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Suhendri Suhendri
STMIK "AMIKBANDUNG"
Computer Science & IT

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Journal : JOINT (Journal of Information Technology

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Metode Grayscale Co-occurrence Matrix (GLCM) Untuk Klasifikasi Jenis Daun Jambu Air Menggunakan Algoritma Neural Network Suhendri Suhendri; Putri Rahayu
Journal of Information Technology Vol 1 No 1 (2019): JoinT (Journal of Information Technology)
Publisher : LPPM STMIK AMIK BANDUNG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47292/joint.v1i1.4

Abstract

The color and shape of leaves each different plant water rose so that it can be found a certain texture to classify. This study uses an image texture recognition leaves to be classified. Leaves used are three types of guava leaves, Bunton 3 Green Guava, Guava and Guava image Bol. Feature extraction process used a method is Gray Level Co-Occurrence Matrix (GLCM) with Matlab tool. GLCM is used to retrieve the value of the image attribute or value matrix. This study uses a Neural Network algorithm with a tool RapidMiner. One alternative solution to the above problems is by way of classifying types of guava leaf water by looking at the characteristics of the water guava leaves. Leaf is one of the characteristics of the plant that is easily recognizable. The classification process is to produce a good accuracy value against bunton guava leaves 3 green, pink bol, and guava image. The results showed that the level of accuracy in the guava leaf bol is 81.25%, bunton leaves 3 Green 75%, and 80% leaf image and the total value of the overall accuracy of 78.89%. Thus the above results show that the value of the accuracy of the resulting research shows three types of guava leaf water has been classified and deserves to be investigated.
Peningkatan Sistem Keamanan Parkir dengan Teknologi Artificial Intelligence Imaging Ari Purno Wahyu; Suhendri Suhendri; Heri Heryono
Journal of Information Technology Vol 1 No 2 (2019): JoinT: Journal of Information Technology
Publisher : LPPM STMIK AMIK BANDUNG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47292/joint.v1i2.9

Abstract

Parking space is a public facility available at an agency or office that serves to temporally store vehicles, the vehicle that enters the parking area is become tens or even thousands, because tahat reason parking system and management area is needed. Such arrangements able parking procedures and even other support systems such as adequate parking facilities and infrastructure, other functions is making and developing parking systems in general for provide security and comfort, bacause the condition vehicle will be well organized in terms of vehicle placement and security and safety can be used for 24 hours. Constraints this time increasing number of vehicles requires a wider parking area or space, the slow pace of vehicle data collection because the technology used is still carried out vehicle license plate validation manually, another problem is the placement of large areas, this limitation is based on the number of parking attendants in the field is very limited, so extra time are needed to arrange and check the vehicles that have entered the parking area. This problem can be handle using image processing and OCR algorithm techniques, this technique has been implemented in several developed countries that are used to manage they parking system, image processing is used to record and monitor the number of vehicles in the area by reading the number plate, scanning techniques using OCR (Optical Character recognition techniques) , data from a vehicle plate image is converted into text or numbers and can be stored inside database, data from the vehicle plate that has been stored is then matched with a vehicle photo, with help the system can be integrated with the camera so that the supervision of the parking area can be carried out directly for a long time, the system is able to display data visually.
Sistem Informasi Pemeriksaan Jalur Kereta Api Menggunakan Drone dan Teknik Image Processing Siti Mardiana; Dani Hamdani; M Benny Chaniago; Ari Purno Wahyu; Heri Heryono; Suhendri Suhendri
Journal of Information Technology Vol 2 No 1 (2020): JOINT: Journal of Information Technology
Publisher : LPPM STMIK AMIK BANDUNG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47292/joint.v2i1.002

Abstract

Train is the main mode of transportation that we often use, the train itself can be used as a tool for shipping goods and mobilizing passengers, this transportation is very unique and has its own path in the form of steel strings across from hundreds of kilometers, railroad bearing structures currently exist which uses concrete and wood, the railroad is very vital and is an important supporting facility. The process of railroad monitoring is complex and complicated, takes a long time, the previous method is simple and conventional by tracing the railroad tracks manually or using a geometric gauge mounted direl or also known as railpod, railpod will follow the rails and will provide report if there is a train track that is damaged, broken or shifted, this research will create an image-based monitoring system using drones as a track monitor, another way is to take pictures using satellite data that will provide clear information about road conditions before being passed by the train, the railroad data processing system by using image processing can display visual responses up to cm in size, the response appears if there is a shift in the path then the system directly provides data in the form of location and shifting paths on the main computer, this system is more c eTat in checking and analyzing train track data with high accuracy and precision up to 90%, in addition to imagery from satellite images can use drones, drones themselves are very easy in maintenance and use and are able to cut production costs and even workplace accidents in the field workers themselves can be avoided because the drone is able to reach the track and railroad that is difficult for example through the tunnel or the railroad track along the hills and densely populated.
Co-Authors Ari Purno Wahyu Wibowo Dani Hamdani Heri Heryono M Benny Chaniago Putri Rahayu Siti Mardiana