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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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In Silico Molecular Docking Analysis of Limonene with The Fat Mass and Obesity-Associated Protein by Using Autodock Vina Ahmed, Muhammad Zeeshan; Hameed, Shahzeb; Ali, Mazhar; Zaheer, Ammad
Scientific Journal of Informatics Vol 8, No 1 (2021): May 2021
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v8i1.29051

Abstract

Purpose: This study aimed to predict the binding affinity, orientation, and physical interaction between limonene and fat mass and obesity-associated protein. Methods: The mechanism of limonene and protein association was explored by molecular docking, a bioinformatic tool. The association results were compared with the reported results of the anti-obesity drug such as orlistat and with the flavonoids. AutoDock Vina tools were used for the molecular docking of limonene with fat mass and obesityassociated protein. PyMol and Discovery Studio Visualizer was used to visualize the results of this docking. Result: The binding affinity of limonene was higher (Least negative G) than the orlistat and flavonoids such as Daidzein, Exemestane, Kaempherol, Letrozole, And Rutin. Novelty: In this study, the limonene can alleviate obesity by interacting with the fat mass and obesity-associated protein. This inhibitory interaction was more significant as compared to other reported phytochemicals and drugs. Keywords: AutoDock Vina, Binding Affinity, Limonene, Molecular Docking. 
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.
Business Process re-engineering to support the sustainability of the construction industry and sales commodities in large scale transaction during Covid 19 with integrating ERP and Quotation System Budiman, Kholiq; Subhan, Subhan; Efrilianda, Devi Ajeng
Scientific Journal of Informatics Vol 8, No 1 (2021): May 2021
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v8i1.27969

Abstract

Covid 19 has become a pandemic that has hit all over the world. Almost all sectors are affected by this pandemic, not only in the health sector. The economic and industrial sectors have also suffered severe impacts due to the coronavirus pandemic. This spreading virus does not support economic growth either nationally or globally. Finally, it has an impact on various industrial sectors in the country, from manufacturing to finance. The industry was one of the largest contributors to Indonesia's Gross Domestic Product (GDP) last year. The contribution given from this industry to the 2019 GDP was recorded at 19.62%. Due to this pandemic, according to the Central Statistics Agency (BPS), during February 2020, the importance of all categories of goods decreased compared to January 2020. This stunted industrial development was due to the government's appeal for social distancing; social distancing made it difficult for industry players to make transactions. Several obstacles require re-engineering of business processes in the industry. In general, the industry already has an Enterprise Resource Planning (ERP) system used in the related production process. However, ERP does not enter into the realm of buying and selling or the process of procuring goods with consumers. Therefore we need a Business Process Reengineering as an engineering process to integrate the ERP and the bidding system or quotation system. Using the moving average method as a forecasting method, we can get sustainable sales even during the Covid period, even seen an increase in transactions in the new period, along with the implementation of the quotation information system applied in the re-engineering business process.
RETRACTED: The Evaluation of Final Assignment System Using the USE Questionnaire Approach Purwinarko, Aji; Subagja, Mona; Yanuarto, Alfath
Scientific Journal of Informatics Vol 8, No 1 (2021): May 2021
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v7i2.26033

Abstract

This paper is retracted by editor due to publication ethics missconducted by author (simultaneously publication in other issue).Similar article has appeared in https://journal.unnes.ac.id/nju/index.php/sji/article/view/26053
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%.
Adversity Response Profile IT-assisted for Lectures Online during New Normal Ardiansyah, Adi Satrio; Sari, Salsabilla Naura; Caesario, Nico
Scientific Journal of Informatics Vol 8, No 1 (2021): May 2021
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v8i1.28828

Abstract

The Distance Education implemented by the government during New Normal has an impact on student learning activities and student lectures. To find out the ability of students to face problems in current conditions, it can be seen from the Adversity Quotient (AQ) which can be measured by the Adversity Response Profile (ARP). The purpose of this study was to develop valid and reliable IT-assisted ARP in online lectures during New Normal. The research method used was Research and Development (R&D) which was conducted on 50 students of the UNNES Mathematics Department. This development research consists of three stages, namely the initial investigation, the prototype phase and the assessment phase which will then be analyzed using quantitative analysis techniques. The results showed that the IT-assisted ARP met the valid and reliable criteria. The results show that the reliability value is very high, namely 0.98. With the discovery of valid and reliable ARP, educators can use it to determine the level of student ability in dealing with learning problems during the New Normal.
A Comprehensive Survey On Cloud Computing Simulators Oladimeji, Oladosu Oyebisi; Oyeyiola, Dasola; Oladimeji, Olayanju; Oyeyiola, Pelumi
Scientific Journal of Informatics Vol 8, No 1 (2021): May 2021
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v8i1.28878

Abstract

Cloud Computing is one of the upcoming technologies which has gotten the attention of many researchers and investor. But cloud computing still faces challenges because it is not economical and impractical for research institutions and industries to set up a physical cloud for research and experiments on it (cloud computing). Due to this, the researchers have chosen to test their contributions with simulators. Therefore, the purpose of this study is to perform a survey on existing cloud simulators. These cloud simulators aid in modeling cloud application through the creation of virtual machine, data Centre, and other thing which can be easily added and configured to it in order to provide stress free analysis. Till this present time, many cloud simulators with various features have been proposed and available for use. In this paper a comprehensive study has been performed on major cloud simulators by highlighting their features, strength and weakness through analysis. After which comparative analysis was done on the simulation, from the study, none of the simulators have the feature to simulate mobile cloud computing issues. This study has not been published anywhere else.
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.
Utilization of SVM Method and Extraction of GLCM Features in Classifying Fish Images with Formalin Muhathir, Muhathir; Wanti, Eka Pirdia; Pariyandani, Ayu; Idrus, Syed Zulkarnain Syed; Lubis, Andre Hasudungan
Scientific Journal of Informatics Vol 8, No 1 (2021): May 2021
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v8i1.26806

Abstract

Purpose: Fish is a type of animal protein that can be consumed by humans to supplement protein in the body. Due to the fact that there is an abundance of fish in Indonesia, traders often experience losses because of rotting fish. A small proportion of traders tricked the buyers by mixing fish with formaldehyde to preserve fish in order to prevent fish spoilage until it can be consumed.  Thus, every fish buyer must be aware of fraud by traders. Methods: To be able to find out that the fish has been mixed with formalin, the solution offered is computerized by utilizing the GLCM feature extraction as information extraction on the fish image and the SVM method as a classification method. Result: The results showed an average accuracy of 0.784, precision of 0.799, recall of 0.784, and f-measure of 0.781. Novelty: The effect of the SVM classification method on the performance measurement of the model is not too big compared to previous studies, but it is better. 
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. 

Page 26 of 57 | Total Record : 564

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