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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 564 Documents
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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*.
Pencarian File Teks Berbasis Content dengan Pencocokan String Menggunakan Algoritma Brute force Danuri, Danuri
Scientific Journal of Informatics Vol 3, No 1 (2016): May 2016
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v3i1.6515

Abstract

Keberadaan file menjadi penting saat dibutuhkan dan menjadi permasalahan apabila tidak ditemukan. Nama dari suatu file belum tentu memberikan gambaran isi yang terkandung pada file. Ini yang menjadi dasar dalam pencarian file berbasis konten. Terdapat beberapa algoritma untuk menyelesaikan permasalahan tersebut diantaranya algoritma brute force. Pengembangan algoritma pencarian dengan menciptakan pencarian lokal dan global memberikan kesempatan setiap kata pada file dan file pada lokasi yang dicari dapat diperiksa. Hasil pengujian menunjukkan rata-rata waktu proses 1 file sebesar 0.003847 detik dari 120 kali percobaan. Semakin banyak jumlah kata dalam suatu file dan jumlah file dalam satu tempat penyimpanan menyebabkan kebutuhan waktu semakin meningkat.
Autocomplete and Spell Checking Levenshtein Distance Algorithm To Getting Text Suggest Error Data Searching In Library Yulianto, Muhamad Maulana; Arifudin, Riza; Alamsyah, Alamsyah
Scientific Journal of Informatics Vol 5, No 1 (2018): May 2018
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v5i1.14148

Abstract

Nowadays internet technology provide more convenience for searching information on a daily. Users are allowed to find and publish their resources on the internet using search engine. Search engine is a computer program designed to facilitate a user to find the information or data that they need. Search engines generally find the data based on keywords they entered, therefore a lot of case when the user can’t find the data that they need because there are an error while entering a keyword. Thats why a search engine with the ability to detect the entered words is required so the error can be avoided while we search the data. The feature that used to provide the text suggestion is autocomplete and spell checking using Levenshtein distance algorithm. The purpose of this research is to apply the autocomplete feature and spell checking with Levenshtein distance algorithm to get text suggestion in an error data searching in library and determine the level of accuracy on data search trials. This research using 1155 data obtained from UNNES Library. The variables are the input process and the classification of books. The accuracy of Levenshtein algorithm is 86% based on 1055 source case and 100 target case.
High School Major Classification towards University Students Variable of Score Using Nave Bayes Algorithm Sudibyo, Usman; Astuti, Yani Parti; Kurniawan, Achmad Wahid
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.v4i2.12017

Abstract

Completeness of data in each institution, such as major in a university, is necessary. Data of former school has important role in the need of students data. However, there is no relationship between data of former school and variable of students score. The suitable classification used in this research is data mining technique which is nave bayes algorithm. This algorithm is able to manage massive data with a relative fast timing. By using this algorithm, the data results 64.77% performances in classifying former major in school towards variable of score. Hence, the researchers optimize selection feature by using Backward Elimination and result 71.71% performances data. It concludes that performance increases with selection feature. The increasing shows that not all variable of score affects the former school major.
Algorithm for Identifying Objects in The Relief Image Using Watershed Segmentation Auliasari, Karina; Orisa, Mira
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.v4i2.11177

Abstract

This study aims to automate the process of understanding temple relief, despite the difficulties to analyze the contents of natural images. Three preprocessing stages are develop in this research namely edge detection based on convolution (EC), edge detection based on gaussian (EG) and Hybrid which is a combination between edge detection based on convolution and gaussian. These algorithm is to support the operation of Watershed transform to segment relief images. A set of relief images obtained from several temples near Malang City are used in this experiment. Two experimental parameter are develop in order to measure the performance of these algorithm, namely number of object and quality of retrieval from segmentation result. The result of experiment show that hybrid approach deliver the best performances compare the other approaches.
Usability Laman Penerimaan Mahasiswa Baru UNNES Hardyanto, Wahyu; Adhi, Aryono; Purwinarko, Aji
Scientific Journal of Informatics Vol 3, No 1 (2016): May 2016
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v3i1.4611

Abstract

Salah satu jalur penjaringan mahasiswa baru Universitas Negeri Semarang (UNNES) adalah melalui Seleksi Nasional Masuk Perguruan Tinggi Negeri (SNMPTN). Mekanisme seleksi melalui SNMPTN didesain dengan berbagai kemudahan karena berbasis laman yaitu melalui http://penerimaan.unnes.ac.id. Terdapat fenomena yang menarik terkait dengan kecenderungan jumlah pendaftar mahasiswa baru UNNES yang perlu diteliti menyangkut usability laman http://penerimaan.unnes.ac.id/. Hasil analisis data peminat SNMPTN dan SPMU UNNES selama lima periode terakhir terhadap jumlah mahasiswa yang diterima memperlihatkan jumlah penerimaan mahasiswa UNNES lebih besar berasal dari peminat SPMU dibandingkan dengan peminat SNMPTN. Hal tersebut menunjukkan usability laman http://penerimaan.unnes.ac.id/ optimal.
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 11 of 57 | Total Record : 564

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