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TEKNOKOM : Jurnal Teknologi dan Rekayasa Sistem Komputer

teknokom
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Published by Universitas Wiralodra

ISSN : 26218070 EISSN : 26863219 DOI : https://doi.org/10.31943/teknokom

Core Subject : Science,

Computer Science & IT

Jurnal Teknologi dan Rekayasa Sistem Komputer (TEKNOKOM) with frequency 2 (two) times a year, ie in March and September. The editors receive scientific writings from lecturers, teachers and educational observers about the results of research, scientific studies and analysis and problem solving closely related to the field of ICT and System Computer.

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Articles 7 Documents

Search results for , issue "Vol. 6 No. 1 (2023): TEKNOKOM" : 7 Documents clear

VISITOR GUIDE APPLICATION AT MUSEUM WITH AUGMENTED REALITY ANDROID-BASED Yunita Dwi Cahaya; Ali Ikhwan; Adnan Buyung Nasution
TEKNOKOM Vol. 6 No. 1 (2023): TEKNOKOM
Publisher : Department of Computer Engineering, Universitas Wiralodra

Study this aim as a spatial introduction media on each the floor of the museum and the collections of the Regional Museum of Deli Serdang Pada Visitors Android based . Study this conducted at the Regional Museum of Deli Serdang, which is located at Jalan Negara, Petapahan Sports , Arts and Culture Area , Lubuk Pakam , Deli Serdang, North Sumatra 20517. In research this writer use Research and Development (R&D) methods . Study it also uses Rapid Application Development (RAD) as methodology development application . In conclusion this that the Visitor Guide Application (VGA) with technology Augemented Reality at the Regional Museum of Deli Serdang based on Android has built use Unity 3d apps , Blender and Vuforia with attractive appearance and user friendly. Augmented reality technology can used as tool guide because capable displays 3d object on each collection . The Visitor Guide Application (VGA) is also used as an introduction to spatial planning in each area the floor of the museum and collections in the Deli Serdang Regional Museum visitors Android based . Application this aim for make it easy visitors and the museum in the introduction process collections at the Regional Museum of Deli Serdang.

MONITORING VEGETATION HARVEST OF COFFEE TREES USING KNN-CLUSTERING ALGORITHM Dwi Handoko; Nizamiyati Nizamiyati; Herlini Oktaria; Agus Mulyanto; Muhamad Brilliant
TEKNOKOM Vol. 6 No. 1 (2023): TEKNOKOM
Publisher : Department of Computer Engineering, Universitas Wiralodra

Coffee is one of the plantation commodities spread throughout Indonesia. Coffee is the main commodity for export in Tanggamus Regency. The prediction of crop yields based on aerial photography is the main problem in this study, then there is no dataset of aerial imagery of coffee plantations that are specifically used for the purpose of determining coffee tree vegetation on coffee plantations so that farmers can find out which land is still overgrown by other plants. in addition to coffee trees and the possibility of making predictions for crop yields from aerial imagery of the coffee plantations, this research is also another urgency. This study is intended to build an intelligent model to detect the amount of coffee tree vegetation in a plantation using the KNN-Clustering segmentation algorithm. The image of the coffee tree was taken using a drone with a height of 50 m and an area of 0.25 ha. Preprocessing was carried out. The preprocessed image is called a dataset. After that, the segmentation process is carried out using the Region Growing method to form a black and white image. After Region Growing is done, then the image in Clustering uses the KNN-Clustering method to determine the color pattern of the image in the coffee plantation to distinguish the types of vegetation in the coffee plantation. From the results of KNN-Clustering, the area of coffee tree vegetation is obtained from a total of 0.25 ha of coffee plantation images.

A NODEMCU INTERNET OF THINGS-BASED FIRE AUTOMATION DESIGN WITH BLYNK APPS NOTIFICATIONS Rafli Permana; Andrie Yuswanto; Budi Wibowo
TEKNOKOM Vol. 6 No. 1 (2023): TEKNOKOM
Publisher : Department of Computer Engineering, Universitas Wiralodra

The impact of fires causes quite large losses, often even causing fatalities. The method used in the system is monitoring the fire sensor which is used to detect a fire, the buzzer as a notification output in the form of sound, and the water pump as a fire extinguisher which will function after the fire sensor is on. detecting the presence of fire. to detect fire in realtime and 9 in the event of a fire with a research and development. Monitoring approach on fire sensors used to detect the presence of fire, buzzers as output notifications in the form of sound, and water pumps as a tool to extinguish fires which will function after the fire sensor detect the presence of fire.

SKIN CANCER IMAGE DETECTION SYSTEM USING THE CONVOLUTIONAL NEURAL NETWORK MODEL Muhamad Suhaedi; Hamid Abdillah; Annisa Rizki Liliandari
TEKNOKOM Vol. 6 No. 1 (2023): TEKNOKOM
Publisher : Department of Computer Engineering, Universitas Wiralodra

The development of science and technology (IPTEK) in the current era is growing very rapidly in various fields such as industry, education, especially the health sector. Many technologies can be used, one of which is artificial intelligence technology. This study aims to detect skin cancer images using CNN so that they can be efficient and precise. This research method uses the convolutional neural network (CNN) method, namely image processing, the development of a multilayer perceptron (MLP), in which the neurons of the data are propagated in two dimensions. Because this method has very high accuracy compared to the fuzzy k-nearest neighbors. The results of this study are that there are 7 classes of skin cancer images including actinic keratosis, basal cell carcinoma, dermatofibroma, benign keratosis, melanocytic nevi, vascular lesions and melanoma. From the results of testing the 7 classes using the convolutional neural network (CNN) method with a very high accuracy rate of 99%, 96%, 98%, 99%, 100%, 99% and 96%, respectively. With the conclusion that using the convolutional neural network (CNN) method produces an average accuracy of 98% compared to the Mobilnetv2, Resnet50 and VGG16 models, which means that the CNN model is proven to be more accurate. So it is hoped that this detection system can be applied as a skin cancer detection system for the world of health.

IMPLEMENTATION OF FUZZY LOGIC ON SPEED PREDICTION ON INCLUDING ROADS Alghi Sawaludin; Rahmat Hidayat; Reni Rahmadewi
TEKNOKOM Vol. 6 No. 1 (2023): TEKNOKOM
Publisher : Department of Computer Engineering, Universitas Wiralodra

Going through a road with a high slope has a risk of an accident due to a miscalculation by the driver. Therefore, detecting the speed limit to pass it is the solution. The aim of this research is to create a precise and minimal error system that predicts the uphill speed that must be used by the driver. By using fuzzy logic, of course you can predict what speed should be used. For tilt detection, a gyroscope is used and speed detection is being used using a GPS sensor. For the fuzzy inference system itself, it uses the Takagi Sugeno-Kang, method with a linear and constant output. In addition, the calculation of the crisp value is carried out using the manual calculation method and using a simulation application, namely MATLAB. The results of subsequent calculations are compared to calculate the precision value of the system in detecting uphill speed. The calculation uses MAPE. So the results of this study are speed detection systems that must be used on inclines that predict precisely. The implication of this research is that driving safety on high-slope roads can be improved and accidents that occur can be minimized. In addition, the driver can estimate the speed that must be used.

VEHICLE STARTER SYSTEM FOR SAFETY BASED MICROCONTROLLER USING INTERNET OF THINGS Rachma Khairunisa; Rahmat Hidayat
TEKNOKOM Vol. 6 No. 1 (2023): TEKNOKOM
Publisher : Department of Computer Engineering, Universitas Wiralodra

Technology is currently growing very fast which affects and has a significant purpose in human life. In the current era, the technology of the security system is something that is very necessary. The high crime rate has now reached an alarming stage. Motorcycles currently only use conventional ignition keys to turn them on to improve the vehicle's security system, so a vehicle security system with a microcontroller connected to an Internet of Things-based fingerprint sensor is needed to improve the vehicle's security system. Research shows that a motorcycle security system with a microcontroller is connected to a fingerprint sensor based on the Internet of Things, namely turning on and turning off the vehicle with fingerprints owned or via the internet of things using the telegram application for remote and realtime systems. The way the results of this study work is when the first finger taps on the fingerprint sensor on the registered finger, the motor will turn on, then the second finger taps on the fingerprint sensor, the motor will die, for remote systems, namely using telegram bots, the prefix is to enter chat instructions on the telegram bot if the telegram bot replies to the instruction then the motor will follow according to the instruction on or off and if the instruction is wrong then the telegram bot will tell that the instruction is wrong. The results of this study show that when adding fingerprints it has a delay of 1.74s, removing fingerprints is 0.24s and the IoT system itself is 90% successful.

IMPLEMENTATION OF THE EDAS METHOD IN SELECTING INVESTMENT IN THE AGRICULTURAL SECTOR Ilman Kadori; Susi Widyastuti; Miswadi Miswadi; Nofie Anggraini
TEKNOKOM Vol. 6 No. 1 (2023): TEKNOKOM
Publisher : Department of Computer Engineering, Universitas Wiralodra

Capital is one of the most important things in any business activity that will be carried out. Capital includes capital before planting, planting period until harvest time arrives and post-harvest. Because of the large number of farmers in Kuningan district, the Kuningan district Food Security and Agriculture Agency needs investors to help the farmers. In this study designing and building applications for selecting investments in the agricultural sector using a decision support system with the EDAS method. EDAS is a multi-criteria decision-making method based on the AS score. The data used is data from direct interviews with farmers to determine criteria, sub criteria and alternatives. The criteria include land area, capital, harvest period, yields, and selling price. The alternatives include the names of the farmers, namely Tati, Niryo, Odah, Umin, and Tarwa, as well as types of farming, such as chili, shallots, rice, corn, and peanuts. From the results of the overall calculation of this study, it shows that the EDAS method produces the best choice for Tati farming with the type of chili farming. This research produces a web-based application that can be used by farmers and investors and furthermore, it can be developed into an Android or mobile-based application. The goal is to make it easier for investors to find and choose the best farms to invest in.

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Taufik Hidayat

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Home Page

OAI Link

Editorial Team

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Contact Name Taufik Hidayat

Contact Email thidayat.ft@unwir.ac.id

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Journal Mail Official teknik.komputer@unwir.ac.id

Editorial Address Jl. Ir. H. Juanda KM.03, Singaraja, Indramayu - Jawa Barat 45312

Location Kab. indramayu, Jawa barat INDONESIA

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Contact Name
Taufik Hidayat

Contact Email
thidayat.ft@unwir.ac.id

Phone
-

Journal Mail Official
teknik.komputer@unwir.ac.id

Editorial Address
Jl. Ir. H. Juanda KM.03, Singaraja, Indramayu - Jawa Barat 45312

Location
Kab. indramayu,

Jawa barat

INDONESIA