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Scientific Journal of Informatics
Published by Universitas Negeri Semarang
ISSN : 24077658     EISSN : 24600040     DOI : -
Core Subject : Science,
Computer Science & IT
Scientific Journal of Informatics published by the Department of Computer Science, Semarang State University, a scientific journal of Information Systems and Information Technology which includes scholarly writings on pure research and applied research in the field of information systems and information technology as well as a review-general review of the development of the theory, methods, and related applied sciences.
Arjuna Subject : -
Articles 36 Documents
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Search results for , issue "Vol 5, No 2 (2018): November 2018" : 36 Documents clear
Push-Up Detector Applications Using Quality Function Development and Anthropometry for Movement Error Detection Muzakir, Ari; Kusmindari, Christofora Desi
Scientific Journal of Informatics Vol 5, No 2 (2018): November 2018
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v5i2.16332

Abstract

Push-up is the simplest and most widely performed sport. Although simple, it also has a high risk of injury risk if done not in accordance with the rules. Push-up detector is a good push-up motion monitoring solution. In this way, nonstandard movements can be detected and corrected immediately. It has two motion sensors integrated with Arduino-based microcontroller. From this detector tool got the data of push-up result from sensor mounted. Sensor data will be displayed in the application in real-time. Quality function development is used to determine the criteria of the user. The sample data involved 200 participants who followed the testing of this tool and got 90% who can do the push-up correctly. Factors that affect the height, age, and weight. Tests conducted on adolescent boys aged 18-23 years. The results of this study is an application capable of monitoring each push-up movement to position in accordance with the provisions to minimize injuries resulting from movement errors.
Use of K-Means Clustering and Analytical Methods Hierarchy Process in Determining the Type of MSME Financing in Semarang City Sukmadewanti, Irahayu; Arifudin, Riza; Sugiharti, Endang
Scientific Journal of Informatics Vol 5, No 2 (2018): November 2018
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v5i2.16221

Abstract

The Indonesian government launched an entrepreneurial program to encourage economic growth, one of which is MSME(micro, small and medium enterprises). The constraints commonly faced by MSME are limited enterprises capital. The government has also tried to provide assistance financing for MSMEs in the form of CSR (Corporate Social Responsibility), KUR (Credit People's Enterprises) and KTA (Unsecured Credit). For this type of financing or credit determined based on the type of enterprises accompanied by criteria including number of assets, turnover annually, number of employees, current enterprises period and net income. Based on background behind this research aims to help provide recommendations on types MSME capital financing based on assets, turnover, number of employees, enterprises period and net income of a MSME. This research uses data from MSME in the Semarang City, which has been registered with the Semarang City Cooperatives and MSME Office. K-Means Clustering Method is used to cluster net profit criteria. Then the Analytical Hierarchy Process (AHP) method is used to search recommendations on the types of MSME financing based on each weighted criteria. The results of this application are recommendations for types of capital financing MSME is based on assets, turnover, number of employees, enterprises period and every net profit of MSME. For testing of the system being built, it is carried out by means of a blackbox test. From the test results obtained show that the actual results are appropriate with the expected results so that the functional system is running well. Suggestions from this research, it is necessary to develop further systems regarding grouping data to be more specific.
Comparative Analysis of Certainty Factor Method and Bayes Probability Method on ENT Disease Expert System Setyaputri, Khairina Eka; Fadlil, Abdul; Sunardi, Sunardi
Scientific Journal of Informatics Vol 5, No 2 (2018): November 2018
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v5i2.16151

Abstract

Expert system is computer programs that mimic the thought process and expert knowledge in solving a particular problem. Basically, an expert system has various methods to diagnose various kinds of diseases experienced by humans, animals, and plants. This research analyzes the comparison of Certainty Factor method and Bayes Probability method in the expert system of Ear, Nose, and Throat (ENT) diseases. Both methods have the same basic theory of overcoming uncertainties with existing variables. The Certainty Factor method has many variables that are used as systematic knowledge, namely the weight value of the expert which is the basis of knowledge of the system and the user input weight value, while the Bayes Probability method uses only expert knowledge in the calculation. Based on a comparative analysis of the methods obtained with 10 patients data on the ENT disease expert system, the Certainty Factor method has accuracy in diagnosing the disease by 100%, while the Probability Bayes method of system accuracy is 80%. So it can be concluded that the Certainty Factor method is more accurate in diagnosing ENT than the Bayes Probability method.
Cryptography Triple Data Encryption Standard (3DES) for Digital Image Security Atika Sari, Christy; Rachmawanto, Eko Hari; Haryanto, Christanto Antonius
Scientific Journal of Informatics Vol 5, No 2 (2018): November 2018
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v5i2.14844

Abstract

Advances in technology in the field of internet, making the Internet become the most popular data transmission media for now. This is certainly not free from the incidence of cyber crime, such as theft and data modification. Given the losses caused by data manipulation is very detrimental to the owner, then the original data can be misused in the cyber world. Cryptography offers an algorithm for randomizing data, so it can not be read by unauthorized people. The cryptography technique was implemented using Triple Data Encyption Standard (3DES) given the results of a randomized cryptographic algorithm, it is possible to arouse suspicion from the viewer. For that will be done the process of insertion of cryptographic files into another media in the form of images commonly referred to as steganography. The steganography technique that will be used is End of File (EOF). The combination of 3DES and EOF in the 64x64 pixel image with grayscale color format produces the fastest image processing time of 173.00192 seconds with the highest Peak Signal to Noise Ratio (PSNR) value of 25.0004 dB, while in the 128x128 pixel image with grayscale format has produced the highest PSNR 21.0084 dB.
Automatic License Plate Recognition: A Review with Indonesian Case Study Budianto, Aris
Scientific Journal of Informatics Vol 5, No 2 (2018): November 2018
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v5i2.15804

Abstract

The Automatic License Plate Recognition (ALPR) has been becoming a new trend in transportation systems automation. The extraction of vehicle’s license plate can be done without human intervention. Despite such technology has been widely adopted in developed countries, developing countries remain a far-cry from implementing the sophisticated image and video recognition for some reasons. This paper discusses the challenges and possibilities of implementing Automatic License Plate Recognition within Indonesia’s circumstances. Previous knowledge suggested in the literature, and state of the art of the automatic recognition technology is amassed for consideration in future research and practice.
The Comparison between Bayes and Certainty Factor Method of Expert System in Early Diagnosis of Dengue Infection Rachmawati, Eka Yuni; Prasetiyo, Budi; Arifudin, Riza
Scientific Journal of Informatics Vol 5, No 2 (2018): November 2018
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v5i2.15740

Abstract

The development of existing artificial intelligence technology has been widely applied in detecting diseases using expert systems. Dengue Infection is one of the diseases that is commonly suffered by the community and may cause in death. In this study, an expert diagnosis system for dengue infection is made by comparing between both Bayes method and Certainty Factor. The aims are to build an expert system using Bayes and Certainty Factor for early diagnosis of dengue infection and also to determine their level of accuracy. There are 80 data used in this study which are obtained from the medical records of Sekaran Health Center in Semarang City. The test results show that the level of accuracy obtained from 80 medical record data for Bayes method is 90% and the Certainty Factor method is 93,75%.

Page 4 of 4 | Total Record : 36

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