaga dan operator (manusia). Penelitian ini menawarkan robot penanaman benih secara otomatis.  Robot ini dibuat untuk efisiensi waktu dan tenaga para petani. Robot ini dilengkapi dengan microkontroller Arduino Mega sebagai sebagai komponen utama, serta beberapa komponen pendukung lainnya, seperti: sensor ultrasonic, sensor warna photodioda, motor servo dan driver motor L298N. Dari hasil pengujian dapat dilihat bahwa robot dapat bekerja dengan maksimal.  Motor servo mg996r pada posisi kiri, pada keadaan normal memiliki sudut servo 00 dan ketika bekerja sudutnya sebesar 1150.  Sedangkan, untuk posisi sebelah kanan, pada saat normal, sudut servo 600 dan bekerja 500.  Motor servo sg90 melakukan proses penutupan lubang tanam, dengan sudut servo pada saat menutup 00 dan membuka 600 ketika berada pada posisi sebelah kiri dan pada saat menutup 900 dan membuka 600 untuk posisi sebelah kanan Kata kunci—Penanam benih, sensor jarak, sensor warna, motor serv

Robot Classifying of Gas using Support Vector Machine Method

Fires often happen in the environment of industrial chemical plant caused by harmful gases. To minimize the incident that can be triggered by the gas it takes a tool capable of classifying gases are in the environment industry. The purpose of this research is to know the success in classifying gas on a fire that was triggered by the dangerous gases. We offer solutions in design and build a mobile robot that can classify objects contain hazardous gases by using the method of pattern recognition, the age of the SVM is still relatively young. Nevertheless, the advantages of SVM compared to another method lies in its ability to find the best hyperplane that separates the two class. Based on the results of testing data can classify SVM managed in accordance with the class. The degree of accuracy achieved SVM in classifying reached 86.66 %.</p

Swarm Intelligent in Bio-Inspired Perspective: A Summary

This paper summarizes the research performed in the field of swarm intelligent in recent years. The classification of swarm intelligence based on behavior is introduced. The principles of each behaviors, i.e. foraging, aggregating, gathering, preying, echolocation, growth, mating, clustering, climbing, brooding, herding, and jumping are described. 3 algorithms commonly used in swarm intelligent are discussed. At the end of summary, the applications of the SI algorithms are presented

PELATIHAN PENGGUNAAN INTERNET SECARA TEPAT DAN SEHAT BAGI GURU DAN SISWA DI MTs AR-RAHMAN PALEMBANG GUNA MENINGKATKAN KREATIVITAS SERTA KESADARAN GURU DAN SISWA MENGENAI SISI NEGATIF INTERNET

Internet(interconnection networking) adalah seluruh jaringan komputer yang saling terhubung menggunakan standar sistem global Transmission Control Protocol/Internet Protocol Suite (TCP/IP) sebagai protokol pertukaran paket (packet switching communication protocol) untuk melayani miliaran pengguna di seluruh dunia.Sejalan dengan perkembangan budaya manusia, globalisasi informasi berkembang dengan sangat pesat.Dampak dari globalisasi informasi sangat signifikan, baik yang positif maupun yang negatif. Jika kita tidak mengikuti perkembangan ilmu pengetahuan dan teknologi dunia, maka kita akan menjadi bangsa yang terbelakang dan menjadi bangsa yang direndahkan. Teknologi yang terpesat perkembangannya saat ini adalah teknologi informasi dan telekomunikasi, yang menghadirkan beragam pilihan bentuk teknologi dan kecanggihannya, contohnya adalah internet.Internet juga semakin mempermudah terjadinya pelanggaran terhadap Hak Atas Kekayaan Intelektual (HAKI) karena makin mudahnya mengakses data menyebabkan orang yang bersifat plagiatis akan melakukan kecurangan. Tindakan ini sangat meresahkan penulis dan pengarang Indonesia

PENGENALAN KENDALI ROBOT SAMPAH BERBASIS IPAD DI SMPIT HARAPAN MULIA PALEMBANG

SMPIT Harapan Mulia is one of the schools that uses iPad for its teaching and learning activities.  The use of this small, simple and lightweight iPad is certainly one of the solutions to reduce the burden of the books that the students should carry.  All the learning materials can be found easily in the iPad, therefore the students can learn many things anywhere and anytime. In addition, the use of this iPad also will certainly make the students to more focus on the lesson.  The students have an opportunity to be more flexible in terms of self-development.  Besides the benefits provided by the iPad, there are several obstacles that are often faced, including, the use of iPad is monotonous andexcessive use of iPad can reduce student performance compared to those who do not use tablets (according to research from the Organization for Economic Cooperation and Development (OECD) and University of Michigan). Based on observations and interviews with the principal at SMPIT Harapan Mulia, students who use the iPad are more enthusiastic in joining the teaching and learning process. This can be proven by an increase in the average value obtained by the students of SMPIT Mulia Harapan. However, unfortunately the school also often found the students looked bored with their tablets. This is because their iPad is connected directly to MDM (Mobile Device Management), where the MDM manages the content and activities on each student's iPad.  This MDM limits the student's movement, so that they will not get out of line. However, this MDM also makes students feel uncomfortable and not to be free to express themselves.  Therefore, we need a solution to overcome these problems. This dedication is carried out with the aim to maintain the stability of the students' enthusiasm in using the iPad. In practice, this service provides opportunities for students to develop their skills in using the iPad. Students are equipped with the theory of the development of the use of iPad (in this activity, the iPad is used to control the trash robot). Besides that, the service activity also demonstrated and gave a short workshop on the control of garbage robots using the iPad. The results of this dedication were a simple coding and a monitoring module using a Blynk based iPad

Optimal Kernel Classifier in Mobile Robots for Determining Gases Type

The use of TGS sensor and Arduino could create a robot to be capable of detecting and classifying some gases. In this research, 3 kinds of SVM Kernel Classifiers are investigated. Robots equipped with 3 TGS sensors are used to classify methanol and acetone. Xbee modul is used as a communication medium between robots and server. The robots are run in the experimental environment. When they detect the gas, they will get closer to the source and classify the gas type. The classified gas data is then sent to the server. From this research, it can concluded that polynomial and RBF have better performance in classifying methanol and acetone

Swarm Intelligent in Bio-Inspired Perspective: A Summary

This paper summarizes the research performed in the field of swarm intelligent in recent years. The classification of swarm intelligence based on behavior is introduced.&nbsp; The principles of each behaviors, i.e. foraging, aggregating, gathering, preying, echolocation, growth, mating, clustering, climbing, brooding, herding, and jumping are described. 3 algorithms commonly used in swarm intelligent are discussed.&nbsp; At the end of summary, the applications of the SI algorithms are presented

Optimal Kernel Classifier in Mobile Robots for Determining Gases Type

The use of TGS sensor and Arduino could create a robot to be capable of detecting and classifying some gases. In this research, 3 kinds of SVM Kernel Classifiers are investigated. Robots equipped with 3 TGS sensors are used to classify methanol and acetone. Xbee modul is used as a communication medium between robots and server. The robots are run in the experimental environment. When they detect the gas, they will get closer to the source and classify the gas type. The classified gas data is then sent to the server. From this research, it can concluded that polynomial and RBF have better performance in classifying methanol and acetone