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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 26 Documents
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Search results for , issue "Vol 4, No 2 (2017): November 2017" : 26 Documents clear
An Evaluation Model Using Perceived User Technology Organization Fit Variable for Evaluating the Success of Information Systems Muslimin, Imam; Hadi, Sasongko Pramono; Nugroho, Eko
Scientific Journal of Informatics Vol 4, No 2 (2017): November 2017
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v4i2.12012

Abstract

In the information systems field, the fit between the components of information systems is a topic that has attracted the attention of many researchers. Various concepts of the fit such as Task-Technology Fit (TTF), Fit between Individuals, Tasks, and Technology (FITT), and Human Organization Technology Fit (HOT-Fit) are proposed and studied in various studies. In those various concept, the fit is one of the keys to the successful implementation and acceptance of information systems. Through a study of relevant literature, this study proposes a model consisting of human, organization, and technology characteristics, and adds the Perceived User Technology Organization Fit (PUTOF) variable as the initiated variable that influences the intention to use. In subsequent research, this model can be tested quantitatively with case studies of the information system implementation in an organization.
Performance Appraisal of Seluma Districts Agricultural Extensionist with Fuzzy Simple Additive Weighting Method Suranti, Dewi; Ikhsan, Mohamad
Scientific Journal of Informatics Vol 4, No 2 (2017): November 2017
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v4i2.12016

Abstract

Measuring the performance of an agricultural extensionist is essential for future evaluation and monitoring. An appraisal of agricultural extensionist workers should be performed to determine the achievements achieved by each agricultural extensionist agent. For that according to Permentan 2013 every Agricultural organization is obliged to conduct agricultural extensionist performance appraisal. This study aims to measure the peformance of agricultural extensionist of Seluma Regency by using Fuzzy Simple Additive Weighting (FSAW) method because this method determines the weight value for each attribute, followed by a ranking process that will select the best alternative from a number. This study aims to apply Fuzzy Simple Additive Wighted in the assessment of agricultural extensionist performance in Seluma district and to know the performance of agricultural extensionist workers in organizing agricultural extensionist. The system built is expected to facilitate BP3K sukaraja in carrying out routine performance appraisal of extensionist worker who has been a constraint in carrying out the appraisal performance appraisal. This system can result in accurate assessment of the performance of extensionist workers in accordance with the programs and work plans that have been made and implemented by agricultural extensionist.
Expert System Diagnosis of Bowel Disease Using Case Based Reasoning with Nearest Neighbor Algorithm Vedayoko, Lucky Gagah; Sugiharti, Endang; Muslim, Much Aziz
Scientific Journal of Informatics Vol 4, No 2 (2017): November 2017
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v4i2.11770

Abstract

Expert System is a computer system that has been entered the base of knowledge and set of rules to solve problems like an expert. One method in the expert system is Case Based Reasoning. To strengthen the retrieve stage of this method, the Nearest Neighbor algorithm is used. Bowel is one of the digestive organs susceptible to disease. The purpose of this study is to implement expert systems using Case Based Reasoning with Nearest Neighbor algorithm in diagnosing bowel disease and determine the accuracy of the system. Data used in this research are 60 data, obtained from medical record RSUD dr. Soetrasno Rembang. Variables used are general symptoms and types of diseases. The level of system accuracy resulting from scenario are 40 data as source case,  and 20 data as target case  that is equal to 95%.
Implementation of Firebase Realtime Database to Track BRT Trans Semarang Wiratno, Andreas Ragil; Hastuti, Khafiizh
Scientific Journal of Informatics Vol 4, No 2 (2017): November 2017
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v4i2.10829

Abstract

Many application developed to help people get information about BRT (Bus Rapid Transit) Trans Semarang. However, the existing application felt less effective and unable to provide what user need. So we proposed a prototype of android based application which able to provide information about BRT Trans Semarang in an effective ways. The developed system contains two application, that is driver side application and user side application. The reason for using Firebase Realtime Databse is because of every data changes in database it will synchronize to the user automatically without waiting user to refresh or reload the application. Our proposed method is well designed and implemented and succeed to provides what user need which proved by a user acceptance test
Information Retrieval System for Determining The Title of Journal Trends in Indonesian Language Using TF-IDF and Na?ve Bayes Classifier Trihanto, Wandha Budhi; Arifudin, Riza; Muslim, Much Aziz
Scientific Journal of Informatics Vol 4, No 2 (2017): November 2017
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v4i2.11876

Abstract

The journal is known as one of the relevant serial literature that can support a researcher in doing his research. In it’s development journal has two formats that can be accessed by library users namely: printed format and digital format. Then from the number of published journals, not accompanied by the growing amount of information and knowledge that can be retrieved from these documents. The TF-IDF method is one of the fastest and most efficient text mining methods to extract useful words as the value of information from a document. This method combines two concepts of weight calculation that is the frequency of word appearance on a particular document and the inverse frequency of documents containing the word. Furthermore, data analysis of journal title is done by Naïve Bayes Classifier method. The purpose of the research is to build a website-based information retrieval system that can help to classify and define trends from Indonesian journal titles. This research produces a system that can be used to classify journal titles in Indonesian language, with system accuracy in determining the classification of 90,6% and 9,4% error rate. The highest percentage result that became the trend of title classification was decision support system category which was 24.7%.
Color Space to Detect Skin Image: The Procedure and Implication Endah, Sukmawati Nur; Kusumaningrum, Retno; Wibawa, Helmie Arif
Scientific Journal of Informatics Vol 4, No 2 (2017): November 2017
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v4i2.12013

Abstract

Skin detection is one of the processes to detect the presence of pornographic elements in an image. The most suitable feature for skin detection is the color feature. To be able to represent the skin color properly, it is needed to be processed in the appropriate color space. This study examines some color spaces to determine the most appropriate color space in detecting skin color. The color spaces in this case are RGB, HSV, HSL, YIQ, YUV, YCbCr, YPbPr, YDbDr,  CIE XYZ, CIE L*a*b*, CIE  L*u* v*, and CIE L*ch. Based on the test results using 400 image data consisting of 200 skin images and 200 non-skin images, it is obtained that the most appropriate color space to detect the color is CIE L*u*v*.

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