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INDONESIA
Jurnal Informatika
Published by Universitas Ahmad Dahlan
ISSN : 19780524     EISSN : 25286374     DOI : 10.26555
Core Subject : Science,
Computer Science & IT
Arjuna Subject : -
Articles 5 Documents
 1 
Search results for , issue "Vol 12, No 2: July 2018" : 5 Documents clear
Vulnerability of injection attacks against the application security of framework based websites open web access security project (OWASP) Imam Riadi; Rusydi Umar; Wasito Sukarno
Jurnal Informatika Vol 12, No 2: July 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (272.384 KB) | DOI: 10.26555/jifo.v12i2.a8292

Abstract

The development of website applications is currently growing rapidly, but it is not followed by a good security system that can cause the number of security holes that can be entered by the attacker. The number of website applications that are vulnerable to injection attacks to make managers must be aware of and often update and immediately close the security gap. Website applications that have good security will become more secure but the application is still vulnerable to injection attacks. Updating and changing passwords periodically will be better than in fix. Many security hints and risks are released by Open Web Application Security Project (OWASP) TOP 10-2017 as well as a reference in wary of security risks in the application.
Combination and comparison of AES and RC4 cryptography in least significant bit (LSB) method in digital image to improve message security Rahmat Sulaiman
Jurnal Informatika Vol 12, No 2: July 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jifo.v12i2.a8667

Abstract

Message security is something that must be kept secretly. However, to maintain the security and the secret of a message it takes two different methods. To maintain the security of messages, the science that has been widely used is to use cryptography. As for maintaining the secret of the message, the science used is steganography. For that, we need a security message that can maintain the security and the secret of the message simultaneously. Various algorithms have been widely applied in data security, but it is unknown which algorithm has a superior speed when applied in the LSB. The test is done by calculating the length of the encryption time process and the decryption time process of each algorithm with the same number of messages and key lengths. Measurement time is done as much as 10 times, then taken average value to get consistent time because system instability. Therefore, we will compare the speed of encryption and decryption process by applying AES and RC4 algorithm to LSB in Visual Studio 2008. In the process of encryption and decryption, the AES algorithm is superior in terms of speed compared to RC4 algorithm. The MSE and PSNR values generated from the encrypted images based on the AES and RC4 algorithm doesn’t show significant value. Overall the AES algorithm is better than RC4 algorithm when applied in LSB.
Analysis of factors affecting the area of forest and land fires in Indonesia uses spatial regression Geoda and SaTScan Tuti Purwaningsih; Alya Cintami
Jurnal Informatika Vol 12, No 2: July 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1331.898 KB) | DOI: 10.26555/jifo.v12i2.a12340

Abstract

This study discusses the factors that influence the extent of forest and land fires in Indonesia that relate several other factors such as rain, fire events, and wind speed which were the events during 2015. Forest fires are one of the environmental and forest problems that is a local and global concern. Countermeasures have been carried out for a long time but are relatively low. By looking for the best regression model with a significance level of 0.05 or 95% using the Spatial Autoregressive Model (SAR) method, the coefficient of determination of 25.00% is obtained which can be obtained by the research regression model and leaves 75.00% needed by other variables that are variables changed
Recommendation system for web article based on association rules and topic modelling Guntur Budi Herwanto; Annisa Maulida Ningtyas
Jurnal Informatika Vol 12, No 2: July 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jifo.v12i2.a12629

Abstract

The World Wide Web is now the primary source for information discovery. A user visits websites that provide information and browse on the particular information in ac-cordance with their topic interest. Through the navigational process, visitors often had to jump over the menu to find the right content. Recommendation system can help the visitors to find the right content immediately. In this study, we propose a two-level recommendation system, based on association rule and topic similarity. We generate association rule by applying Apriori algorithm. The dataset for association rule mining is a session of topics that made by combining the result of sessionization and topic modeling. On the other hand, the topic similarity made by comparing the topic proportion of web article. This topic proportion inferred from the Latent Dirichlet Allocation (LDA). The results show that in our dataset there are not many interesting topic relations in one session. This result can be resolved, by utilizing the second level of recommendation by looking into the article that has the similar topic.
Facial recognition using deep learning Abdulrazak Yahya Saleh; Kirthanaa A/P Jiva Rattinami
Jurnal Informatika Vol 12, No 2: July 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (519.153 KB) | DOI: 10.26555/jifo.v12i2.a12742

Abstract

In this article, the researcher presented the results of recognition of four emotional states (happy, sad, angry, and disgust) based on facial expressions. A deep learning method with a Convolutional Neural Network algorithm for recognizing problems has been proven very effective way to overcome the recognition problem. A comparative study is carried out using MUAD3D dataset from Faculty of Computer Science and Information Technology, Universiti Malaysia Sarawak for evaluating accuracy performance of this dataset. More discussion is provided to prove the effectiveness of the Convolutional Neural Network in recognition problems.

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