Claim Missing Document
Check
Articles

Found 4 Documents
Search
Journal : Journal of Computer Networks, Architecture and High Performance Computing

Implementation of Bot Telegram as Broadcasting Media Classification Results of Convolutional Neural Network (CNN) Images of Rice Plant Leaves Adi Fajaryanto; Fauzan Masykur; Mohammad Rizqi Rosyadi
Journal of Computer Networks, Architecture and High Performance Computing Vol. 5 No. 1 (2023): Article Research Volume 5 Issue 1, January 2023
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v5i1.1976

Abstract

Rice plants play an important role in the life of the Indonesian people because rice is the raw material for rice as a staple food. The rice production process does not rule out the possibility of interference by pests and diseases resulting in losses that cause crop failure. Meanwhile, pests on rice plants can be caused by various types, namely types of fungi (leafblast, hispa, brownspot) and types of nuisance animals. In this research, it will be carried out how to classify the image of rice plant leaves using the deep learning Convolutional Neural Network (CNN) algorithm, then the results of the classification are sent to users by utilizing the telegram chat application. The rice plant leaf image dataset is grouped into 4 groups (leafblast, brownspot, hispa and healthy). From several experiments it can be seen the results of system performance, namely the classification speed takes 30-60 seconds.
Implementation of Fuzzy Logic for Chili Irrigation Integrated with Internet of Things Angga Prasetyo; Arief Rahman Yusuf; Yovi Litanianda; Sugianti; Fauzan Masykur
Journal of Computer Networks, Architecture and High Performance Computing Vol. 5 No. 2 (2023): Article Research Volume 5 Issue 2, July 2023
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v5i2.2518

Abstract

Chili, mustard greens, and tomatoes have always been farmers' favored crops, despite their high water and labor demands. Adapt to these conditions by utilizing smart agriculture systems (SAS) agricultural techniques that involve technology such as automatic irrigation that regulates watering based solely on routine, regardless of land conditions. This type of control during the transitional season can lead to root rot and fungisarium disease on chile plants. In the form of an embedded system with internet of things (IoT) monitoring, a system incorporating artificial intelligence such as fuzzy logic is proposed as a solution. Fuzzy logic will regulate irrigation based on the land's humidity and temperature using computational mathematics. Beginning with the fuzzyification stage to map the sensor's temperature and humidity input values, fuzzy logic is applied. The creation of an inference engine in the NodeMcu 8266 microcontroller to interpret fuzzy rule statements in the form of aggregation of minimum conditions with the AND operator, followed by the combination of a single set value of 0 and 1 in the fuzzy system to produce an appropriate actuator response After the entire system has been prototyped, testing is conducted to determine the responsiveness of the fuzzy program code to changes in the simulated agricultural cultivation land ecosystem. This study found that the fuzzy logic program code embedded in the nodeMCU8266 microcontroller effectively controls the spraying duration of the pump in response to various simulated environmental conditions within 3.6 seconds.
Implementation of Bot Telegram as Broadcasting Media Classification Results of Convolutional Neural Network (CNN) Images of Rice Plant Leaves Cobantoro, Adi Fajaryanto; Fauzan Masykur; Rizqi Rosyadi, Mohammad
Journal of Computer Networks, Architecture and High Performance Computing Vol. 5 No. 1 (2023): Article Research Volume 5 Issue 1, January 2023
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v5i1.1976

Abstract

Rice plants play an important role in the life of the Indonesian people because rice is the raw material for rice as a staple food. The rice production process does not rule out the possibility of interference by pests and diseases resulting in losses that cause crop failure. Meanwhile, pests on rice plants can be caused by various types, namely types of fungi (leafblast, hispa, brownspot) and types of nuisance animals. In this research, it will be carried out how to classify the image of rice plant leaves using the deep learning Convolutional Neural Network (CNN) algorithm, then the results of the classification are sent to users by utilizing the telegram chat application. The rice plant leaf image dataset is grouped into 4 groups (leafblast, brownspot, hispa and healthy). From several experiments it can be seen the results of system performance, namely the classification speed takes 30-60 seconds.
Implementation of Fuzzy Logic for Chili Irrigation Integrated with Internet of Things Prasetyo, Angga; Yusuf, Arief Rahman; Litanianda, Yovi; Sugianti; Masykur, Fauzan
Journal of Computer Networks, Architecture and High Performance Computing Vol. 5 No. 2 (2023): Article Research Volume 5 Issue 2, July 2023
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v5i2.2518

Abstract

Chili, mustard greens, and tomatoes have always been farmers' favored crops, despite their high water and labor demands. Adapt to these conditions by utilizing smart agriculture systems (SAS) agricultural techniques that involve technology such as automatic irrigation that regulates watering based solely on routine, regardless of land conditions. This type of control during the transitional season can lead to root rot and fungisarium disease on chile plants. In the form of an embedded system with internet of things (IoT) monitoring, a system incorporating artificial intelligence such as fuzzy logic is proposed as a solution. Fuzzy logic will regulate irrigation based on the land's humidity and temperature using computational mathematics. Beginning with the fuzzyification stage to map the sensor's temperature and humidity input values, fuzzy logic is applied. The creation of an inference engine in the NodeMcu 8266 microcontroller to interpret fuzzy rule statements in the form of aggregation of minimum conditions with the AND operator, followed by the combination of a single set value of 0 and 1 in the fuzzy system to produce an appropriate actuator response After the entire system has been prototyped, testing is conducted to determine the responsiveness of the fuzzy program code to changes in the simulated agricultural cultivation land ecosystem. This study found that the fuzzy logic program code embedded in the nodeMCU8266 microcontroller effectively controls the spraying duration of the pump in response to various simulated environmental conditions within 3.6 seconds.