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.
Articles
564 Documents
<![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. Â 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[Watermarking Techniques Using Least Significant Bit Algorithm for Digital Image Security Standard Solution- Based Android ]]>
<![CDATA[Muzakir, Ari]]>;
<![CDATA[Habibi, Mailan]]>
<![CDATA[ Scientific Journal of Informatics Vol 4, No 1 (2017): May 2017 ]]>
Publisher : <![CDATA[Universitas Negeri Semarang ]]>
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DOI: 10.15294/sji.v4i1.7290
<![CDATA[Ease of deployment of digital image through the internet has positive and negative sides, especially for owners of the original digital image. The positive side of the ease of rapid deployment is the owner of that image deploys digital image files to various sites in the world address. While the downside is that if there is no copyright that serves as protector of the image it will be very easily recognized ownership by other parties. Watermarking is one solution to protect the copyright and know the results of the digital image. With Digital Image Watermarking, copyright resulting digital image will be protected through the insertion of additional information such as owner information and the authenticity of the digital image. The least significant bit (LSB) is one of the algorithm is simple and easy to understand. The results of the simulations carried out using android smartphone shows that the LSB watermarking technique is not able to be seen by naked human eye, meaning there is no significant difference in the image of the original files with images that have been inserted watermarking. The resulting image has dimensions of 640x480 with a bit depth of 32 bits. In addition, to determine the function of the ability of the device (smartphone) in processing the image using this application used black box testing. ]]>
<![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 userâs 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 userâs 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[Fuzzy Logic Inference System for Determining The Quality Assesment of Studentâs Learning ICT ]]>
<![CDATA[Pamuji, Agus]]>
<![CDATA[ Scientific Journal of Informatics Vol 4, No 1 (2017): May 2017 ]]>
Publisher : <![CDATA[Universitas Negeri Semarang ]]>
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DOI: 10.15294/sji.v4i1.7082
<![CDATA[The Assesment that held in the school is one of the learning process in education who do it by teacher. One of the course that exemined is Computer Application. In the computer application have 3 topic, they are Microsoft Word, Microsoft Excel, Microsoft Power Point. The assesment for studentâs at politecnic about learning computer application have 3 criteria in the selection. First of all, the students have ability to operate computer system generaly, it has understanding the formula on microsoft excel, the students have skill toward any application. In this study, fuzzy logic used for determining the quality assesment of stundentâs learning Information and Comunication Technology (ICT) as a tools to analyze any constraint that are known as min-max method. As a result, we have found that the students have good for analyzing in the application from the each question or case of study when the course it has been examined. ]]>
<![CDATA[An Identification of Tuberculosis (Tb) Disease in Humans using Naïve Bayesian Method ]]>
<![CDATA[Trihartati S., Agustin]]>;
<![CDATA[Adi, C. Kuntoro]]>
<![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.v3i2.7918
<![CDATA[Tuberculosis (TB) is a disease that can cause a death if not recognized or not treated properly. To reduce the death rate of tuberculosis patients, the health experts need to diagnose that disease as early as possible. Based on the main indication data, laboratory test results and the  rontgen photo, Naïve Bayesian approach in data mining techniques could be optimized to diagnose tuberculosis. Naïve Bayes classifiers predict class membership probabilities with a class that has the highest probability value. The output of the system is an identification Tuberculosis type of the patients. Testing of the system using 237 data sample with variation of cross-validation in 3, 5, 7 and 9-fold cross validation gives an average accuracy 85,95%.]]>
<![CDATA[Identification of Tuberculosis Patient Characteristics Using K-Means Clustering ]]>
<![CDATA[Sari, Betha Nur]]>
<![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.v3i2.7909
<![CDATA[In Indonesia, tuberculosis remains one of the major health problems unresolved. Indonesia is second ranked in the world as the country with the most tuberculosis cases. The purpose of this research is to study how K-means clustering applied to the treatment of tuberculosis patients data in order to identify the characteristics of tuberculosis patients. The results of K-means clustering validated by gene shaving and silhoutte coefficient. The experiment results indicate the optimum clusters value obtained from the K-mean clustering that has been validated by gene shaving and silhouette coefficient. K-means clustering divided four groups of tuberculosis patients based on their characteristics. There were divided at a category of disease (pulmonary TB, Extra Pulmonary TB and both), the age of the patient and the results of treatment of tuberculosis.]]>
<![CDATA[K-Medoid Algorithm in Clustering Student Scholarship Applicants ]]>
<![CDATA[Defiyanti, Sofi]]>;
<![CDATA[Jajuli, Mohamad]]>;
<![CDATA[Rohmawati, Nurul]]>
<![CDATA[ Scientific Journal of Informatics Vol 4, No 1 (2017): May 2017 ]]>
Publisher : <![CDATA[Universitas Negeri Semarang ]]>
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DOI: 10.15294/sji.v4i1.8212
<![CDATA[Data Grouping scholarship applicants Bantuan Belajar Mahasiswa (BBM) grouped into 3 categories entitled of students who are eligible to receive, be considered, and not eligible to receive scholarship. Grouping into 3 groups is useful to make it easier to determine the scholarship recipients fuel. K-Medoids algorithm is an algorithm of clustering techniques based partitions. This technique can group data is student scholarship applicants. The purpose of this study was to measure the performance of the algorithm, this measurement in view of the results of the cluster by calculating the value of purity (purity measure) of each cluster is generated. The data used in this research is data of students who apply for scholarships as many as 36 students. Data will be converted into three datasets with different formats, namely the partial codification attribute data, attributes and attribute the overall codification of the original data. Value purity on the whole dataset of data codification greatest value is 91.67%, it can be concluded that the K-Medoids algorithm is more suitable for use in a dataset with attributes encoded format overall. ]]>
<![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[Recognition Number of The Vehicle Plate Using Otsu Method and K-Nearest Neighbour Classification ]]>
<![CDATA[Hidayah, Maulidia Rahmah]]>;
<![CDATA[Akhlis, Isa]]>;
<![CDATA[Sugiharti, Endang]]>
<![CDATA[ Scientific Journal of Informatics Vol 4, No 1 (2017): May 2017 ]]>
Publisher : <![CDATA[Universitas Negeri Semarang ]]>
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DOI: 10.15294/sji.v4i1.9503
<![CDATA[The current topic that is interesting as a solution of the impact of public service improvement toward vehicle is License Plate Recognition (LPR), but it still needs to develop the research of LPR method. Some of the previous researchs showed that K-Nearest Neighbour (KNN) succeed in car license plate recognition. The Objectives of this research was to determine the implementation and accuracy of Otsu Method toward license plate recognition. The method of this research was Otsu method to extract the characteristics and image of the plate into binary image and KNN as recognition classification method of each character. The development of the license plate recognition program by using Otsu method and classification of KNN is following the steps of pattern recognition, such as input and sensing, pre-processing, extraction feature Otsu method binary, segmentation, KNN classification method and post-processing by calculating the level of accuracy. The study showed that this program can recognize by 82% from 100 test plate with 93,75% of number recognition accuracy and 91,92% of letter recognition accuracy. ]]>
