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Journal of Applied Engineering and Technological Science (JAETS)

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Published by Yayasan Pendidikan Riset dan Pengembangan Intelektual

ISSN : 27156087 EISSN : 27156079 DOI : -

Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Industrial & Manufacturing Engineering

Journal of Applied Engineering and Technological Science (JAETS) is published by Yayasan Pendidikan Riset dan Pengembangan Intelektual (YRPI), Pekanbaru, Indonesia. It is academic, online, open access, peer reviewed international journal. It aims to publish original, theoretical and practical advances in Computer Science & Engineering, Information Technology, Electrical and Electronics Engineering, Electronics and Telecommunication, Mechanical Engineering, Civil Engineering, Textile Engineering and all interdisciplinary streams of Engineering Sciences. Journal of Applied Engineering and Technological Science (JAETS) is published annually 2 times every June and Desember.

Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)

Articles 358 Documents

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Classification of Booster Vaccination Symptoms Using Naive Bayes Algorithm and C4.5 Rudi Tri Jaya; Tri Wahyudi
Journal of Applied Engineering and Technological Science (JAETS) Vol. 4 No. 1 (2022): Journal of Applied Engineering and Technological Science (JAETS)
Publisher : Yayasan Riset dan Pengembangan Intelektual (YRPI)

Covid-19 is a respiratory infection that is transmitted through the air. The first case was reported on March 2, 2020, to be precise in Depok, West Java, Indonesia. To reduce the number of corona virus sufferers, the government has made various efforts including policies to limit activities outside the home, online learning, work from home, and even worship activities. To reduce the number of people infected with the Covid-19 virus, efforts are being made, one of which is the provision of vaccines. In this study, the types of booster vaccines are Pfizer and AstraZeneca. Due to the symptoms caused by the condition of the patient after vaccination, the researchers used the Naive Bayes Algorithm and C4.5 methods with attributes including gender, age, comorbidities (comorbidities), temperature, blood pressure, Covid 19 survivors > 1 month, pregnant condition, type of vaccine. primer and booster vaccine types which aim to get the highest accuracy value between the two algorithm methods which are tested using cross validation on the RapidMiner Studio tool. And obtained the Naive Bayes algorithm method with the highest accuracy value of 78.82%. Keywords: Covid 19, booster, AEFI, Naive Bayes, C4.5, Rapid Miner

Classification of Maturity Levels in Areca Fruit Based on HSV Image Using the KNN Method Frencis Matheos Sarimole; Anita Rosiana
Journal of Applied Engineering and Technological Science (JAETS) Vol. 4 No. 1 (2022): Journal of Applied Engineering and Technological Science (JAETS)
Publisher : Yayasan Riset dan Pengembangan Intelektual (YRPI)

Areca nut (Areca catechu) is a kind of palm plant that grows in Asia and Africa, the eastern part of the Pacific and in Indonesia itself, areca nut can also be found on the islands of Java, Sumatra and Kalimantan. At the stage of classifying the maturity of the betel nut so far, it is still using the manual method which at that stage has subjective weaknesses. Based on these problems, researchers will create a system that is able to classify the level of maturity of areca nut using HSV feature extraction with assistance at the classification stage using the KNN method. In this study, 842 datasets were used which were divided into 3 types of classes, namely ripe, unripe and old fruit. The dataset was divided into 683 training data and 159 test data. In the next stage, the data is tested using the K-Nearest Neighbor method by calculating the closest distance using k = 1. From the results of the calculation of the closest distance k1 produces an accuracy rate of 87.42%. Kata kunci— Matlab, Areca Ripeness, KNN, HSV.

Ergonomic Risk Analysis of Musculoskeletal Disorders (MSDs) Using ROSA and REBA Methods On Administrative Employees Faculty Of Science Achmad Nuzul Amri; Boy Isma Putra
Journal of Applied Engineering and Technological Science (JAETS) Vol. 4 No. 1 (2022): Journal of Applied Engineering and Technological Science (JAETS)
Publisher : Yayasan Riset dan Pengembangan Intelektual (YRPI)

In administrative tasks, computers really need help so they can get the job done quickly and efficiently. Computers in the administration department are managed by a job that runs continuously for eight hours. Improper work posture and posture can cause fatigue and discomfort at work. One of the influencing factors is the working posture and body posture during these activities. This study aims to reduce the level of risk gained by performing Rapid Office Strain Assessments (ROSA) and Rapid Entire Body Assessments (REBA) for clerical staff in engineering departments. Posture analysis data processing using the ROSA (Rapid Office Strain Assessment) method found that five of her employees surveyed were at risk levels and needed to be corrected immediately. The Rapid Entire Body Assessment (REBA) method shows that five employees are currently at risk of urgent needs and requirements.

Health Detection of Betal Leaves Using Self-Organizing Map and Thresholding Algorithm Dadang Iskandar Mulyana; Ahmad Saepudin; Mesra Betty Yel
Journal of Applied Engineering and Technological Science (JAETS) Vol. 4 No. 1 (2022): Journal of Applied Engineering and Technological Science (JAETS)
Publisher : Yayasan Riset dan Pengembangan Intelektual (YRPI)

Betel leaf is one of the plants that is widely used as a natural or traditional medicine by the community, natural treatment with the use of plants is relatively safer. But there is a problem when we choose healthy betel leaves because of our mistakes in choosing which betel leaves are healthy and which are not. With this research the authors aim to detect healthy and sick betel leaves using data collection. Feature extraction used is the value of Red, Green, and Blue (RGB) and Hue, Saturation, and Value (HSV) to get the characteristics of the color image. Then the results of the feature extraction are used to classify the health of green betel leaves using the Self-Organizing Maps method. The green betel leaf data used is 1500 images for train data and 450 images for testing data are image test data, test data that produces an evaluation value with an accuracy value of 97.20% on the Self-Organizing Maps method.

Classification of Melinjo Fruit Levels Using Skin Color Detection With RGB and HSV Dadang Iskandar; Marjuki Marjuki
Journal of Applied Engineering and Technological Science (JAETS) Vol. 4 No. 1 (2022): Journal of Applied Engineering and Technological Science (JAETS)
Publisher : Yayasan Riset dan Pengembangan Intelektual (YRPI)

This study aims to detect the ripeness of melinjo fruit using digital image method. Structured identification or division using image processing and computer vision requires the socialization of patterns based on training datasets. Melinjo (Gnetum gnemon L.) is a plant that can grow anywhere, such as yards, gardens, or on the sidelines of residential areas, as a result, produces melinjo into a plant that has relatively large potential to be developed. The process of image processing and pattern socialization is a highly developed research study. Starting based on the process of socializing an object, or a structured division of the object and about detecting the level of fruit maturity. The structured division process regarding ripeness into 3 classes, namely: raw, half-cooked and ripe where the process is carried out using Google Collaboratory which processes the RGB color space to HSV. In this study, the testing method for the system that will be used is a functional test where the test is carried out only by observing the execution results through test data and checking the functionality of the system being developed. The level of accuracy obtained from this study is 98.0% correct.

Classification of Durian Types Using Features Extraction Gray Level Co-Occurrence Matrix (GLCM) AND K-Nearest Neighbors (KNN) Frencis Matheos Sarimole; Achmad Syaeful
Journal of Applied Engineering and Technological Science (JAETS) Vol. 4 No. 1 (2022): Journal of Applied Engineering and Technological Science (JAETS)
Publisher : Yayasan Riset dan Pengembangan Intelektual (YRPI)

Durian is one of the most popular fruits because it has a delicious taste and distinctive aroma. It has different shapes and types, especially from thorns and different colors and has fruit parts that are also not the same as other parts. In terms of fruit selection, care must be taken because consumers generally still find it difficult to distinguish physically identified types of Durian fruit due to limited knowledge of the types of Durian fruit and require a relatively long time and accuracy in sorting. Therefore, there is a need for a method to sort the types of Durian fruit effectively and efficiently. Namely image segmentation based on the classification of the types of Durian fruit to help consumers. The method used is Gray Level Co-Occurrence Matrices for feature extraction, while to determine the proximity between the test image and the training image using the K-Nearest Neighbor method based on texture based on the color of the Durian fruit obtained. Extraction features using the GLCM method based on angles of 0°, 45°, 90° and 135°. Then the KNN method is used for the classification of characteristic results using K = 3. In this study, 1281 data training was used and 321 data testing was used, resulting in an accuracy of 93%.

Classification of Edelweiss Flowers Using Data Augmentation and Linear Discriminant Analysis Methods Fransiscus Rolanda Malau; Dadang Iskandar Mulyana
Journal of Applied Engineering and Technological Science (JAETS) Vol. 4 No. 1 (2022): Journal of Applied Engineering and Technological Science (JAETS)
Publisher : Yayasan Riset dan Pengembangan Intelektual (YRPI)

Edelweiss is a plant that grows at a height, and is known as a perennial flower because it has beautiful petals and does not wilt easily. Although edelweiss in Indonesia is still in the same family as Leontopodium Alpinum, it turns out that the type of edelweiss found in the mountains of Indonesia is different from edelweiss found abroad. Therefore, in this study, an image processing system was developed that can classify the types of edelweiss flowers based on their image using Linear Discriminant Analysis to classify data into several classes based on the boundary line (straight line) obtained from linear equations. In this study, the types of edelweiss flowers used in this study were Anaphalis Javanica and Leontopodium Alpinum, the two types of edelweiss flowers were distinguished based on their color characteristics using hue and saturation values. The images used are 1500 images for training data and 450 test data images with a training and test data ratio of 70:30, so that the accuracy produced in the testing process is 99.77% in the Linear Discriminant Analysis method.

Design of Appropriate Technology Based on Waste Treatment Equipment Using Value Engineering Method in Kedung Turi Sultan Afli; Boy Isma Putra
Journal of Applied Engineering and Technological Science (JAETS) Vol. 4 No. 1 (2022): Journal of Applied Engineering and Technological Science (JAETS)
Publisher : Yayasan Riset dan Pengembangan Intelektual (YRPI)

The purpose of this research is to create a waste burner using raw materials from factory welding waste. The method used in this research is the value engineering method. In Gununggansir Village, there is an increase in waste, one of which is in Kedung Turi Hamlet, which is very significant, causing a buildup of garbage and inadequate waste management in Gununggangsir Village. This is an alternative that is made is an environmentally friendly waste incinerator. The process of making a garbage incinerator has the advantage of being environmentally friendly by using used goods that are not used and can still be used. In this research, what will be done is utilizing used goods that have value and function to achieve a target value. The result of using this used material is that it saves the cost of making Trush Burner which was originally worth Rp. 1,626,000 to Rp. 965,000.

Detection of The Deaf Signal Language Using The Single Shot Detection (SSD) Method Dadang Mulyana Iskandar; Mesra Betty Yel; Aldi Sitohang
Journal of Applied Engineering and Technological Science (JAETS) Vol. 4 No. 1 (2022): Journal of Applied Engineering and Technological Science (JAETS)
Publisher : Yayasan Riset dan Pengembangan Intelektual (YRPI)

Sign Language is a language that prioritizes manual communication, body language, and lip movements, instead of sound, to communicate. Deaf people are the main group who use this language, usually by combining hand shape, orientation and movement of the hands, arms, and body, and facial expressions to express their thoughts. Therefore, the researcher created an image recognition program in sign language using the Single Shot Detection (SSD) method, which is a convolution activity by combining several layers of preparation, by utilizing several components that move together and are motivated by a biological sensory system. The letters used in making sign language programs use the letters of the alphabet (az). This sign language detection programming that runs on the Google Collaboratory application

Sign Language Detection System Using Adaptive Neuro Fuzzy Inference System (ANFIS) Method Dadang Mulyana Iskandar; Mesra Betty Yel; Eka Maheswara
Journal of Applied Engineering and Technological Science (JAETS) Vol. 4 No. 1 (2022): Journal of Applied Engineering and Technological Science (JAETS)
Publisher : Yayasan Riset dan Pengembangan Intelektual (YRPI)

Sign language is a language that prioritizes communication with hands, body language, and lip movements to communicate. The deaf are the main group who use this language, often combining hand shape, hand, arm and body orientation and movement, and facial expressions to express their thoughts. The sign language detection system is designed using the Adaptive Neuro Fuzzy Inference System (ANFIS). This study uses data from the kaggle.com dataset, which is a site that provides research data on artificial intelligence. This study was conducted to recognize empty hand signals. Where it will help users naturally without any additional help. The test is carried out using a data set as evidenced by 1 display. In this process, The characteristics of the hand were carried out using the Histogram Oriented Gradient (HOG) method. Meanwhile, to separate it from the background image, it is used with color segmentation. The results of the process are then taken for classification. The classification process uses the Adaptive Neuro Fuzzy Inference System method. The results of the tests carried out for accuracy are as much as

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Home Page

OAI Link

Editorial Team

Contact

Reviewer

Google Scholar

Contact Name
Muhammad Luthfi Hamzah

Contact Email
muhammad.luthfi@uin-suska.ac.id

Phone
+6282385405905

Journal Mail Official
editor.jaets@gmail.com

Editorial Address
Jl. Amanah, No. 17 B Kec. Marpoyan Damai, Pekanbaru, Riau

Location
Kota pekanbaru,

Riau

INDONESIA

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

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Abstract

Home Page

OAI Link

Editorial Team

Contact

Reviewer

Google Scholar

Contact Name Muhammad Luthfi Hamzah

Contact Email muhammad.luthfi@uin-suska.ac.id

Phone +6282385405905

Journal Mail Official editor.jaets@gmail.com

Editorial Address Jl. Amanah, No. 17 B Kec. Marpoyan Damai, Pekanbaru, Riau

Location Kota pekanbaru, Riau INDONESIA

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Contact Name
Muhammad Luthfi Hamzah

Contact Email
muhammad.luthfi@uin-suska.ac.id

Phone
+6282385405905

Journal Mail Official
editor.jaets@gmail.com

Editorial Address
Jl. Amanah, No. 17 B Kec. Marpoyan Damai, Pekanbaru, Riau

Location
Kota pekanbaru,

Riau

INDONESIA