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JAIS (Journal of Applied Intelligent System)
Published by Universitas Dian Nuswantoro
ISSN : 25020493     EISSN : 25029401     DOI : -
Core Subject :
Journal of Applied Intelligent System (JAIS) is published by LPPM Universitas Dian Nuswantoro Semarang in collaboration with CORIS and IndoCEISS, that focuses on research in Intelligent System. Topics of interest include, but are not limited to: Biometric, image processing, computer vision, knowledge discovery in database, information retrieval, computational intelligence, fuzzy logic, signal processing, speech recognition, speech synthesis, natural language processing, data mining, adaptive game AI.
Arjuna Subject : -
Articles 191 Documents
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Implementation of Temperature and Humidity Control Devices in IOT-Based Hydrophonic Peppermint Cultivation at Sufiagrifarm Slawi Maulana, Donny; Afriantoro, Irfan
Journal of Applied Intelligent System Vol. 8 No. 1 (2023): Journal of Applied Intelligent System
Publisher : Universitas Dian Nuswantoro and IndoCEISS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/jais.v8i1.7171

Abstract

Along with the rapid development of existing technology, especially in the field of information and the Internet of Thinks ( IoT ), which is developing so fast and producing a lot of benefits to help humans both in the field of education and in manufacturing and agriculture. But at this time there are still so many technologies that still cannot be implemented in certain fields, for example like agriculture, where everything is still done manually so that it takes a lot of time, costs and also more energy in the process. Such as the constraints that exist with Sufiagrifarm, where in this case to meet the needs of temperature and humidity in Peppermint plants that use a hydrophonic planting system it is still done manually by spraying the plants with a spray that produces dew. Given these problems, this research aims to assist Sufiagrifarm in overcoming problems in regulating temperature and humidity in peppermint plants so that temperature and humidity compliance in peppermint plants can be carried out automatically and can be monitored in real time. Development in this method is carried out using the SDLC Waterfall method. This application was created using the Java programming language using the MITApp inventor platform, for the tool itself it was made using an Arduino microcontroller with the C programming language supported by several other devices such as Thingspeak. The results of this study are to help fulfill temperature and humidity in peppermint cultivation at Sufiagrifarm.
Design Of Gas Leak Detection Using Gas Sensor And Microcontroller Based On Android Indriyono, Bonifacius Vicky; Zahari, Iqlima; Karmila, Karmila; Alimudin, Erna; Wijoyo, Tomsen
Journal of Applied Intelligent System Vol. 8 No. 1 (2023): Journal of Applied Intelligent System
Publisher : Universitas Dian Nuswantoro and IndoCEISS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/jais.v8i1.7076

Abstract

Today the use of gas cylinders is increasingly widespread in society. Starting from simple stalls, street vendors and many households use these gas cylinders. The impact that occurs is an increase in orders to producers to produce gas cylinders. With the increase in orders, it causes less attention to the safety side of gas cylinders. One side of security that is not given enough attention is gas leaks. This study aims to implement Internet of Things (IOT) concept by designing a tool that can be used to detect leaks using the MQ-2 gas sensor and android. This tool serves to provide leak notifications in the form of an alarm. The alarm will turn on automatically when the sensor detects gas that emits an odor so that it can be anticipated immediately. The test results show that this detector can work properly and optimally in giving gas cylinder leak warnings.
The Implementation of Improved Advanced Encryption Standard and Least Significant Bit for Securing Messages in Images Pujiono, Imam Prayogo; Rachmawanto, Eko Hari; Nugroho, Dicky Anggriawan
Journal of Applied Intelligent System Vol. 8 No. 1 (2023): Journal of Applied Intelligent System
Publisher : Universitas Dian Nuswantoro and IndoCEISS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/jais.v8i1.7324

Abstract

Security and confidentiality are essential aspects needed in the process of exchanging messages. Maintaining the message's security and confidentiality can be done by encrypting the message with cryptographic techniques to protect the message. However, the encrypted message (ciphertext) usually raises suspicion from eavesdroppers so that they try to unravel the contents of the message or damage the contents of the message or prevent the message from reaching the intended recipient. To avoid eavesdroppers' suspicion of encrypted messages, after encryption, the ciphertext can then be inserted into an image using steganography techniques so that eavesdroppers do not know whether there is a secret message in an image. In this research, the authors use the Improved AES-128 (Advanced Encryption Standard) Algorithm to encrypt messages and LSB (Least Significant Bit) Algorithm to insert ciphertext into an image. Where the AES Algorithm Improvement is made by adding a sending and receiving applications ID to modify the Key Schedule process, with modifications to the Key Schedule process, messages can only be read on the original recipient's cellphone by entering the correct key. The results of this study show that eavesdroppers do not easily know the existence of the ciphertext, besides that even if the eavesdroppers get the ciphertext and know the encryption key, the message remains unreadable on their cellphone because the ID of the application sending or receiving the message has changed.
Comparison of String Similarity Algorithm in post-processing OCR Susanto, Al Birr Karim; Muliadi, Nuraziz; Nugroho, Bagus; Muljono, Muljono
Journal of Applied Intelligent System Vol. 8 No. 1 (2023): Journal of Applied Intelligent System
Publisher : Universitas Dian Nuswantoro and IndoCEISS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/jais.v8i1.7079

Abstract

The Optical Character Recognition (OCR) problem that often occurs is that the image used, has a lot of noise covering letters in a word partially. This can cause misspellings in the process of word recognition or detection in the image. After the OCR process, we must do some post-processing for correcting the word. The words will be corrected using a string similarity algorithm. So what is the best algorithm? We conducted a comparison algorithm including the Levenshtein distance, Hamming distance, Jaro-Winkler, and Sørensen – Dice coefficient. After testing, the most effective algorithm is the Sørensen-Dice coefficient with a value of 0.88 for the value of precision, recall, and F1 score
Gerga Orange Quality Using Naïve Bayes Based on Feature Extraction Nugroho, Fajar Raditya; Khoirudin, Khoirudin
Journal of Applied Intelligent System Vol. 8 No. 1 (2023): Journal of Applied Intelligent System
Publisher : Universitas Dian Nuswantoro and IndoCEISS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/jais.v8i1.7335

Abstract

In an effort to increase the number of sales, the process of classifying the type of Gerga citrus fruit is very necessary. The problem that often occurs is the mixing of various types of fruit from the storage warehouse so that the quality of the fruit will be mixed and it will be difficult to determine the selling price because the quality of the fruit itself is not evenly distributed so that a sorting process is needed. There are still many sellers or growers of citrus fruits who sort the quality of the fruit manually so that it can take a very long time. Given these problems, it is necessary to classify the quality of Gerga oranges automatically with the Naïve Bayes Classifier algorithm with GLCM feature extraction and HSV color characteristics. as a method for classifying the quality of Gerga citrus fruit and as for the media used, there is digital image media. From the experiments that have been carried out the use of angles in the formation of co-occurrence matrices with the best accuracy values reaching 80% are found at angles of 0°, 45°, and 135°, while the lowest accuracy values are found at angles of 90°. It was concluded that the Gerga citrus fruit quality classification system using the Naïve Bayes method was categorized as good with an AUC value of 0.8.
Implementation of the K-Nearst Neighbor (k-NN) Algorithm in Classification of Angora and Country Cats Andriana, Wiwin; Wisnumurti, Reza; Lestari, Yuni; Indriyono, Bonifacius Vicky; Wibowo, Dibyo Adi; Udayanti, Erika Devi
Journal of Applied Intelligent System Vol. 8 No. 1 (2023): Journal of Applied Intelligent System
Publisher : Universitas Dian Nuswantoro and IndoCEISS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/jais.v8i1.7129

Abstract

There are so many types of mixed cats from various cat breeds, so many people find it difficult to identify and classify them. Therefore, we need a method that can classify the type of cat breeds. In this study the authors used the K-Nearest Neighbor (k-NN) algorithm to make it easier to recognize and classify cat breeds based on certain characteristics. The author took samples of 2 types of cat races, namely the Anggora race and the Kampung race. The implementation stage is to determine the euclidean distance and sort it and then determine the value of K to find the nearest neighbor. In testing, the authors used 50 training data and 50 test data with 6 attributes used, namely body shape, nose width, nose height, food type, hair type and hair length. The results of the classification of cat breeds using the k-NN method obtained an accuracy rate of 94% and an error rate of 6%.
Classification of Naive Bayes Algorithm on Dengue Hemorrhagic Fever and Typhoid Fever Based on Hematology Results Handayani, Yuni; Hakim, Alvin Rainaldy
Journal of Applied Intelligent System Vol. 8 No. 1 (2023): Journal of Applied Intelligent System
Publisher : Universitas Dian Nuswantoro and IndoCEISS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/jais.v8i1.7547

Abstract

The application of increasing technology developed explicitly in the health field would significantly have an urgent role in guaranteeing quality service. Application deep data mining techniques classifier method, one among them used for classify something possibility, for example for classification disease. Dengue Hemorrhagic Fever is a disease caused by the dengue virus biting the Aedes aegypti mosquito. Meanwhile, Typhoid Fever is a disease caused by the bacterium Salmonella typhi. The second disease could attack all types of circles, fine children or mature ones. The second disease is almost the same symptom, so a proper diagnosis is needed to differentiate it. Study this applies the Naive Bayes algorithm to classify Dengue Hemorrhagic Fever and Typhoid Fever using 250 yield data test blood routine hematology at Tugurejo Hospital. Attributes used in the study, age, type sex, temperature, leukocytes, erythrocytes, hemoglobin, hematocrit, platelets, anti-dengue IgG, anti-dengue IgM, salmonella typhi o and salmonella Typhi h. The Naïve Bayes method is one of the techniques that can be used to perform analysis in determining the diagnostic results from a number of data studied with the aim of producing optimal results. The use of the Naïve Bayes method in this application is due to the probability that the accuracy value of the Nave Bayes method is close to the accuracy value of the experts.[12] The results of testing the Naive Bayes method using a confusion matrix show Recall value is 97.62%, Precision is 93.89%, accuracy is 93.33%, and Error Rate is 6 %. It can be concluded that this method is suitable for classifying Dengue Hemorrhagic Fever and Typhoid Fever and can be applied in studying this.
Decision Support System For Determining The Best Employee Using The Visekriterijumsko Kompromisno Rangiranje Method (Case Study At Distribution Center Guardian) Auliyah, Risma; Maulana, Donny; Afriantoro, Irfan
Journal of Applied Intelligent System Vol. 8 No. 2 (2023): Journal of Applied Intelligent System
Publisher : Universitas Dian Nuswantoro and IndoCEISS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/jais.v8i2.8637

Abstract

The quality of human resources is one of the supporting factors to increase the performance productivity of a corporate agency. Highly competent human resources can support the level of performance, with performance appraisal, the achievements of each employee will be obtained. To obtain fast and accurate information on employee performance that meets the expected criteria. To find out this, with a multi-criteria decision-making method by solving complex and unstructured situations into parts and compiling them using the Visekriterijumsko Kompromisno Rangiranje (VIKOR) method on Decision Support Systems (SPK), the determination of the best employee can be calculated based on the calculation of the weight their respective criteria, so that they can quickly select the best employees in the company. From the final results of the VIKOR method, ranking 1 is Sukron, with a value of 0.
File Cryptography Optimization Based on Vigenere Cipher and Advanced Encryption Standard (AES) Muslih, Muslih; Handoko, L. Budi; Rizqy, Aditya
Journal of Applied Intelligent System Vol. 8 No. 2 (2023): Journal of Applied Intelligent System
Publisher : Universitas Dian Nuswantoro and IndoCEISS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/jais.v8i2.7899

Abstract

The rapid The main problem in the misuse of data used in crime is the result of a lack of file security. This study proposes a data security method to protect document files using the Advanced Encryption Standard (AES) algorithm combined with the Vigenere Cipher. This research carried out 2 processes, namely the encryption process and the decryption process. The encryption process will be carried out by the AES algorithm and then encrypted again with the Vigenere Cipher algorithm. The experiments show that the proposed method can encrypt files properly, where there are changes in the value of the document file and the encrypted file cannot be opened and the description results do not cause changes to the original file. The results of this study are that the system is able to work properly so as to produce file encryption and decryption using the AES method combined with the Vigenere Cipher. In document files, the largest difference in encryption and decryption time is 8 seconds, while in image files the difference in encryption and decryption time is 17 seconds. This longest time difference is generated by large files.
The Involvement of Local Binary Pattern to Improve the Accuracy of Multi Support Vector-Based Javanese Handwriting Character Recognition Sari, Christy Atika; Sari, Wellia Shinta; Shelomita, Viki Ari; Kusuma, Mohammad Roni; Puspa, Silfi Andriana; Gusta, Muhammad Bima
Journal of Applied Intelligent System Vol. 8 No. 2 (2023): Journal of Applied Intelligent System
Publisher : Universitas Dian Nuswantoro and IndoCEISS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/jais.v8i2.8450

Abstract

Indonesia is a country that is rich in cultural diversity. An example of one such variety is the Javanese language. The letters that are usually used in Javanese are non-Latin letters or are usually known as Javanese script. However, along with advances in technology, the Javanese language is increasingly being forgotten. In the past, the Javanese script was used as a subject in schools, aiming for Indonesian students to continue to gain knowledge about the Javanese script. The initial step in the introduction of the Javanese script starts with the preprocessing process by changing the image of the Javanese script from the RGB image to a grayscale image which is then performed feature extraction, where the feature extraction used in this script recognition is texture extraction with the Local Binary Pattern (LBP) algorithm. The results of this processing are obtained information that can be used as a parameter in the Multi Support Vector Machine (SVM) classification to predict Javanese script images. In this study using the LBP method with the Multi SVM Algorithm as a classification algorithm produces a high accuracy of 90% in the recognition of Javanese script, better than using only Multi SVM with an accuracy of 80%.

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