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Bulletin of Data Science
Published by Forum Kerjasama Pendidikan TInggi
ISSN : -     EISSN : 28079493     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering
Bulletin of Data Science journal publishes manuscripts within the fields of: 1. Soft Computing, 2. Experts System, 3. Decision Support System, 4. Cryptography, 5. Big Data, 6. Data Mining, 7. Artificial Inteligence, and etc
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 5 Documents
 1 
Search results for , issue "Vol 2 No 2 (2023): February 2023" : 5 Documents clear
Implementasi Metode MD2 Untuk Autentikasi Hasil Citra Rontgen (Ronsen) Harahap, Mahanum
Bulletin of Data Science Vol 2 No 2 (2023): February 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletinds.v2i2.4021

Abstract

Implementation is considered as the main form and a crucial stage in the policy-making process or the implementation of a carefully and detailed plan, that without effective implementation, policy decisions will not be successfully executed. Implementation can also be interpreted as a series of actions carried out by various policy implementers with supporting means based on established rules to achieve predetermined goals. Authentication can also be interpreted as a very important thing in delivering information, both in the form of data or text messages. This is because authentication is needed for the authenticity of the contents of the data, with the existence of authentication, the use of authentication systems is expected to form a specific system in that field, one example is the implementation of X-ray image results where the authenticity of the data must be truly real with the results diagnosed by the doctor on the patient. The Message Digest Algorithm 2 (MD2) method can be interpreted as a cryptographic hash function developed by Ron Rivest in 1989, this algorithm is optimized using an 8-bit computer. MD2 is actually specified in RFC 1319 and the MD2 algorithm produces a hash value that is 18 bits in size and accepts input messages with an unspecified length. With this method, it is expected to solve problems that often occur in X-ray results so that the process of applying X-ray image results with doctor's diagnosis is tested for its authenticity value based on the MD2 method, then an application is built using the "Hasher Lite" application to prove the results of the whole process.
Penerapan Syaraf Tiruan Untuk Memprediksi Persediaan Barang Menerapkan Algoritma Elman Recurrent Neural Network Sitinjak, Tiur Dahlia
Bulletin of Data Science Vol 2 No 2 (2023): February 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletinds.v2i2.4022

Abstract

Inventory management is an operational issue frequently faced by minimarkets. If the inventory level is too low and demand cannot be met due to insufficient stock, it will lead to customer disappointment, and there is a possibility that customers may not return. Similarly, if the inventory level is too high, it will result in losses for the minimarket, as they need to allocate more space, face potential depreciation of the value of goods, and incur additional costs related to inventory, such as maintenance and accounting expenses. The inventory problem at PT. Indomarco Prismatama arises from the current system used, which is based on the daily sales of each store. The daily sales data is sent to PT. Indomarco Prismatama through a link every day. As a result, the goods sent by the warehouse are based on the daily sales data provided. This needs to be improved to maximize the warehouse's performance in providing goods, especially items that need to be sent to each store with varying buying patterns specific to each store. To address the inventory management issues, a robust system is required to optimize the inventory at the warehouse. The proposed system is expected to accurately calculate the inventory at PT. Indomarco Prismatama by utilizing an artificial neural network employing the Elman Recurrent Neural Network (ERNN) algorithm.
Kombinasi Metode Discrete Cosine Transform Dan Convolutional Neural Network Dalam Mengidentifikasi Tingkat Kematangan Buah Mangga Berdasarkan Warna Purba, Riski Arnol; Pristiwanto, Pristiwanto; Sihite, A. M. Hatuaon
Bulletin of Data Science Vol 2 No 2 (2023): February 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletinds.v2i2.4497

Abstract

The classification of mango fruit ripeness levels is currently predominantly done manually, which unfortunately has several drawbacks. One of the primary shortcomings is the lack of consistency in accuracy, often resulting in differences among operators conducting the sorting. On the other hand, in image classification processes, a combination of the Discrete Cosine Transform (DCT) and Convolutional Neural Network (CNN) methods is utilized. DCT is a technique commonly used in image processing, especially for image pictures. In this research, there is a proposal to merge the Discrete Wavelet Transform method with the Convolutional Neural Network (CNN). Currently, CNN is one of the methods that provides the most significant results in image recognition. CNN attempts to mimic the image recognition system in the human brain, particularly the visual cortex, allowing it to efficiently process image information. The DCT method is used to transform image data into a frequency image form, which is subsequently employed in feature extraction in the Deep Neural Networks classification method. The research results indicate that the combined method of Discrete Cosine Transform and Convolutional Neural Network achieves the highest accuracy rate of 93.33% in classifying mango fruit ripeness levels. This outcome demonstrates significant potential for automating the mango ripeness classification process with high accuracy, overcoming the inconsistencies associated with manual approaches.
Deteksi Ketinggian Air Pada Citra Screenshot Dengan Menerapkan Metode Template Matching Purwati, Rima
Bulletin of Data Science Vol 2 No 2 (2023): February 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletinds.v2i2.4498

Abstract

The current development of digital technology significantly impacts our daily lives. One prominent change is the digitization of image data, altering how we interact with the world around us. Digital technology enables digital media users to utilize image processing as an intelligent solution to tackle various challenges. A critical aspect of this technological application pertains to water level detection, particularly relevant in household water storage. Water storage serves as a pivotal element in storing clean water reserves to meet daily needs. Ensuring an adequate and high-quality water supply within these storage systems is a top priority. However, difficulties arise when attempting to monitor water levels, especially at night when illumination is minimal. To overcome this obstacle, innovative techniques for water detection and recognition are employed to accurately measure water levels during nighttime, aided by easily deployable IP camera technology. One efficient method involves template matching techniques. This innovation serves as a tangible example of how technological advancements, particularly in image processing, can bring about positive changes in managing and monitoring water availability in a household context. Consequently, technology plays a crucial role in meeting daily water needs more effectively, ensuring an ample water supply within the household environment.
Penerapan Algoritma SHA-384 Pada Aplikasi Duplicate Video Scanner Hanafiah, Muhammad
Bulletin of Data Science Vol 2 No 2 (2023): February 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletinds.v2i2.4499

Abstract

Cryptography is used to maintain the security of private information from anyone except those with the authority or secret keys to access encrypted information. However, with the rapid advancement of computer technology, challenges to information security are increasing. Video manipulation is one of the serious threats in the digital world today. Video manipulation is a common phenomenon where individuals can easily manipulate videos with harmful intent or to confuse others. One of the most dangerous types of video manipulation is the duplicate video scanner, in which a fake video is created to resemble the original video in many aspects, including color, shape, objects, and content, without significant changes from other parties. This can deceive many viewers and cause significant losses. In this research, the author proposes the use of the SHA-384 algorithm as a method to detect duplicate video scanners. This algorithm is used to generate a unique signature or hash from video data, which is then used to verify the authenticity of the video. The results of this research have great potential in addressing serious issues related to video manipulation. The ability to distinguish real videos from fake ones has a significant impact in various fields, including law, security, and information integrity. This research provides an effective solution to ensure video authenticity and can help combat the increasing fraud and manipulation in a complex digital environment.

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