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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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Associative Analysis Data Mining Pattern Against Traffic Accidents Using Apriori Algorithm Ruswati, Ruswati; Gufroni, Acep Irham; Rianto, Rianto
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.v5i2.16199

Abstract

Traffic accidents are one of the causes of high mortality in the community. Based on information from the World Health Organization (WHO) the number of accident victims in each year amounts to 1,300,000 fatalities, this is caused by traffic accidents that exist throughout the world. The police recorded data on accidents that occurred in several regions of East Priangan namely Ciamis and Tasikmalaya Regencies for the 2016-2017 period reaching an accident rate of ± 1500. The analysis that can be done to reduce the intensity of the occurrence of these events is to use data mining processing techniques. The right method is used by looking at the condition of the data obtained, namely the Association Rules method with the calculation of the Apriori Algorithm. This method will look for patterns of data relations that are formed from combinations of an itemset, so that knowledge will appear from large datasets. The pattern of the relationship sought is the linkages of itemset variables involved in the accident by involving 4 variables that describe the identity of the perpetrators, namely gender, age, profession and level of education and 22 attributes of the dataset. The minimum limit of support, confidence and lift ratio values used in the Apriori Algorithm calculation rules is 15%, 70% and 1.1. This value is used to get many rules that have a high level of occurrence accuracy. The results of the combination pattern calculation were 3 times iterations on each number of data in each region, the pattern of associations found in the Tasikmalaya region were the relation of the professional variables and the age of the perpetrator with the attribute of the Student profession dataset and the boundary group ages 16 to 30 years, while for the pattern associations found in the area of Ciamis Regency, namely the relation between age and education level with the attribute dataset of the 16 to 30 year age group and high school education level. The accuracy of the value obtained is calculated manually and uses one of the data mining applications as a comparison of value accuracy, namely Tanagra 1.4.
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 Peoples 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.
Digital Evidence Identification on Google Drive in Android Device Using NIST Mobile Forensic Method Yudhana, Anton; Umar, Rusydi; Ahmadi, Ahwan
Scientific Journal of Informatics Vol 6, No 1 (2019): Mei 2019
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v6i1.17767

Abstract

The use of cloud storage media is very popular nowadays, especially with the Google Drive cloud storage media on smartphones. The increasing number of users of google drive storage media does not rule out the possibility of being used as a medium for storing illegal data, such as places to store negative content and so on. On a smartphone with an Android operating system that has a Google Drive application installed, digital evidence can be extracted by acquiring and analyzing the system files. This study implemented a mobile forensic method based on guidelines issued by the National Institute of Standards of Technology (NIST). The results of this study are presented in the form of data recovery in the deleted Google Drive storage media, which results in the form of headers of the data type in the form of deleting account names, deleted file types, and timestamp of deleted files. Digital evidence obtained with 59 Axiom Magnet software found in the Entry227 file, with 46 files, if the percentage is a success rate of 77%.
Decision Support System for Household Labor Services Selection “Best Helper” Using AHP and TOPSIS Methods Pirnanda, I Kadek Aditya; Pradnyana, I Made Ardwi; Wirawan, I Made Agus
Scientific Journal of Informatics Vol 6, No 1 (2019): Mei 2019
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v6i1.18050

Abstract

Selection of household labor services was an important aspect in families who have a lot of activity. The existence of helpful household labour services would avoid the occurrence of problems that should be caused. Types of household labour services which were often used were maids, baby sitters, elderly nurses, gardeners, and drivers. The main problem arose in the difficulty of service seekers in choosing the desired service and how to minimize the time spent. To overcome this, a decision support system was used using the Analytical Hierarchy Process (AHP) method which was used to find the criteria for each alternative weight, and ranking calculations using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method. This research was implemented using PHP language with CodeIgniter framework. The result shows that the usability test obtains the average value with the system usability scale (SUS) method of 71.09%. It shows that the level of system usability is classified as good and can be accepted and used easily by the users. Meanwhile, the result of the user response test shows a percentage of 87.5%, so it can be concluded that the system belongs to good category and feasible to use.
Comparative Analysis of Dempster-Shafer Method and Certainty Factor Method On Personality Disorders Expert Systems Yuwono, Doddy Teguh; Fadlil, Abdul; Sunardi, Sunardi
Scientific Journal of Informatics Vol 6, No 1 (2019): Mei 2019
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v6i1.17216

Abstract

Kepribadian adalah sifat dan kebiasaan seseorang yang membedakannya dari orang lain. Identifikasi gangguan kepribadian penting untuk semua orang. Kondisi kepribadian yang mencerminkan kondisi mental yang sehat. Namun, tidak bagi manusia untuk tidak bisa menerima tekanan pada diri sendiri. Dalam beberapa kasus, banyak orang ingin melakukan pengujian dengan sumber daya yang cukup dan verifikasi yang sesuai. Untuk mengatasinya, diperlukan tes validasi untuk metode deteksi cacat. Metode yang mendukung validasi adalah Metode Dempster-Shafer dengan Metode Faktor Kepastian.Analisis validasi dilakukan pada metode Dempster-Shafer dengan metode Certainty Factor karena menimbang nilai kerusakan kedua metode ini diperlukan dari data hipotesis atau perubahan dalam bentuk data simptom. Analisis validasi dilakukan pada nilai bobot yang dihasilkan untuk setiap metode yang diterapkan. Dari hasil analisis validasi, nilai bobot yang diperoleh dengan metode Demp-ster-Shafer dapat menghasilkan nilai bobot yang lebih akurat.
Comparison of PCA and 2DPCA Accuracy with K-Nearest Neighbor Classification in Face Image Recognition Sutarti, Sri; Putra, Anggyi Trisnawan; Sugiharti, Endang
Scientific Journal of Informatics Vol 6, No 1 (2019): Mei 2019
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v6i1.18553

Abstract

Face recognition is a special pattern recognition for faces that compare input image with data in database. The image has a variety and has large dimensions, so that dimension reduction is needed, one of them is Principal Component Analysis (PCA) method. Dimensional transformation on image causes vector space dimension of image become large. At present, a feature extraction technique called Two-Dimensional Principal Component Analysis (2DPCA) is proposed to overcome weakness of PCA. Classification process in 2DPCA using K-Nearest Neighbor (KNN) method by counting euclidean distance. In PCA method, face matrix is changed into one-dimensional matrix to get covariance matrix. While in 2DPCA, covariance matrix is directly obtained from face image matrix. In this research, we conducted 4 trials with different amount of training data and testing data, where data is taken from AT&T database. In 4 time testing, accuracy of 2DPCA+KNN method is higher than PCA+KNN method. Highest accuracy of 2DPCA+KNN method was obtained in 4th test with 96.88%. while the highest accuracy of PCA+KNN method was obtained in 4th test with 89.38%. More images used as training data compared to testing data, then the accuracy value tends to be greater.
Bayes Theorem and Forward Chaining Method On Expert System for Determine Hypercholesterolemia Drugs Perbawawati, Anna Adi; Sugiharti, Endang; Muslim, Much Aziz
Scientific Journal of Informatics Vol 6, No 1 (2019): Mei 2019
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v6i1.14149

Abstract

The development of technology capable to imitating the process of human thinking  and led to a new branch of computer science named the expert system. One of the problem that can be solved by an expert system is selecting hypercholesterolemia drugs.  Drug selection starts from find the symptoms and then determine the best drug for the patient. This is consist with the mechanism of forward chaining which starts from searching for information about the symptoms, and then try to illustrate the conclusions. To accommodate the missing fact, expert systems can be complemented with the Bayes theorem that provides a simple rule for calculating the conditional probability so the accuracy of the method approaches the accuracy of the experts. This reseacrh uses 30 training data and 76 testing data of medical record that use hypercholesterolemia drugs from Tugurejo Hospital of Semarang. The variable are common symptoms and some hypercholesterolemia drugs. This research obtained a selection of hypercholesterolemia drugs system with 96.05% accuracy
Dataset Characteristics Identification for Federated SPARQL Query Rakhmawati, Nur Aini; Fadzilah, Lutfi Nur
Scientific Journal of Informatics Vol 6, No 1 (2019): Mei 2019
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v6i1.17258

Abstract

Nowadays, the amount of data published in the RDF format is increasing. Federated SPARQL query engines that can query from multiple distributed SPARQL endpoints have been developed recently. A federated query engine usually has different performance compared to the others. One of the factors that affect the performance of the query engine is the characteristic of the accessed RDF dataset, such as the number of triples, the number of classes, the number of properties, the number of subjects, the number of entities, the number of objects, and the spreading factor of a dataset. The aim of this work is to identify the characteristic of RDF dataset and create a query set for evaluating a federated engine.  The study was conducted by identifying 16 datasets that used by ten research papers in Linked Data area.
Compression and Decompression of Audio Files Using the Arithmetic Coding Method Silitonga, Parasian D. P; Morina, Irene Sri
Scientific Journal of Informatics Vol 6, No 1 (2019): Mei 2019
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v6i1.17839

Abstract

Audio file size is relatively larger when compared to files with text format. Large files can cause various obstacles in the form of large space requirements for storage and a long enough time in the shipping process. File compression is one solution that can be done to overcome the problem of large file sizes. Arithmetic coding is one algorithm that can be used to compress audio files. The arithmetic coding algorithm encodes the audio file and changes one row of input symbols with a floating point number and obtains the output of the encoding in the form of a number of values greater than 0 and smaller than 1. The process of compression and decompression of audio files in this study is done against several wave files. Wave files are standard audio file formats developed by Microsoft and IBM that are stored using PCM (Pulse Code Modulation) coding. The wave file compression ratio obtained in this study was 16.12 percent with an average compression process time of 45.89 seconds, while the average decompression time was 0.32 seconds.

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