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Sriwijaya Journal of Informatics and Applications
Published by Universitas Sriwijaya
ISSN : -     EISSN : 28072391     DOI : -
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Sriwijaya Journal of Informatics and Applcations (SJIA) is a scientific periodical researchs articles of the Informatics Departement Universitas Sriwijaya. This Journal is an open access journal for scientists and engineers in informatics and Applcations area that provides online publication (two times a year). SJIA offers a good opportunity for academics and industry professionals to publish high quality and refereed papers in various areas of Informatics e.q., Machine Learning & Soft Computing, Data Mining & Big Data Analytics, Computer Vision and Pattern Recognition and Automated Reasoning, and Distributed and security System
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Articles 5 Documents
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Search results for , issue "Vol 3, No 2 (2022)" : 5 Documents clear
Cat Breeds Classification Using Convolutional Neural Network For Multi-Object Image Naura Qatrunnada; Muhammad Fachrurrozi; Alvi Syahrini Utami
Sriwijaya Journal of Informatics and Applications Vol 3, No 2 (2022)
Publisher : Fakultas Ilmu Komputer Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36706/sjia.v3i2.46

Abstract

Cat is one of the most popular pets. There are many cat breeds with unique characteristic and treatment for each breed. A cat owner can have more than one cat, either the same breed or different breeds.  But not all cat owners know the breeds of their cats. Computers can be trained to recognized cat breeds, but there are many challenges for computers because it limited by how much they have been trained and programmed. In recent years, a lot of research about image classification has been done before and got various result, but most of the data used in previous research were single object images. Therefore, this study of cat breeds classification would be conducted with Convolutional Neural Network (CNN) in the Multi-Object images. This method was chosen because it had good classification results in the previous studies. This study used 5 breeds of cats with every breed having 200-3200 images for training. The test results were measured using confusion matrix, obtaining the precision, recall, f1 score and accuracy of 100% on multi-object images with 2 objects and 3 objects. On images with 4 objects achieved the precision, recall, f1 score and accuracy value of 89%, 87%, 87% and 95%. While the value of precision, recall, f1 score and accuracy on images with 5 objects get 87%, 86%, 86% and 94%, respectively.
Text Similarity Detection Between Documents Using Case Based Reasoning Method with Cosine Similarity Measure (Case Study SIMNG LPPM Universitas Sriwijaya) Nabila Febriyanti; Dian Palupi Rini; Osvari Arsalan
Sriwijaya Journal of Informatics and Applications Vol 3, No 2 (2022)
Publisher : Fakultas Ilmu Komputer Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36706/sjia.v3i2.47

Abstract

LPPM Universitas Sriwijaya is an institution that coordinates academic research and community service inside Universitas Sriwijaya. In carrying out the duty, LPPM assesses every proposal’s originality which would be impossible to do manually in the future due to massive data growth. Thus, automatization for the proposal's originality check is needed. The Case Based Reasoning method is used in this research because it allows the system to reuse the information that has been obtained to find documents that are similar to the test document. In this study, the data is represented in the form of the Vector Space Model and uses Cosine Similarity to measure document to document similarity. The data is represented by giving weight for each part of the tested documents. In this study, four formulas from previous research will be used for term weighting then the final result will be compared. The process begins by extracting data, separating parts of the document, figuring the similarity value of the test document to the case base utilizing Cosine Similarity Measure, results filtering with a certain threshold, summarizing the calculation results, and finally preserving the results obtained to be reused in the next calculation. The results of this study indicate that the text-similarity detection between documents has been successfully carried out using the proposed method with the best sensitivity level and the fastest computation time achieved in configuration II.
MEMBER ELECTION DECISION SUPPORT SYSTEM SOUTH SUMATERA PASKIBRAKA USING TOPSIS-PROMETHEE METHOD Angga Adiningrat Mulyanata; Yunita Yunita; Desty Rodiah
Sriwijaya Journal of Informatics and Applications Vol 3, No 2 (2022)
Publisher : Fakultas Ilmu Komputer Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36706/sjia.v3i2.41

Abstract

Paskibraka is the best young generation selected through various selections to raise and lower the Heritage Flag on Indonesian Independence Day. However, in the enthusiasm of the students to take part, the Dispora of South Sumatra Province still uses a manual assessment system so that several obstacles were found in its implementation. done with Microsoft Excel, as well as a calculation system that can only be used for one period, while this selection is an annual event that is held every time to celebrate Indonesian Independence Day. Therefore we need a way that can help the Dispora of South Sumatra Province in determining the best alternative for paskibraka members. One algorithm that is useful in decision support is Topsis. Topsis is used in the application of values for each criterion and a different range of values. Then using the Promethee method can improve the Topsis method because the Promethee method is used to determine the order of priority in multi-criteria analysis. The data taken by 60 participants were then researched according to predetermined criteria including written test scores, interview tests, health tests, physical fitness, and posture. Produced the best participants according to the system as many as 15 data. The results of the research test have an accuracy of 80%.
Securing Text File on Audio Files using Least Significant Bit (LSB) and Blowfish Ahmad Rizky Fauzan; Al Farissi; Muhammad Naufal Rachmatullah
Sriwijaya Journal of Informatics and Applications Vol 3, No 2 (2022)
Publisher : Fakultas Ilmu Komputer Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36706/sjia.v3i2.42

Abstract

Along with the development of technology, communication can be done in various ways, one of which is digital messages. But often the messages sent do not reach their destination and are obtained by irresponsible parties. This happens because of the lack of security in the file. For this reason, security is needed so that messages cannot be stolen or seen by other parties. There are various ways to secure messages, including Steganography and Cryptography techniques. This study uses a combination of the Least Significant Bit method and the Blowfish algorithm to secure secret messages in audio files. This research will measure encryption and decryption time, analysis of message file size changes after encryption and decryption, and PSNR value of audio files. The result of encryption using blowfish is a change in the size of the message file caused by the size of the message file is less than the block cipher size, so additional bytes are given so that the message size matches the block cipher size. The speed of the encryption and decryption process using the blowfish algorithm results in an average time for encryption of 547.98ms while the average time for decryption is 538.19ms. The longest time for the encryption process is 557.30ms and the fastest is 534.50ms, while the longest time for the decryption process is 548.74ms and the fastest is 531.46ms. Hiding messages in audio files using LSB produces PSNR values above 30dB.
Decision Support Systems For Selection Of Pet Cat Using Preference Selection Index (PSI) & Multi-Objective Optimization On The Basis Of Ratio Analysis (MOORA) Methods Bunga Ayu Ferdiyanti; Yunita Yunita; Nabila Rizky Oktadini
Sriwijaya Journal of Informatics and Applications Vol 3, No 2 (2022)
Publisher : Fakultas Ilmu Komputer Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36706/sjia.v3i2.43

Abstract

In its evolution, cats have many variants that make adopters confused in determining the right choice. In the early stages of the search there are several common ways that adopters use, such as visiting websites on the internet, reading magazines or books, or directly coming to a pet store. The search process requires money, effort, and time. Therefore, in this final project was built a Decision Support System for Selection of Pet Cat using Preference Selection Index (PSI) & Multi-Objective Optimization On The Basis Of Ratio Analysis (MOORA) Methods which is expected to be able to help adopters to improve cost efficiency, energy and issued time. This system is expected to be able to provide recommendations for the type of pet cat according to the criteria and needs of the adopter. The criteria used include adoption costs, health, nature, weight, and treatment time. The basic concept of the two method is to calculate the weight of the criteria which is then multiplied by a normalized matrix and ranking. Based on the results of usability testing that applies the Technology Acceptance Model (TAM) theory by distributing questionnaire to 69 respondents, the results obtained are 0.92 with a VERY STRONG relationship level, so this system can be considered useful for users.

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