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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 28 Documents
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Search results for , issue "Vol 7, No 2 (2020): November 2020" : 28 Documents clear
Classification of Traditional Batik Motifs in Central Java using Gabor Filter andBackpropagationNeural Network Isnanto, R Rizal; Triwiyatno, Aris
Scientific Journal of Informatics Vol 7, No 2 (2020): November 2020
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v7i2.26215

Abstract

Batik has a variety of varied motifs, each region in Indonesia has certain characteristics on batik motifs. Based on literature studies theuse of backpropagation neural network methods to recognize complex patterns has a satisfactory rate of success. The purpose of this research is to develop and apply neural networks that are fast, precise and accurate to classify batik designs and patterns. Types of batik motifs typical of Central Java that are used include; Truntum from Solo, Warak Ngendhog from Semarang, Sekar Jagad from Lasem, Burnt from Pati, and Jlamprang from Pekalongan. The image first undergoes RGB color feature extraction based on mean values of R, G, and B, and Gabor filter texture characteristics. The tests were carried out using 90 batik images, 60 batik images for training data and 30 batik images for testing data. The results of the study concluded that the best parameter settings were, the number of hidden layer 30 neurons in the first layer and 15 in the second layer, with 6 input layers and 5 output layers. Gabor filter with 90º orientation angle and wavelength 4 become the best combination in this study. From the results of training and testing results obtained an average accuracy of 93.3% in all batik classes in Central Java.
Diagnosis of Lung Disease Using Learning Vector Quantization 3 (LVQ3) Midyanti, Dwi Marisa
Scientific Journal of Informatics Vol 7, No 2 (2020): November 2020
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v7i2.25368

Abstract

Lung disease is one of the diseases with the highest number of patients in Indonesia. Lung disease is a disease with many types and symptoms that are almost the same as each other. This study uses an artificial neural network Learning Vector Quantization 3 (LVQ3), to diagnose lung disease. The data used in this study were 113 medical records, with seven types of lung disease, and 27 symptoms of the disease. From the experimental results, the best LVQ3 parameters from this study are using m = 0.15, and the learning rate = 0.15. LVQ3 produces the best accuracy value for training data at 87.5% of 80 data, and accuracy for test data 88% of 33 data.
Fake Twitter Account Classification of Fake News Spreading Using Naïve Bayes Santoso, Heru Agus; Rachmawanto, Eko Hari; Hidayati, Ulfa
Scientific Journal of Informatics Vol 7, No 2 (2020): November 2020
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v7i2.25747

Abstract

Twitter is a very popular microblog, where users can search for various information, current news, celebrity posts, and hot topics. Indonesia is ranked 5th for the most Twitter users. The large number of users makes Twitter used for the benefit of certain parties with bad goals, such as spreading fake news using fake accounts. Fake accounts are often used by several parties to spread fake news, therefore the spread of fake news must be immediately limited to minimize the negative impact caused by fake news. For this reason, this research is written with the aim of being able to classify fake and genuine Twitter accounts. In this study, using data mining techniques that are closely related to big data in decision making by applying the Naive Bayes method. Naïve Bayes is one of the most widely used classification methods because it has good accuracy and faster computation time. The classification process uses nine parameters, namely based on the Profile Created, Favorite Count, Follower Count, Following Count, Geo Enabled, Follower Rate, Following Rate, Follower Following Ratio, Verified. This study uses 210 datasets of twitter accounts that spread fake news, the result is that Naïve Bayes works very promising  in the classification of fake twitter accounts and in the testing process using 5% of training set produces an accuracy of 80%.
Edge Computing Implementation for Action Recognition Systems Pratama, Afis Asryullah
Scientific Journal of Informatics Vol 7, No 2 (2020): November 2020
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v7i2.26433

Abstract

Nowadays the deep learning has been improved to many different sectors, including human action recognition system. This system mostly needs a high computing resource to work on. In its implementation, it will be built under cloud computing architecture which requires sensors used to send whole raw data to the cloud which puts a load in the networks. Therefore, edge computing system exists to overcome that weakness. This paper presents a method to recognize human action using deep learning with edge computing architecture. With RGB image as the input, this system will detect all persons in the frame using SSD-Mobilenet V2 model with various threshold values, then recognize every person’s action using our trained model with DetectNet architecture in various threshold too. The output of the system is detected person’s RoI and its recognized action action, which a lot smaller than the whole frame. As a result, our proposed system yields the best accuracy of human detection at 64.06% with a threshold at 0.15 and the best accuracy of action recognition at  37.8% with a threshold at 0.4.
Test-Driven Development (TDD) for Point of Sale System at Bicycle Shop Subhiyakto, Egia Rosi; Astuti, Yani Parti
Scientific Journal of Informatics Vol 7, No 2 (2020): November 2020
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v7i2.25884

Abstract

The information technology systems are developing faster; one of its developments is a system to process the recording of sales data (Selling System). To support the selling process in Ali Cycle bicycle shop, which previously done manually, it needs a system to record the stock of goods, transaction, supplier, and sales report. There is a lot of model in building the system, one of the model is traditional development model, generally, the phase of this model is never-ending related to system problems or bugs, sometimes bugs are not found in the development but comes after practical use begins. A Point of Sale (POS) system with Test Driven Development (TDD) method has been built in which a test is written before the coding phase in a purpose of the codes, which are created, has passed the test, reducing the bug and it tests the system. The results show that all codes have passed the test; the test consists of 89 functions and 397 statements. Evaluation results of end-users testing showed that the majority of respondents strongly agree and agree with a system with an average rating of 94% for performance, 89% interface and 83% user satisfaction. The conclusion is, building a POS system using TDD method succeeded by producing a useful system as the requirement and expected system quality.
Software as a Service: Design and Build Lower Usage Cost Email Marketing for Hospitality Industry Sukarsa, I Made; Buana, Putu Wira; Arynasta, I Putu Krisna
Scientific Journal of Informatics Vol 7, No 2 (2020): November 2020
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v7i2.25498

Abstract

The hospitality industry is an industry that is very customer-focused because it relies on customer information. Therefore, Customer Relationship Management (CRM) is implemented worldwide in this sector. Many features of CRM applications that are often not suitable for use by small and medium companies also make features in CRM applications tend to be wasteful. This paper aims to develop a software as a service CRM with lower usage costs without imposing development costs on users and focuses on email marketing features and data exchange integration. The system development uses the SDLC (System Development Life Cycle) method. Testing in this paper was conducted with User Acceptance Testing (UAT) where managers or hotel owners and students in the field of information technology use the application system then provide an assessment through a questionnaire. The total score obtained from 30 respondents is 1233 and be on point between the Quartile III (1200) and the Maximum score point (1500) base on LSR interpretation scaling and showed the system is considered positive and successful. The conclusion of this study is the application system can be used by hoteliers in the hospitality industry at various levels of the company to carry out functions that support customer relationship management and email marketing.
The Evaluation of Final Assignment System Using the USE Questionnaire Approach Purwinarko, Aji; Subagja, Mona; Yanuarto, Alfath
Scientific Journal of Informatics Vol 7, No 2 (2020): November 2020
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v7i2.26053

Abstract

Universitas Negeri Semarang has utilized information system technology to facilitate the assessment of final student assignments. So it is necessary to test this information system to determine user satisfaction and the success of the information system in providing services. One way to test the information system is to analyze the usability aspect, using the Usefulness, Satisfaction, and Ease of use (USE) Questionnaire. Data collection involved 75 respondents from users of the final assignment system. The reliability test results on 30 questions resulted in a Cronbach's alpha value of 0.97, which means that the questionnaire's reliability was excellent. Whereas for Usability measurement, the percentage value of Usefulness is 86.7%, Ease of Use is 84.4%, Ease of learning is 86.6%, and Satisfaction is 83.0%, which shows that the final assignment system is very worthy of being used.
Distribution Route Making for Mushroom Harvest Using Artificial Bee Colony Method Ari Santosa, I Made
Scientific Journal of Informatics Vol 7, No 2 (2020): November 2020
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v7i2.25942

Abstract

Mushrooms are food ingredient that is currently favored by the public. Seeing the large demand for mushrooms, many mushroom businesses have developed. The high level of demand for mushrooms by consumers in different locations results in the high time and costs spent in distributing mushrooms. In addition, determining distribution routes in mushroom marketing is still done manually based on the sender's knowledge, therefore reduces the effectiveness and efficiency of mushroom marketing because the distribution routes used are not optimal. To overcome these problems, it is necessary to determine an effective and efficient distribution route to reduce distribution costs and speed up distribution time. Based on these problems, this research uses the Artificial Bee Colony (ABC) method in determining the distribution route of mushroom harvest. The purpose of this study was to apply the ABC method in determining the distribution routes of mushroom harvest. The result of this research is a visualization of mushroom distribution routes using the ABC method, so it can help to distribute mushroom harvest effectively and efficiently. The research method consists of defining the problem, collecting data, analyzing systems and implementing methods, designing systems, building systems, and drawing conclusions.
Sentiment Analysis Provider By.U on Google Play Store Reviews with TF-IDF and Support Vector Machine (SVM) Method Fransiska, Susanti; Rianto, Rianto; Gufroni, Acep Irham
Scientific Journal of Informatics Vol 7, No 2 (2020): November 2020
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v7i2.25596

Abstract

Provider By.U is a relatively new and attractive telecommunications service with claims to be the first digital provider in Indonesia. All services are done digitally with the By.U application that offers convenience. Even so not all users are satisfied with the service, there are criticisms and suggestions, one of which is delivered through the By.U app review feature on the Google Play Store. Sentiment analysis is performed to extract information related to provider by.U. The steps taken are scrapping review data, positive and negative labeling, preprocessing data including data cleaning, data normalization, stopword removal and negation handling, sentiment classification using Support Vector Machine (SVM) and TF-IDF as feature extraction. TF-IDF+SVM with 5-Fold Validation produces pretty good accuracy with an average accuracy of 84.7%, precision of 84.9%, recall of 84.7%, and f-measure of 84.8%. The highest accuracy results in fold 2, 86.1%. The effect of TF-IDF on the measurement of model performance is not so great, but it is better.
FinTech E-Commerce Payment Application User Experience Analysis during COVID-19 Pandemic Abdillah, Leon A.
Scientific Journal of Informatics Vol 7, No 2 (2020): November 2020
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v7i2.26056

Abstract

Application of information technology in the era of big data and cloud computing has led to the trend of electronic payments through financial technology, or FinTech. One of the most popular FinTech applications in Indonesia is Go-Pay in the Gojek start-up application. This research will analyze how the FinTech Go-Pay user experience both for transactions on Gojek and at merchants that collaborate with Gojek. User Experience (UX) is analyzed using the User Experience Questionnaire which consists of 6 (six) variables (Attractiveness, Perspicuity, Efficiency, Dependability, Stimulation, and Novelty). Total data collected amounted to 258. After analyzing the calculation results, the mean scores are obtained in the following order: Efficiency, Perspicuity, Stimulation, Attractiveness, Dependability, and Novelty. Then when compared with benchmark data the following sequence is obtained: Efficiency, Perspicuity, Stimulation, Attractiveness, Dependability, and Novelty. Overall the Go-Pay service is efficient and perspicuity, but the Go-Pay service needs to improve its novelty.

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