Articles
<![CDATA[Application of the Learning Vector Algorithm Quantization On Smart Barcodes ]]>
<![CDATA[Andre Andre]]>;
<![CDATA[Achmad Fauzi]]>;
<![CDATA[Milli Alfhi Syari]]>
<![CDATA[ Indonesian Journal of Education And Computer Science Vol. 1 No. 2 (2023): INDOTECH - August 2023 ]]>
Publisher : <![CDATA[PT. INOVASI TEKNOLOGI KOMPUTER ]]>
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DOI: 10.60076/indotech.v1i2.41
<![CDATA[The implementation of the Learning Vector Quantization (LVQ) algorithm on smart barcodes aims to enhance efficiency and accuracy in recognizing and tracking product data. In this context, barcodes serve as visual representations containing crucial product information. The LVQ algorithm is employed to optimize the classification and matching processes of barcode data with precise references. Through repeated training, this algorithm adapts learning vectors to better recognize barcode variations. In this study, researchers analyze the impact of LVQ algorithm implementation on smart barcode systems concerning identification accuracy, computational efficiency, and adaptability to changes. Experimental results demonstrate the significant benefits of applying barcodes to inventory systems in overall stock management and business efficiency. By utilizing barcode technology, the processes of tracking and recording product data become faster, more accurate, and automated. Barcode usage minimizes human errors, optimizes time, and reduces operational costs. By combining the intelligence of the LVQ algorithm with the potential of barcodes, this research illustrates a crucial advancement in the technology integration domain for the development of more sophisticated and effective systems]]>
<![CDATA[Watermarking QR Code Application On Birth Certificates Using The Discrete Cosine Transform (DCT) Method ]]>
<![CDATA[Aulia Firliansyah]]>;
<![CDATA[Achmad Fauzi]]>;
<![CDATA[Hermansyah Sembiring]]>
<![CDATA[ Indonesian Journal of Education And Computer Science Vol. 1 No. 2 (2023): INDOTECH - August 2023 ]]>
Publisher : <![CDATA[PT. INOVASI TEKNOLOGI KOMPUTER ]]>
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DOI: 10.60076/indotech.v1i2.46
<![CDATA[The current era's development directs us to understand data security better. Vital documents such as family cards often become subjects of forgery. Therefore, we must be capable of safeguarding the confidentiality of our data. This issue can be addressed through watermarking methods. Watermarking is a technique that can be used to embed information into an image. A digital image represents a machine-captured approximation of an image based on sampling and quantization. The image utilized here employs QR Code, which represents the evolution of one-dimensional barcodes into two-dimensional forms. This study employs the Discrete Cosine Transform (DCT) algorithm. This algorithm converts data from spatial form by segmenting images into sub-parts with varying frequencies. The application of the Discrete Cosine Transform (DCT) method in watermarking the QR Code on birth certificates has significantly contributed to the security and authentication of the document. Throughout this implementation, DCT has proven to be an effective tool for embedding additional information into birth certificate images without compromising the integrity of the main information. However, it should be noted that the use of DCT can also impact the visual quality of the image. Thus, parameter adjustments are necessary to strike the right balance between security and visual aesthetics.]]>
<![CDATA[Hybrid Sistem Algoritma Rivest Shamir Adleman (RSA) dan Algoritma Blum Blum Shub (BBS) dalam Mengamankan File Database E-Absensi ]]>
<![CDATA[Tania Br Surbakti]]>;
<![CDATA[Achmad Fauzi]]>;
<![CDATA[Husnul Khair]]>
<![CDATA[ Indonesian Journal of Education And Computer Science Vol. 1 No. 3 (2023): INDOTECH - December 2023 ]]>
Publisher : <![CDATA[PT. INOVASI TEKNOLOGI KOMPUTER ]]>
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DOI: 10.60076/indotech.v1i2.59
<![CDATA[The E-Attendance System has become an efficient solution in monitoring individual attendance at various institutions. However, new challenges arise regarding data security and privacy in managing E-Attendance database files. Facing potential risks such as hacking and data leaks, data security becomes very important. Therefore, in this study, we propose the implementation of a hybrid system that combines the strengths of the Rivest Shamir Adleman (RSA) Algorithm and the Blum Blum Shub (BBS) Algorithm to improve the security of the E-Absence database file. RSA is a cryptographic algorithm that is widely used for encryption and digital signatures. On the other hand, BBS is a random number generation algorithm that has a strong level of security. The combination of the two in the form of a hybrid system is expected to provide a higher level of security in securing E-Absence data. The aim of this research is to develop a hybrid RSA and BBS system in the context of securing E-Attendance database files. This research outlines the basic concepts of the two algorithms and how they can be integrated. The results of this study are the combination of the Rivers, Shamir, Adleman (RSA) algorithm and the Blum Blum Shub (BBS) algorithm in a hybrid system to increase security in the process of encoding messages]]>
<![CDATA[A Combination Of A Rail Fence Cipher And Merkle Hellman Algorithm For Digital Image Security ]]>
<![CDATA[Irwansyah]]>;
<![CDATA[Achmad Fauzi]]>;
<![CDATA[Siswan Syahputra]]>
<![CDATA[ Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 2 No. 3 (2023): June 2023 ]]>
Publisher : <![CDATA[Yayasan Kita Menulis ]]>
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DOI: 10.59934/jaiea.v2i3.212
<![CDATA[Image is a combination of planes, points, lines and colors to create a physical or human object. Images can be in the form of 2-dimensional images, such as photographs and paintings. 3-dimensional image like a statue. The use of image media information has several weaknesses, one of which is the ease with which it can be manipulated by certain parties with the help of increasingly developing technology. In this study, the Rail Fence Cipher and Merkle Hellman methods were applied which aimed to obtain a stronger cipher by utilizing two key levels where an asymmetric algorithm was used to protect the symmetric key. The asymmetric algorithm used is Merkle Hellman and the symmetrical algorithm used is Rail Fence Cipher. The results of this study indicate that applying the Rail Fence Cipher and Merkle Hellman algorithms can secure image files and secure keys for data integrity. Encryption and description processing time is affected by the size and resolution of the image file.]]>
<![CDATA[Digital Image Security Implementation With Uses Super Encryption Algorithm Myszkowski And The Algorithm Paillier Cryptosystem ]]>
<![CDATA[EVAPIONA]]>;
<![CDATA[Achmad Fauzi]]>;
<![CDATA[Milli Alfhi Syari]]>
<![CDATA[ Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 3 No. 1 (2023): October 2023 ]]>
Publisher : <![CDATA[Yayasan Kita Menulis ]]>
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DOI: 10.59934/jaiea.v3i1.262
<![CDATA[This study aims to implement digital image security by applying two encryption algorithms, namely the Myszkowski algorithm and the Paillier Cryptosystem algorithm. Digital images are a very important form of data and are used frequently in a variety of applications, so protecting their security is a major concern. The encryption method proposed in this study uses a combination of the Myszkowski algorithm to randomize image pixels and the Paillier Cryptosystem algorithm to perform symmetric key encryption. At the experimental stage, qualitative and quantitative analysis was carried out on the performance of the encryption implemented on digital images. Testing is carried out by comparing the level of security and encryption speed of the two algorithms used. In addition, size analysis of encrypted images was also performed to evaluate the efficiency of the proposed system. The results of the study show that the use of a combination of the Myszkowski algorithm and the Paillier Cryptosystem algorithm provides a high level of security for digital images. In addition, the efficiency of this system has also been proven in producing efficient encryption image sizes, so that it can be implemented in image-based applications that require a higher level of security.]]>
<![CDATA[Application Of Super Encryption Using Rot 13 Algorithm Method and Algorithm Beaufort Cipher For Image Security Digital ]]>
<![CDATA[AYUDEVIAPERTIWI]]>;
<![CDATA[Achmad Fauzi]]>;
<![CDATA[Siswan Syahputra]]>
<![CDATA[ Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 3 No. 1 (2023): October 2023 ]]>
Publisher : <![CDATA[Yayasan Kita Menulis ]]>
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DOI: 10.59934/jaiea.v3i1.263
<![CDATA[Digital image security is becoming increasingly critical in today's digital era, where sensitive information and data are often stored in image form. Therefore, an effective and secure encryption method is needed to protect the integrity and confidentiality of digital images. This study aims to implement a stronger security approach by combining classic encryption methods, namely the ROT13 algorithm and the Beaufort Cipher algorithm which produces an encryption called "Super Encryption". In this study, first of all, the ROT13 encryption method will be applied to randomize digital image text by shifting characters as far as 13 positions in the alphabet. Then, the Beaufort Cipher algorithm will be used to apply additional encryption to the digital image, which involves using the key as input in the encryption process. The results of this study indicate that the Super Encryption method which combines the ROT13 and Beaufort Cipher algorithms provides a higher level of security compared to using each method separately. Security testing and vulnerability analysis show that the combination of these two algorithms produces digital images that are more difficult to decrypt by commonly used decryption attacks.]]>
<![CDATA[Clustering Disease on Settlements Inhabitant In place seedy With Use Clustering Method ]]>
<![CDATA[Ruine Buana Br Sitepu]]>;
<![CDATA[Achmad Fauzi]]>;
<![CDATA[Rusmin Saragih]]>
<![CDATA[ Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 3 No. 1 (2023): October 2023 ]]>
Publisher : <![CDATA[Yayasan Kita Menulis ]]>
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DOI: 10.59934/jaiea.v3i1.275
<![CDATA[Residents living in slum areas often face serious problems related to public health, where the prevalence of disease tends to be high and its spread is difficult to control. The impact of the formation of slums for the community is that safety is threatened, health deteriorates, and social conditions worsen, causing many diseases for people living in slums. Therefore, this study aims to identify patterns and clusters of diseases that exist in residential areas in slums Binjai city using clustering method. The K-Means Algorithm clustering method was chosen because it is able to group data based on similar characteristics, so that it can help identify diseases in a more focused and efficient manner, using the MATLAB application is also very appropriate in this problem so that it can produce output from data mining that can be used in decision making. future decisions. By utilizing the data mining process using the clustering method, clustering can be a problem of grouping diseases in slum settlements. Based on the results of trials with 20 sample data conducted with MATLAB obtained in cluster 1 DHF cases with high slums, Cluster 2 cases of vomiting with moderate slums and cluster 3 cases of diarrhea with moderate slums. The results of this study are expected to provide in-depth insight into disease patterns and clusters in residential areas in slums.]]>
<![CDATA[Diagnosis of Baby Blues Syndrome sing the Certainty Factor Method (Case Study: FULL BETHESDA Hospital) ]]>
<![CDATA[Sulisni]]>;
<![CDATA[Achmad Fauzi]]>;
<![CDATA[Suci Ramadani]]>
<![CDATA[ Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 3 No. 1 (2023): October 2023 ]]>
Publisher : <![CDATA[Yayasan Kita Menulis ]]>
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DOI: 10.59934/jaiea.v3i1.289
<![CDATA[Baby blues syndrome is a psychological disorder experienced by women after giving birth, such as feeling excessively upset and sad, and tired for no apparent reason. About 80% of women who have just given birth will experience Baby blues Syndrome, if this continues and is prolonged it will be very dangerous for the health of the mother and baby. From the problems above, the hospital needs to have an additional system that can help make it easier for the medical team to speed up handlers in analyzing and diagnosing Baby blues Syndrome suffered by patients using the certainty factor method. The purpose of this research is to build an expert system for diagnosing the symptoms of Baby blues syndrome using the certainty factor method. Based on the results of the CF calculation, the highest score is the type of baby blues syndrome with a value of 0.9602 or 96.02%. From the results obtained, the system identified that the patient had a type of baby blues syndrome.]]>
<![CDATA[Application Of The Ahp Method In Decision Support System For Security Recruitment ]]>
<![CDATA[Agung Kurniawan]]>;
<![CDATA[Achmad Fauzi]]>;
<![CDATA[Siswan Syahputra]]>
<![CDATA[ Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 3 No. 1 (2023): October 2023 ]]>
Publisher : <![CDATA[Yayasan Kita Menulis ]]>
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DOI: 10.59934/jaiea.v3i1.312
<![CDATA[PT Perkebunan Nusantara II (PTPN II) Sei Semayang, a state-owned enterprise (BUMN) engaged in palm oil and sugarcane production. Security officers play a crucial role in maintaining the company's security and productivity. Currently, the security officer recruitment process remains conventional, relying on subjective assessments based on several criteria. The aim of this study is to introduce a more structured, transparent, and objective approach to security officer recruitment. By implementing the Analytic Hierarchy Process (AHP) method, decisions in selecting prospective security officers can be made based on predetermined criterion weights. AHP enables decision-makers to identify, compare, and prioritize relevant criteria, addressing the complexity of selecting candidates who fit the established criteria. Through this approach, the study seeks to enhance efficiency and effectiveness in the security officer selection process, reduce the risk of errors in candidate selection, and improve overall company performance and security. It is hoped that the application of the AHP method in the decision support system for security officer recruitment at PTPN II Sei Semayang will assist the company in optimizing the selection process and supporting more data-driven decision-making.]]>
<![CDATA[Identification of Banana Fruit Types Using the Backpropagation Method ]]>
<![CDATA[Dian Widodo]]>;
<![CDATA[Achmad Fauzi]]>;
<![CDATA[Arnes Sembiring]]>
<![CDATA[ Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 3 No. 1 (2023): October 2023 ]]>
Publisher : <![CDATA[Yayasan Kita Menulis ]]>
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DOI: 10.59934/jaiea.v3i1.314
<![CDATA[Identification of types of bananas and assessment of their maturity level is an important process in the agricultural and distribution industries. In an effort to automate this process, the authors propose an approach to identify bananas and their level of ripeness using a Backpropagation neural network. Through digital image processing, images or pictures of bananas will be extracted with images such as RGB (red green blue), metric and eccentricity (shape features). The results of the image data training process are as many as 55 image data input, obtained by the training process data on banana types with 11 iterations from the maximum input epoch 10000, target error or performance 0.00642 with an accuracy value of 80%. Furthermore, the training process obtained data on the maturity level of bananas with 4 iterations from the maximum input epoch 10000, the target error or performance is 0.00606 with an accuracy value of 90%. From the test image process that has been carried out, the system can identify the type of banana and its maturity level based on the feature extraction input from the image of the banana. This study also aims to test and determine the accuracy of the application of the Backpropagation method in identifying the types of bananas and their level of maturity.]]>
