The development of the internet of things has penetrated in several lines, including in agriculture. To respond to the development of this IoT requires rapid technological adaptation as well. To build a system quickly, one can utilize the Rapid Application Development (RAD) method. RAD is a model that allows non-experts to benefit from high-performance computing, while allowing expert programmers to take full advantage of the underlying hardware. This enables rapid prototyping, retargeting, and reuse of existing software, while allowing hardware-specific optimization if needed. The RAD system emphasizes the fast development cycle that is designed and high-quality results from other methods such as waterfall, agile, scrum and others. The system was built using the minimum NodeMCU system with the help of a soil moisture sensor. The use of the RAD method in building an IoT-based agricultural irrigation system gives good results in testing all functions and equipment controls. The average delay level on testing IoT devices is around 4.6 seconds so that the RAD method can be used as a reference in the construction of an IoT-based system.
Water is an important aspect in aspects of life. In agriculture it is a major component of photosynthesis and transportation of nutrients from the soil to plants. Usually farmers provide water twice a day on a regular basis, but at certain times require excess water to maintain soil moisture. In chili plants, humidity needs around 60% to 80% so that plants can grow to the maximum. Internet of things (IoT) technology can help farmers to support the water needs that are in the soil. With IoT technology it can also help in the irrigation process by releasing or managing pumps automatically. The IoT device used to make this system is equipped with NodeMCU, a humidity sensor and a mobile based application as an IoT device control software. The Internet of Things (IoT) system can help the irrigation system in chilli plants to ensure the safety of the soil is raised 60% to 80%.
Broilers are an excellent source of protein and are needed in the productive age population. From the central statistics data in 2019, the number of broiler populations in Indonesia reached 3.15 billion heads. To maximize production and reduce production efficiency, artificial intelligent application innovations are carried out for temperature, humidity, and gas control in broiler chicken coops. Internet of Things helps farmers make efficient use of human resources to adjust the temperature and humidity of the cage. The microcontroller’s primary device uses a wifi-embedded ESP32 to be able to transmit data to the server. To read the environmental conditions of the cell, use DHT11 for temperature and MQ2 for gas. The results of the system’s application were tested using two models, namely, testing the sensor reading value compared to the weight on the Thermo hygrometer and observation of the reaction of chickens in the cage. The test results were conducted by comparing the sensor’s value with Thermo hygrometer difference can be tolerated and normal chicken reaction because the temperature in the enclosure is well maintained.
Abstract The increasing human population in the world with the need for mobilization of motorized vehicles both 2 wheels and 4 wheels is no longer a secondary need but has become a primary need. With the increasing population of vehicles on the road becoming its own problem that is often the occurrence of both single and successive accidents that resulted in many victims both minor injuries, severe to death. Kediri is one of the cities with high accident rates. Although in 2018 this number has decreased but in 2017 there were 1,258. This resulted in the need for an information system to dig deeper about it. The k-mean algorithm is an algorithm used to group the same data and put it into a Cluster group to dig up information. The information system was developed using PHP and MYSql programming languages. The results of clustering are of 3 types namely accident rarely, accident-prone and very accident-prone. The most common incidents in the Pare Subdistrict with the cluster being very accident-prone. Throughout 2017 pare sub-districts there were 133 accident cases. Keywords: K-Means, Data mining.,accident, PHP, clustering. __________________________ Abstrak Semakin meningkatnya populasi manusia di dunia dengan kebutuhan mobilisasi kendaraan bermontor baik roda 2 maupun roda 4 bukan lagi menjadi kebutuhan sekunder tetapi sudah menjadi kebutuhan primer. Dengan semakin meningkatnya populasi kendaraan di jalan raya menjadi maslah sendiri yakni sering terjadinya kecelakaan baik tunggal maupun beruntun yang mengakibatkan banyak korban baik luka ringan, berat sampai meninggal dunia. Kediri adalah salah satu kota yang masih tinggi angka kecelakaan. Meski di tahun 2018 ini mengalami angka penurunan akan tetapi di tahun 2017 tercatat 1.258. Hal ini mengakibatkan perlu adanya suatu system informasi untuk menggali lebih dalam mengenai hal tersebut. Algoritma k-mean adalah algoritma yang digunakan untuk mengelompokkan data yang sama dan dimaksukkan ke kelompok Cluster untuk menggali informasi. Pada system infprmasi dikembangkan menggunakan Bahasa pemograman PHP dan MYSql. Hasil dari clustering terdapat 3 jenis yaitu jarang terjadi kecelakaan, rawan kecekalaan dan sangat rawan kecelakaan. Kecataman dengan kejadian terbanyak terjadi di kecamatan Pare dengan cluster sangat rawan kecelakaan. Sepanjang tahun 2017 kecamatan pare terjadi kasus kecelakaan sebanyak 133 kasus. Kata Kunci: K-Means, Kecelakaan, Data mining, PHP, Clustering. __________________________
– Broiler chickens or broiler chickens are one of the popular sources of nutrition in Indonesia. The production of broilers reaches 3.15 billion heads, with the most production center on Java’s island. The Covid-19 disaster that hit Indonesia caused broilers’ production to decrease due to the government’s social restrictions. To maximize production and reduce production efficiency, artificial Intelligent application innovations are carried out for temperature, humidity, and gas control in broiler chicken coops. Artificial Intelligent methods of developing machines can think like humans to help control and make decisions. This artificial Intelligent model uses a fuzzy logic Pulse Width Modulator (PWM)model. The device used for control utilizes Internet of Things technology with a microcontroller as its primary device and sensor as an environmental data reader. The microcontroller used is ESP32 which has been embedded with Wifi to facilitate the transmission of data to the server. To read the sensors’ environmental conditions used by temperature sensors, humidity uses DHT11 and ammonia gas using MQ2. Environment data is sent to the server, which is useful for the user monitoring the cage environment’s condition remotely and, if needed, can be controlled by using the application interface. In this research, the process of system development using waterfall method, namely needs analysis, design, implementation and testing. The system’s application results were tested using two models, namely, trying the sensor reading value compared to the weight on the hygrometer and observation of the reaction of chickens in the cage. The test results obtained the difference in value between the sensor and hygrometer can be tolerated and the chicken reaction following the system’s cooling status.
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