Scientific Journal of Informatics
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.
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<![CDATA[Decision Support Model for User Submission Approval Energy Partners Candidate Using Profile Matching Method and Analytical Hierarchy Process ]]>
<![CDATA[Moedjiono, Moedjiono]]>;
<![CDATA[Kurnianda, Nia Rahma]]>;
<![CDATA[Kusdaryono, Aries]]>
<![CDATA[ Scientific Journal of Informatics Vol 3, No 2 (2016): November 2016 ]]>
Publisher : <![CDATA[Universitas Negeri Semarang ]]>
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DOI: 10.15294/sji.v3i2.7916
<![CDATA[In the field of services, customer satisfaction is a very important factor and determine the success of an enterprise. In the field of outsourcing, customer satisfaction indicator is the labor required delivery in a timely manner and has a level of quality in accordance with the terms proposed by the customer. To provide the best talent to customers, team recruitment and selection must perform a series of tests with a variety of methods to match the criteria of office given by the user with the criteria owned candidates and in order to support growth in graduation rates force a partner at the stage of user approval. For this purpose, the authors conducted a study with the method of observation, interviews, document reviews the candidate recruitment process, so as to provide recommendations for candidates with the highest quality delivery to the user at the stage of approval. The author put forward a model of decision support that is supported by the method of profile matching and Analytical Hierarchy Process (AHP) in problem solving. The final results of this study can be used to support a decision in order to improve the effectiveness of the delivery of quality candidates, increase customer satisfaction, lower costs and improve gross operational margin of the company.]]>
<![CDATA[Assessment The Method of Fuzzy Logic to Determine The Quality of Service Expedition in Jabodetabek Area ]]>
<![CDATA[Pamuji, Agus]]>
<![CDATA[ Scientific Journal of Informatics Vol 3, No 2 (2016): November 2016 ]]>
Publisher : <![CDATA[Universitas Negeri Semarang ]]>
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DOI: 10.15294/sji.v3i2.7906
<![CDATA[Search application services that was designed, could be the based on the difficulty to find out, and to select expedition services which have provided. In these case, when someone who wants to send the packages to a particular destination. Each shipper will see the name of courier services, the speed the god arrive at the destination, prices, and customer services. This application is designed with fuzzy logic method that can be based on the selection of criteria, and specific category. The using and fuzzy logic method implementation can to help and ensure the selection of expedition service that based in variable or criteria are price, speed, location, and services. The result of this research will to display of application that was supported with database systems such as expedition services information and location, and then table of price is available.]]>
<![CDATA[The Implementation of Grey Forecasting Model for Forecast Results Food Crop Agricultural ]]>
<![CDATA[Muqtadir, Asfan]]>;
<![CDATA[Suryono, Suryono]]>;
<![CDATA[Gunawan, Vincensius]]>
<![CDATA[ Scientific Journal of Informatics Vol 3, No 2 (2016): November 2016 ]]>
Publisher : <![CDATA[Universitas Negeri Semarang ]]>
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DOI: 10.15294/sji.v3i2.7912
<![CDATA[The increasing of the needs of food crops raised several issues related to land use. The problems of land used caused by the lack of information related to productivity and eligibility used of land. The goal of this research is to implementation a model of Grey forecasting GM(1,1) to forecast agricultural production, especially in food crops. GM(1,1) is used to built a model with limited data samples and generate good forecasts for short libertine forecasts. This research uses data from the production of food crops for the 2004-2013 it can be calculated by using the model of GM (1,1). The results showed the model GM (1,1) can produce highly accurate forecasts, from the experimental results for pattern trends generate value ARPE 5.74% or accuracy of forecasts reached 94.26% in crop production.]]>
<![CDATA[COMPARISON OF PATTERNS SHAPES AND PATTERNS TEXTURE FOR IDENTIFICATION OF MALARIA PARASITES IN MICROSCOPIC IMAGE ]]>
<![CDATA[Kusanti, Jani]]>;
<![CDATA[Santosa, Yusuf Zain]]>
<![CDATA[ Scientific Journal of Informatics Vol 3, No 2 (2016): November 2016 ]]>
Publisher : <![CDATA[Universitas Negeri Semarang ]]>
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DOI: 10.15294/sji.v3i2.7917
<![CDATA[Identification of malaria parasites in red blood cells has been done, with the aim of as tools to identify experts microscopic parasites more quickly. This study aimed to compare the level of accuracy in the results to identify and classify parasites based on the pattern shape and texture patterns. The comparison is based on the characteristics of the pattern used, the steps being taken in this study is the image quality improvement process, the process of segmentation with Otsu method, feature extraction process on the image data to be tested. The process of pattern recognition and pattern shapes texture. The last step is to test the identification and classification of plasmodium falciparum parasite into 12 classes using methods Learning Vector Quantization (LVQ). The results of this study indicate that the pattern forms can provide a higher level of accuracy compared to LVQ texture pattern. LVQ with input shape pattern successfully identified 91% of image data correctly and input texture successfully identified 48% of image data properly.]]>
<![CDATA[DECISION SUPPORT SYSTEMS WITH AHP AND SAW METHOD FOR DETERMINATION OF CATTLE WITH SUPERIOR SEEDS ]]>
<![CDATA[Josaputri, Clarissa Amanda]]>;
<![CDATA[Sugiharti, Endang]]>;
<![CDATA[Arifudin, Riza]]>
<![CDATA[ Scientific Journal of Informatics Vol 3, No 2 (2016): November 2016 ]]>
Publisher : <![CDATA[Universitas Negeri Semarang ]]>
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DOI: 10.15294/sji.v3i2.7908
<![CDATA[Department of Animal Husbandry and Fisheries of Semarang District is an institution in charge of livestock and animal health. Basically the Animal Husbandry Department has provided standardization for quality livestock cattle with superior seeds that usually can be judged or measured by various criteria.They are weight, age and value of BCS (Body Condition Score).They needed a system that could help the Department of Livestock and Fisheries of Semarang District in determining the electoral process cattle with superior seeds. In this research, the manufacture of Decision Support Systems in the determination cattle with superior seedsis using a combination of two methods is Analytical Hierarchy Process (AHP) and the Simple Addictive Weighting (SAW). In AHP will perform an importance value calculation criteria that will be paired up with an alternative to the SAW the next process is the sum of the weight from performance rating of all the attributes to each alternative, a ranking conducted to determine the result of cattle with superior seeds. Suggestions on this system, can be developed further by combining other methods to determine the recommendation that more effective.]]>
<![CDATA[DECISION SUPPORT SYSTEM TO CHOOSE DIGITAL SINGLE LENS CAMERA WITH SIMPLE ADDITIVE WEIGHTING METHOD ]]>
<![CDATA[Putri, Tri Pina]]>;
<![CDATA[Rosa, Paulina H. Prima]]>
<![CDATA[ Scientific Journal of Informatics Vol 3, No 2 (2016): November 2016 ]]>
Publisher : <![CDATA[Universitas Negeri Semarang ]]>
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DOI: 10.15294/sji.v3i2.7913
<![CDATA[One of the technologies that evolve today is Digital Single Lens Reflex (DSLR) camera. The number of products makes users have difficulties to choose the appropriate camera based on their criteria. Users may utilize several ways to help them choosing the intended camera such as using magazine, internet, and other media. This paper discusses about a web based decision support system to choose cameras by using SAW (Simple Additive Weighting) method in order to make the decision process more effective and efficient. This system is expected to give recommendations about the camera which is appropriate with the users need and criteria based on the cost, the resolution, the feature, the ISO, and the censor. The system was implemented by using PHP and MySQL. Based on the result of questionnaire distributed to 20 respondents, 60% respondents agree that this decision support system can help users to choose the appropriate camera DSLR in accordance with the users need, 60% of respondents agree that this decision support system is more effective to choose DSLR camera and 75% of respondents agree that this system is more efficient. In addition, 60.55% of respondents agree that this system has met 5 Es Usability Framework.]]>
<![CDATA[Expert System for Determination of Type Lenses Glasses Using Forward Chaining Method ]]>
<![CDATA[Pramesti, Atikah Ari]]>;
<![CDATA[Arifudin, Riza]]>;
<![CDATA[Sugiharti, Endang]]>
<![CDATA[ Scientific Journal of Informatics Vol 3, No 2 (2016): November 2016 ]]>
Publisher : <![CDATA[Universitas Negeri Semarang ]]>
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DOI: 10.15294/sji.v3i2.7914
<![CDATA[One of the branches of computer science that is widely used by humans to help her work is the establishment of an expert system. In this study we will design an expert system for determining the type of spectacle lenses using a forward chaining method. In forward chaining method, starting with the initial information (early symptoms) and moved forward to fit more information to find the information in accordance with the rules of the knowledge base and production, and will be concluded in the form of the type of disorder diagnosis of eye disorders and provide solutions in the form of lenses of eyeglasses. Result from this study is that the match calculation of algorithm of forward chaining method between system and manual calculations produce the same output.]]>
<![CDATA[Performance Test of Openflow Agent on Openflow Software-Based Mikrotik RB750 Switch ]]>
<![CDATA[Kartadie, Rikie]]>
<![CDATA[ Scientific Journal of Informatics Vol 3, No 2 (2016): November 2016 ]]>
Publisher : <![CDATA[Universitas Negeri Semarang ]]>
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DOI: 10.15294/sji.v3i2.7987
<![CDATA[A network is usually developed by several devices such as router, switch etc. Every device forwards data package manipulation with complicated protocol planted in its hardware. An operator is responsible for running configuration either to manage rules or application applied in the network. Human error may occur when device configuration run manually by operator. Some famous vendors, one of them is MikroTik, has also been implementing this OpenFlow on its operation. It provides the implementation of SDN/OpenFlow architecture with affordable cost. The second phase research result showed that switch OF software-based MikroTik resulted higher latency value than both mininet and switch OF software-based OpenWRT. The average gap value of switch OF software-based MikroTik is 2012 kbps lower than the value of switch OF software-based OpenWRT. The average gap value of throughput bandwidth protocol UDP switch OF software-based MikroTik is 3.6176 kBps lower than switch OF software-based OpenWRT and it is 8.68 kBps lower than mininet. The average gap throughput jitter protokol UDP of switch OF software-based MiktoTik is 0.0103ms lower than switch OF software-based OpenWRT and 0.0093ms lower than mininet. ]]>
<![CDATA[The Effect of Best First and Spreadsubsample on Selection of a Feature Wrapper With Naïve Bayes Classifier for The Classification of the Ratio of Inpatients ]]>
<![CDATA[Wijaya, M Rizky]]>;
<![CDATA[Saptono, Ristu]]>;
<![CDATA[Doewes, Afrizal]]>
<![CDATA[ Scientific Journal of Informatics Vol 3, No 2 (2016): November 2016 ]]>
Publisher : <![CDATA[Universitas Negeri Semarang ]]>
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DOI: 10.15294/sji.v3i2.7910
<![CDATA[Diabetes can lead to mortality and disability, so patients should be inpatient again to undergo treatment again to be saved. On previous research about feature selection with greedy stepwise forward fail to predict classification ratio inpatient of patient with the result of recall and precision 0 on data training 60%, 75%, 80%, and 90% and there is suggestion to handle unbalanced class data problem by comparison of data readmitted 6293 and the otherwise 64141. The research purposed to know the effect of choosing the best model using best first instead of greedy stepwise forward and data sampling with spreadsubsample to resolve unbalanced class data problem. The data used was patient data from 130 American Hospital in 1999 until 2008 with 70434 data. The method that used was best first search and spreadsubsample. The result of this research are precision found 0.4 and 0.333 on training dataset 75% and 90% with best first method, while spreadsubsample method found that value of precision and recall is more significantly increased. Spreadsubsample has more effect with the result of precision and recall rather than using best first method.]]>
<![CDATA[Model of Multilevel Sub-Image to Find the Position of Region of Interest ]]>
<![CDATA[Hartono, Budi]]>;
<![CDATA[Lusiana, Veronica]]>
<![CDATA[ Scientific Journal of Informatics Vol 3, No 2 (2016): November 2016 ]]>
Publisher : <![CDATA[Universitas Negeri Semarang ]]>
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DOI: 10.15294/sji.v3i2.7915
<![CDATA[Searching image is based on the image content, which is often called with searching of image object. If the image data has similarity object with query image then it is expected the searching process can recognize it. The position of the image object that contains an object, which is similar to the query image, is possible can be found at any positionon image data so that will become main attention or the region of interest (ROI). This image object can has different wide image, which is wider or smaller than the object on the query image. This research uses two kinds of image data sizes that are in size of 512X512 and in size of 256X256 pixels.Through experimental result is obtained that preparing model of multilevel sub-image and resize that has same size with query image that is in size of 128X128 pixels can help to find ROI position on image data. In order to find the image data that is similar to the query image then it is done by calculating Euclidean distance between query image feature and image data feature.]]>
