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Journal of Artificial Intelligence and Engineering Applications (JAIEA)
Published by Yayasan Kita Menulis
ISSN : -     EISSN : 28084519     DOI : https://doi.org/10.53842/jaiea.v1i1
Core Subject : Science, Engineering,
Automotive Engineering Computer Science & IT Control & Systems Engineering
The Journal of Artificial Intelligence and Engineering Applications (JAIEA) is a peer-reviewed journal. The JAIEA welcomes papers on broad aspects of Artificial Intelligence and Engineering which is an always hot topic to study, but not limited to, cognition and AI applications, engineering applications, mechatronic engineering, medical engineering, chemical engineering, civil engineering, industrial engineering, energy engineering, manufacturing engineering, mechanical engineering, applied sciences, AI and Human Sciences, AI and education, AI and robotics, automated reasoning and inference, case-based reasoning, computer vision, constraint processing, heuristic search, machine learning, multi-agent systems, and natural language processing. Publications in this journal produce reports that can solve problems based on intelligence, which can be proven to be more effective.
Arjuna Subject : Ilmu Komputer (semua kategori) - Kecerdasan Buatan
Articles 430 Documents
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Selection of the Best Village Crop Potential Using the Multi-Attribute Border Approximation Area Comparison (MABAC) Method Khalid Muhammad Abdul Khalid
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 3 No. 1 (2023): October 2023
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v3i1.341

Abstract

The difference in the location of each geographical condition of each village resulted in many different types of superior agricultural products in each village, this resulted in not all villages in Langkat Regency being able to utilize the crops in their village. This has caused the Community and Village Empowerment Service of Langkat Regency to work very hard in providing support for the progress of each village in developing existing agricultural products. The support provided by the government through the Langkat Regency DPMD is subsidized fertilizer, subsidized seeds and so on. Based on the results of research that has been conducted at the DPMD of Langkat Regency, the selection process to determine the village with the best agricultural products which is done manually can slow down the results of the decisions given and the results obtained are ineffective and inefficient. In overcoming this, it is necessary to build a system to streamline the process of selecting villages with the best agricultural products that have been properly computerized by utilizing the process of the Decision Support System (DSS). In this study a Decision Support System (DSS) will be built using the Multi-Attribute Border Approximation Area Comparison (MABAC) method which in this method is known as a method that can provide solutions in making a decision compared to other methods. The system was successfully built using the PHP programming language with a MySQL database. In the system built, the appropriate criteria to be used in supporting the final results of decisions that have been successfully analyzed and applied to the system are land area, income per harvest, number of workers and number of harvests each year. Based on the results of the research that has been done, the MABAC method is able to determine the ranking of the processed data based on the results of the total value of the criterion function.
Binjai Train Ticket Counter Queue Simulation Using Weibull Service Distribution Refirda Agtalia; Akim M H Pardede; Magdalena Simanjuntak
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 3 No. 1 (2023): October 2023
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v3i1.343

Abstract

This research aims to improve the efficiency of train ticket counter services at Binjai Station through the use of Weibull service distribution-based queuing simulations. Long queues and excessive waiting times are often problems at many train stations, and this research aims to address these problems.This study collects queuing data from train ticket booths at Binjai Station over a certain period and analyzes them to identify existing queuing patterns. The Weibull service distribution was chosen as the appropriate model to describe the ticket counter service time, because this distribution has the flexibility to handle variations in service time well.   Queue simulation is carried out using simulation software that models the queuing process at the train ticket counter. Weibull distribution parameters are integrated into the simulation to predict service time at the ticket counter. In this simulation, various scenarios and strategies for improving service efficiency are evaluated to identify the best alternative that can be implemented at Binjai Station. The results of this study will provide guidance to the management of the Binjai train station in making decisions regarding increasing the efficiency of ticket counter services. By optimizing service time and reducing customer waiting time, it is expected to increase customer satisfaction and operational efficiency of train stations.
Simulation Of The Queue For Collecting Village Social Assistance Funds Using The Exponential Method Triana Dewi lestari; Akim m h pardede; katen lumbanbatu
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 3 No. 1 (2023): October 2023
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v3i1.347

Abstract

Abstract This research aims to model and analyze the queuing process for collecting Village Bansus funds using an exponential distribution-based simulation method. The exponential method is used to describe the time variability between the arrival of the applicant and the service time in the queue. By utilizing simulation software, this research will examine various fund collection scenarios, including the effect of the number of service personnel on applicant waiting times and the efficiency of the fund collection process. It is hoped that the results of this simulation can provide recommendations for increasing efficiency in the process of collecting Village Bansus funds, including determining the optimal number of service officers. Apart from that, this research can also help village governments in planning and managing the Village Assistance program so that it can be more effective and responsive to community needs. This simulation provides important insight into how the queuing process can be optimized to improve the quality of service to applicants for Village Bansus funds.
Design And Development Of Karo Traditional Music Instrument Recognition Application Based On Digital Image Using Convolutional Neural Network Method Rizki Oktavinus Tarigan; Achmad Fauzi
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 3 No. 1 (2023): October 2023
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v3i1.348

Abstract

In this modern era, multimedia technology has role important in various field like education, health, and publications. Thesis This focused on development application introduction tool music traditional Karo tribe based digital image use Convolutional Neural Network (CNN) method. Karo music has characteristic typical unique and important for culture of North Sumatra. Study This use method Squeezenet and MobileNetV2 for compare accuracy in introduction object tool music Karo tribe. The Convolutional Neural Network (CNN) method is used in the introduction process. Steps covers convolution, function Activation ReLU, pooling, layers connected full, and the output layer with function Activation Soft max. Image data tool music Karo tribe gathered from Google Images. System This own steps like preprocessing image, model training with CNN method, and analysis results training. Research results This give comparison accuracy between method Squeezenet and MobileNetV2 in recognize tool music Karo tribe. Supporting data used in analysis, especially image tool music obtained Karo tribe from Google Images, with structured design and implementation of CNN, applications This succeed recognize type tool music with level good accuracy.
Grouping of Outstanding Students at Abdi Negara Vocational School Using the K-Nearest Neighbor Method Erika Br Milala
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 3 No. 1 (2023): October 2023
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v3i1.349

Abstract

Abdi Negara Vocational School is a Vocational High School in the city of Binjai. To improve the competence of their students, and so that students are more focused on developing their own potential and interests. As for the basis for classifying students, namely values, academic potential, academic ability, academic achievement, ethics and attitudes, as well as the assessment of teachers and homeroom teachers. Currently the system running at Abdi Negara Vocational School for grouping students is through school management and teacher meetings. Where in the meeting it will be discussed which students are nominated as outstanding students. So the homeroom teacher will provide names for consideration. The grouping process at Abdi Negara Vocational School has several problems, including first, a lot of data will take up time, energy and requires extra precision. Second, the accuracy of the recapitulated processed data is often wrong because the components used as parameters are quite a lot, as well as the data to be grouped. From these problems, we need a technique that can help in grouping high achieving students in State Vocational Schools precisely and accurately so as to reduce the risk of errors. Algorithms such as K-Nearest Neighbor and a website-based system can make it easier to input grades and group students. From the results of trials on existing cases, it was obtained that a student named Rahma was classified as an Outstanding Student. These results are obtained from the results of calculations with the distance between the selected K values ​​and then with the most classification, namely the outstanding students with grades0.929 and 0.976.
Determining the Best Route for Multiple Orders Clients in Food Delivery Services with Simulated Annealing Algorithm Delila Amynadia Delila
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 3 No. 1 (2023): October 2023
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v3i1.350

Abstract

Food delivery services have been widely implemented by several companies such as Gojek Indonesia, Grab, Shopee Food and many more. Busyness and busy activity motivates someone to order online food delivery to meet their needs. For example, a worker who is tired of working all day orders food online for the dinner menu instead of cooking. Simulated annealing (SA) is an algorithm for performing general optimization. In this study, researchers built a system that determines the best delivery routes to deliver messages between customer meals using a simulated annealing algorithm. From the results of the study it was found that the application of the simulated annealing algorithm in finding the best route for multiple client food delivery in Binjai using data collected from drivers was quite good. Based on the results of trials conducted, Route [0-1-5-2-3-4] with a length of 6.29 km is the best route among others.
Employee Selection Decision Support System The Best Marketing at SMK Dwiwarna Medan Using the Simple Additive Weighting Method Uni Anzar
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 3 No. 1 (2023): October 2023
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v3i1.351

Abstract

Medan Dwiwarna Private Vocational School is a private school that has the main advantage of being a center of excellence (PK) school. Medan Dwiwarna Vocational School has 8 (eight) school departments. Currently, the best marketing selection system at Dwiwarna Private Vocational School in Medan still uses manual selection methods, because there is no system that can automatically select the best employees based on criteria and assessment of marketing performance using an application system. The criteria determined to be able to select one of the best marketing employees to work at Dwiwarna Private Vocational School in Medan require that every marketing employee must have high discipline and royalty at Dwiwarna Private Vocational School in Medan. To find the right solution in this research, a decision support system was created that can select one of the best marketing employees to be given a bonus for their performance using a simple additive weighting method which functions to provide an assessment of each marketing employee with the final result of ranking the best performance in the marketing sector.
Data Mining Grouping Areas Of Diarrhea Disease In The City Medan Using K-Means (Clustering) Algorithm In Service Environment In Medan City Borkat parulian pohan
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 3 No. 1 (2023): October 2023
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v3i1.353

Abstract

Diarrhea is a contagious disease and is characterized by symptoms such as changes in the shape and consistency of the stool from becoming soft to liquefying and an increase in the frequency of defecation more than usual accompanied by vomiting, thus causing sufferers to experience a lack of fluids in the body or dehydration which in In the end, if you don't get help immediately it can cause seriousness and even death. Diarrhea can attack all ages with symptoms such as frequent bowel movements with a liquid or watery stool consistency, signs and symptoms of dehydration, fever, vomiting, anorexia, weakness, paleness, changes in vital signs (rapid pulse and breathing), urine output. decreased or absent. Of the 20 data grouping of diarrheal disease areas using the clustering method with the k-means algorithm, 3 groups were obtained, where the most cluster members were in cluster 1 with a total of 11 data centered on centroids 2, 5, 3, namely data on the spread of diarrhea in 6-10 sub-districts, the number 15,000-20,000 sufferers with sporadic distribution status.Keywords: Data Mining, Medan City Environment Service, K-means algorithm
Decision Support System at PDAM Tirta Sari City of Binjai Using the Decision Tree Method in Determining Maintenance Actions for Clean Water Distribution Networks Imam Hidayat
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 3 No. 1 (2023): October 2023
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v3i1.354

Abstract

Water is a very important need for human survival, without water there would be no life on earth. Every region should have clean water service management for community needs, especially in Binjai City which is managed by PDAM Tirta Sari, a company owned by the Binjai City government. Problems that often occur during this time are that water distributed to residents sometimes experiences problems such as difficulty in flowing water to residents' homes, leaks in distribution pipes, dirty water or smelly water if there is heavy rain. Based on the problems above, it is necessary to observe the causes of problems that occur in the distribution of clean water in the city of Binjai. As the community grows and the increasing number of people requesting the installation of new drinking water meters causes pressure on water distribution in the Binjai area, there is a problem of not being able to distribute water normally, therefore it is necessary to examine which areas need to be improved so that water distribution can be even by applying algorithms. DecisionTree. Based on the problem of maintaining the clean water distribution network, it requires a decision-making method that is able to accommodate complex problems, which provides a value to support a decision. One method that can be used is a decision tree. This method is a method that tries to find discrete approximation functions, and was built using the ID3 algorithm (Interative Dychotomizer Version 3), and for ranking using risk analysis. The system is designed using the PHP programming language with a MySQL database. From the results of the decision tree above, it is known that node 1.1 is routine inspection, routine maintenance is carried out to check problems that occur in the field with the aim of ensuring that water distribution can flow normally to residents' homes, node 1.2 monitors water quality, node 1.3 pipe maintenance, node 1.4 changes equipment and nodes 1.5 checking water pressure, where the PDAM will check the water pressure if it is known that the water in the reservoir has decreased, then it is ensured that the distributed water pressure reaches the minimum standard so that the water can reach residents' homes.
Linear Regression Algorithm Predicts Bullying Rate Of Sma Negeri 6 Binjai Students Kelana Rambe
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 3 No. 1 (2023): October 2023
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v3i1.355

Abstract

At SMA Negeri 6 Binjai which is a school located in the city of Binjai in the village of Nangka village, and has several educators and teaching staff in this school, the case study of bullying in schools that is focused in this study, in order to obtain the predicted level of bullying that occurs in SMA Negeri 6 Binjai schools where there is physical and non-physical bullying and through social media. So that the school can find out how much bullying occurs in SMA Negeri 6 Binjai. Method used to solve problems in bullying rate prediction with Linear Regression algorithm. To make it easier for SMA Negeri 6 schools to predict bullying with a linear regression algorithm. The results of testing the linear regression method in the bullying level at SMA Negeri 6 Binjai school used linear regression with the amount of forecasting data that had been analyzed as an analysis, and determined the forecasting results of the value of 19.60222 obtained data results with the number of bullying levels.

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