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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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Forecasting Inflation Rate Using Support Vector Regression (SVR) Based Weight Attribute Particle Swarm Optimization (WAPSO) Priliani, Erlin Mega; Putra, Anggyi Trisnawan; Muslim, Much Aziz
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.v5i2.14613

Abstract

Data mining is the process of finding patterns or interesting information in selected data by using a particular technique or method. Utilization of data mining one of which is forecasting. Various forecasting methods have progressed along with technological developments. Support Vector Regression (SVR) is one of the forecasting methods that can be used to predict inflation. The level of accuracy of forecasting is determined by the precision of parameter selection for SVR. Determination of these parameters can be done by optimization, to obtain optimal forecasting of SVR method. The optimization technique used is Weight Attribute Particle Swarm Optimization (WAPSO). The use of WAPSO can find optimal SVR parameters, so as to improve the accuracy of forecasting. The purpose of this research is to implement SVR and SVR-WAPSO to predict the inflation rate based on Consumer Price Index (CPI) and to know the level of accuracy. The data used in this study is CPI Semarang City period January 2010-February 2018. Implementation experiments using Netbeans 8.2 gives results, SVR method has an accuracy of 94.654%. SVR-WAPSO method has an accuracy of 97.459%. Thus, the SVR-WAPSO method can increase the accuracy of 2,805% of a single SVR method for inflation rate forecasting. This research can be used as a reference for the next researcher can make improvements in determining the range of SVR parameters to get the value of each parameter more effective and efficient to get more optimal accuracy.
GRAV3D Validation using Generalized Cross-Validation (GCV) Algorithm by Lower Bounds Approach for 3D Gravity Data Inversion Adhi, Mochamad Aryono; Wahyudi, Wahyudi; Suryanto, Wiwit; Sarkowi, Muh
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.v5i2.16736

Abstract

The completion of gravitational data inversion results in a smooth recovered model. GRAV3D is one software that can be used to solve 3D inversion problems of gravity data. Nevertheless there are still fundamental problems related to how to ensure the validity of GRAV3D to be used in 3D inversion. One approach used is to use lower bounds as inversion parameters. In this study lower bounds are set from  to . The results obtained show that the use of lower bounds decreases resulting in a larger data misfit which means that the more data that meets the tolerance calculation, the better recovered model produced.
Quickpropagation Architecture Optimization Based on Input Pattern for Exchange Rate Prediction from Rupiah to US Dollar Zulkarnaen, Harits Farras; Endah, Sukmawati Nur
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.v5i2.15889

Abstract

Money exchange between countries was done by using exchange rates. One of the examples was the exchange between Rupiah and US Dollar. Exchange rates prediction to US Dollar was an attempt to assist all related economic actors to avoid losses during the process of decision making. The prediction could be done by using artificial neural network method. Quickpropagation was one of artificial neural network models considered suitable for prediction. Quickpropagation network architecture consisted of input layer, hidden layer, and output layer. The input layer of quickpropagation architecture could be determined by using autoregression (AR) for the input pattern. In this research, the authors aim to optimize the quickpropagation network architecture method using Nguyen-Widrow weight initialization to predict the Rupiah exchange rate to US Dollar. The research data were the exchange rate from the BI website from May 2017 to July 2017 with a total of 57 data. The test was performed by using K-Fold Cross Validation with k = 11 values for data without AR and k = 8 for AR data. The results show that quickpropagation method using AR has better performance than quickpropagation method without AR in terms of MSE training and testing. The best parameters are in alpha 0,6 and hidden neuron 5, with MSE training value 0,03272 and MSE testing 0,02873 for selling rate and at alpha 0,9 and hidden neuron 5, with MSE training value 0,03297 and MSE testing 0,02828 for buying rate with maximal epoch 100.000 and target error 0,05.
Java Card Approach to Emulate The Indonesian National Electronic ID Smart Cards Priyasta, Dwidharma; Cesar, Wahyu; Susanti, Yanti; Junde, Juliati
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.v5i2.16347

Abstract

This paper presents a successful effort in emulating the Indonesian national electronic ID smart cards using Java Card. The aim is to provide theopportunity for other smart card products to contribute in the national electronic ID program. The life cycle status, the file system concept, commands and security procedures implemented in the Indonesian national electronic ID were reproduced and emulated ina Java Card applet. In the first stage, the emulator applet was tested using some test scenarios developed during the implementation phase. Later on, the emulator applet was tested in the real system under supervisioned by Direktorat Jenderal Kependudukan dan Pencatatan Sipil in order tomeasure its reliability as well as to determine that its behaviour is identical with the Indonesian national electronic ID. The results confirmed that this approach was fruitful.
Application of Exponential Comparison Method and Simple Additive Weighting Method in Assessment of Agricultural Extension Performance Suranti, Dewi
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.v5i2.16128

Abstract

In order to build qualified and reliable agricultural human resources, it is necessary for professional, creative, innovative and global oriented Agricultural Extension workers in the provision of productive, effective and efficient extension services. Agricultural Extension is directed to carry out advisory and consultation tasks for the main actors and business actors in developing their agribusiness business, so the adoption of appropriate technology can run well and in turn increase the empowerment of the main actors, productions, productivity, income and welfare of farmers and their families. The performance of agricultural extension workers can be seen in the aspects of preparation, implementation, evaluation and reporting, development of agricultural extension and agricultural extension profession profession. In addition, agricultural extension programs should be based on analysis of farmers needs and reflect current target audience conditions. Applying Simple Additive Wighted and Exponential Comparison Method in appraisal of farmer extension performance at UPT BPP Sukaraja aims to know the performance of agricultural extension in conducting counseling at UPT BPP Sukaraja. This is due to the lack of extension workers in BP3K Sukaraja. The results of the resulting assessment in the form of work performance ranking of each extension worker. Based on the results of the calculation both methods show the same performance rankings. With this is expected to make it easy for UPT BPP sukaraja in carrying out routine performance appraisal performance of extension workers who had been a constraint in conducting appraisal performance extension. Agricultural extension workers can carry out their duties and responsibilities
Powerpoint for Android Design Using Think Talk Write Model to Improve the Junior High School Students’ Concepts Understanding Buchori, Achmad; Cintang, Nyai
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.v5i2.15357

Abstract

As the development of Science and Technology also influence the development of learning media. Media learning is one of the determinants of student learning success. Utilization of android technology so far is not only used as a means of communication, or just entertainment but now can be developed for learning media. This research aims to develop powerpoint for android with Think Talk Write model to improve understanding of SMP students concept. The research method used is Research and Development and the type of research used is ADDIE. (1) Analyze, student needs analysis shows students need learning media. (2) Design, the products produced in this study media powerpoint for android. (3) Development, media developed then validated by 84% media experts, 82% material experts, and 85% design learning experts so it is said to be valid. (4) Implementation, student responses in class VII C achievement rate 89% are in the practical category. (5) Evaluation, the data in this study consists of preliminary data in the form of values obtained through pretest and final data in the form of values obtained through posttest. The result of the second posttest of the class is tested equality of two averages (right-t test) obtained α = 0.05 obtained t_table = 1.669 and t_count = 3.251 because Since t_count> t_table then H0 rejected and H1 accepted, so it can be concluded learning using Powerpoint for Android with Think Talk Write model to improve concept understanding is said to be valid, practical, and effective than the conventional learning model.
Implementation of Expert System for Diabetes Diseases using Naïve Bayes and Certainty Factor Methods Ilham Insani, Muhammad; Alamsyah, Alamsyah; Putra, Anggyi Trisnawan
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.v5i2.16143

Abstract

Expert Systems is a computer systems that has been entered the base knowledge and a set of rules used to solve problems like an expert. Methods that can be used in the expert systems which is Naïve Bayes and Certainty Factor. Naïve Bayes method can handle quantitative calculations and discreate data and only requires a little research data to estimate the parameters needed in the clasification and Certainty Factor which is suitable for measuring something whether it is certain or not in diagnosing. Diabetes is one of the most frequent diseases suffered in Indonesia. The purpose of this research is implementation expert systems used Naïve Bayes and Certainty Factor in diagnosing diabetes and knowing the level of accuracyof the systems. Data that is used by researchers as much 100 data medical record, obtained from the medical record RSUD Bendan Kota Pekalongan. The variabels used in this research is age, gender, the symptoms of the desease diabetes and result diagnose desease from expert. The accuracy rate of this system derived from the scenario distribution data 70 training data and 30 testing data that is equal to 100% according to the doctors diagnosis.
Forensic Tool Comparison on Instagram Digital Evidence Based on Android with The NIST Method Riadi, Imam; Yudhana, Anton; Putra, Muhamad Caesar Febriansyah
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.v5i2.16545

Abstract

The growth of Android-based smartphone users to access media in communicating using Instagram social media is very fast. Activities are carried out when using Instagram social media in communicating to share information such as sending chat texts and pictures. A large number of Instagram users make this application vulnerable to abuse of Instagram such as pornography crimes from Instagram users. This case can be forensic to get digital evidence in the form of chat text and pictures from Instagram messenger is a feature of Instagram. The investigation in this study uses the National Institute of Standards and Technology (NIST) method which provides several stages of collecting, examining, analyzing, reporting while forensic tools use forensic oxygen and axiom magnets. The results of the recovery and comparison of data result using Oxygen forensics and Axiom Magnets obtained digital evidence in the form of data in the form of images and chat. The data obtained by Magnet Axiom is 100% while forensic oxygen is 84%. These data are the results of the performance of both forensic applications in obtaining digital evidence that has been deleted from the Instagram messenger.
Scheduling Optimization of Sugarcane Harvest Using Simulated Annealing Algorithm Afifah, Eka Nur; Alamsyah, Alamsyah; 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.v5i2.14421

Abstract

Scheduling is one of the important part in production planning process. One of the factor that influence the smooth production process is raw material supply. Sugarcane supply as the main raw material in the making of sugar is the most important componen. The algorithm that used in this study was Simulated Annealing (SA) algorithm. SA apability to accept the bad or no better solution within certain time distinguist it from another local search algorithm. Aim of this study was to implement the SA algorithm in scheduling the sugarcane harvest process so that the amount of sugarcane harvest not so differ from mill capacity of the factory. Data used in this study were 60 data from sugarcane farms that ready to cut and mill capacity 1660 tons. Sugarcane harvest process in 19 days producing 33043,76 tons used SA algorithm and 27089,47 tons from factory actual result. Based on few experiments, obtained sugarcane harvest average by SA algorithm was 1651,63 tons per day and factory actual result was 1354,47 tons. Result of harvest scheduling used SA algorithm showed not so differ average from mill capacity of factory. Truck uses scheduling by SA algorithm showed average 119 trucks per day while from factory actual result was 156 trucks. With the same harvest time, SA algorithm result was greater  and the amount of used truck less than actual result of factory. Thus, can be concluded SA algorithm can make the scheduling of sugarcane harvest become more optimall compared to other methods applied by the factory nowdays.
The Comparison Combination of Naïve Bayes Classification Algorithm with Fuzzy C-Means and K-Means for Determining Beef Cattle Quality in Semarang Regency Devi, Feroza Rosalina; Sugiharti, Endang; 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.v5i2.15452

Abstract

The beef cattle quality certainly affects the quality of meat to be consumed. This researchperforms data processing to do the classification of beef cattle quality. The data used are196 data record taken from data in 2016 and 2017. The data have 3 variables fordetermining the quality of beef cattle in Semarang regency namely age (month), Weight(Kg), and Body Condition Score (BCS) . In this research, used the combination of NaïveBayes Classification and Fuzzy C-Means algorithm also Naïve Bayes Classification andK-Means. After doing the combinations, then conducted analysis of the results of whichtype of combination that has a high accuracy. The results of this research indicate that theaccuracy of combination Naïve Bayes Classification and K-Means has a higher accuracythan the combination of Naïve Bayes Classification and Fuzzy C-Means. This can be seenfrom the combination accuracy of Fuzzy C-Means algorithm and Naïve Bayes Classifierof 96,67 while combination of K Means Clustering and Naïve Bayes Classifier algorithmis 98,33%, so it can be concluded that combination of K Means Clustering algorithm andNaïve Bayes Classifier is more recommended for determining the quality of beef cattle inSemarang regency.

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