bluuebunny/crossref_metadata_2025_split huggingface dataset:
Designing Google Form based Information System for Submitting Students’ Final Assignment’s Title
Authors: Widodo S R , Indrasari L D , Tripariyanto A Y , Komari A 
Published: July 2020

Abstract
In the study of Industrial Engineering, Kadiri University, the final assignment for the title of three titles will be proposed. The way of proposing the proposal is, when there is a decree from Kaprodi, it will be presented to students who program the final assignment, then there are three plans of title that must be proposed, then after writing three plans of the title, the data will be entered by the library attendant, then it will be listed. After being listed, the title plans are data files that will be addressed to Kaprodi. Then, Kaprodi will decide whice title that must be taken by student as well as who the supervisor is.. Observing those activities, students should come to the campus to register the plans for the titles of the assignment that must be taken. To ease the student, researchers want to design information system that will facilitate the submission of plans for the title of the final assignment in the form of links, the link is derived from Google form. With this ease, students are expected to save time, do not have to come to the campus during the registration of the final assignment title plans. Designing forms and activities, it will be simulated by system flow and data flow diagrams, to know the details of the activities that occur, because the flow of the system will be compared to conventional systems with new one. The methods are assisted by data flow diagrams, system flow, and PIECES method.
Rule Based Method in Expert System for Detection Pests and Diseases of Corn
Authors: Sumaryanti Lilik , Istanto Teddy , Pare Selfina 
Published: July 2020

Abstract
Corn is a multi-functional plant, both for direct consumption and as the main raw material for animal feed and the food industry. The need for corn in Indonesia, which continues to increase, needs to be balanced with an increase in production. So that various government policy strategies are carried out, in an effort to increase productivity. Constraints in the cultivation of corn, namely farmers have limitations in identifying diseases that attack plants, and ways to control pests and diseases. The purpose of this study is to propose the use of technology in agriculture by developing an expert system for the detection of corn pests and diseases, which will provide information and strategies for controlling pests and diseases, in order to reduce losses due to crop failure. The knowledge base in expert system contains a set of rules that use the IF-THEN pattern, and to reason on a rule base using forward cahaining method. Expert system is a tool to detection pests and diseases and how to control them like providing expert assistance. In addition, system also provides explanation facility related to the diagnosis results, according to the symptoms obtained from the user. The accuracy detecting pests and diseases 76.6%.
Multimedia development with web-based connected massive open online course (cmoocs) in basic physics material
Authors: Henukh A , Reski A , Nikat R F , Waremra R S , Bahri S 
Published: July 2020

Abstract
This study aims to develop web-based multimedia cMOOCs in basic physics material. The research method used is research and development using the ADDIE model (Analyze-Design-Development-Implementation-Evaluation). The objects in this study were 31 students in the physics education study program at the State University of Jakarta. The research instruments used were material expert validation sheets, multimedia expert validation sheets, and multiple choice questions. The results of the material expert validation showed 94.19% (very good). The results of the multimedia expert validation showed 78.33% (good). The results of the small group trial got a score of 82.67% and the results of the large group trial showed 90.03%. The results of the assessment of the effectiveness of web cMOOCs in the basic physics material I, obtained N-gain at a score of 0.786 so that it falls into the very high category.
Based on the data above, this study shows that cMOOCs web-based multimedia development in basic physics material I can be used as learning multimedia.
Optimization Naive Bayes using Particle Swarm Optimization in Volcanic Activities
Authors: Tempola F , Mubarak A 
Published: July 2020

Abstract
This study is a continuation of previous studies that apply Naive Bayes classifier algorithm for predicting the status of volcanoes in Indonesia based on factors of seismicity. There are 5 criteria used in predicting the status of the mountain, namely the status of normal, alert and standby. The results of the study showed that the system accuracy produced was only 79.31%, in other words, it was still at the stage of fair classification. To overcome these weaknesses so that accuracy increases, optimization is done by giving the weight of criteria or attributes using particle swarm optimization. From the results of research by applying the same data using Particle Swarm optimization methods optimization, the accuracy of the resulting system increase of to 95.65%, where the number of particles is initialized 50 and the weight range [0 2].
Emotion Mining of Indonesia Presidential Political Campaign 2019 using Twitter Data
Authors: Arifiyanti A A , Wahyuni E D , Kurniawan A 
Published: July 2020

Abstract
The presidential election campaign in Indonesia which was held in 2019 attracted the interest of the Indonesian people. People expressing their emotion through social media, one of which is Twitter. Supervised learning is used to classify user’s emotion of that issues. The goal of this research is extracting the emotional content in tweets. The interest is in whether the text is an expression of Twitter users’ about the presidential candidates and whether this online forum represents the election results. For this purpose, text mining techniques are performed and we will compare Naive Bayes Classifier and SVM in classification process. The result showed that Naive Bayes Classifier and SVM have good performance for classifiying text and each of classifier have not outperform the others. The result also showed that stemming step in text pre-processing do not give any significant result in model accuracy, because twitter data use informal languange like abbreviation or slang.
Video-based Tancho Koi Fish Tracking System Using CSK, DFT, and LOT
Authors: Rahmat Basuki , Waluyo Minto , Rachmanto Tuhu Agung , Afandi Mohamad Irwan , Widyantara Helmy , Harianto  
Published: July 2020

Abstract
In this paper, a comparison of Circulant Structure of Tracking-by-detection with Kernels (CSK), Distribution Fields for Tracking (DFT) and Locally Orderless Tracking (LOT) methods is proposed for the process of video-based object tracking. The object in question is the tancho koi fish and its variants, in the form of video recordings. All three methods are applied to trace the red roundabout in the head of the koi fish. The purpose of this study is to provide the best tracking process recommendations for this case. From the experimental results, it is found that the average sample accuracy of the DFT tracking method is more recommended than the other two methods, even though it has an average frame rate that is no better than the CSK method.
Measurement of the IT Helpdesk Capability Level Using the COBIT 5 Framework
Authors: Muttaqin F , Idhom M , Akbar F A , Swari M H P , Putri E D 
Published: July 2020

Abstract
Directorate Information System of Airlangga University (Direktorat Sistem Informasi Universitas Airlangga, DSI) is a unit of Airlangga University as an IT service for all stakeholders. DSI using helpdesk as an IT service to manage service request and incident. The aims of capability level measurement is to improve IT helpdesk to reach a target score. This research using COBIT 5 framework began by mapping domains through several stages. Those several stages are; stakeholder needs analysis, enterprise goals identification, IT goals identification and domain process COBIT 5 identification. The result of the mapping domain obtained DSS 02 manage service request and incident. The next stages are measure current condition capability level, determine expected level, determine gap. The results of this research using DSS 02 domain process showed a level 1 capability level percentage of 97.23% which is a fully achieved rating level and so is rated to level 1 and go to the next level assessment. Level 2 PA 2.1 capability level percentage of 80% which is a largely achieved rating level and PA 2.2 capability level percentage of 60% which is a largely achieved rating level. So, current capability level rated to level 2. The expected level is at level 3. Hence to achieve a level 3 an improvement is required by applying base practices and fulfilment work products of level 2 and 3.
Denoising Convolutional Neural Network for Fundus Patches Quality
Authors: Setiawan Wahyudi , Utoyo Moh. Imam , Rulaningtyas Riries 
Published: July 2020

Abstract
Image quality is one of the factors that supporting a system to perform tasks such as image classification, segmentation, and recognition. Better tasks learning needs image quality improvement. In this study, image quality improvement do by denoising Convolutional Neural Network (dnCNN). The dnCNN network include the convolution layer, rectified linear unit, batch normalization, and final regression layer. DnCNN layer configuration consists of 58 layers. The denoising image process have five steps: data access, noise image, configuration of dnCNN layer, denoised image, and assess image quality with Peak Signal-to-Noise Ratio (PSNR), Structure Similarity (SSIM), and Mean Square Error (MSE) Experiment uses public data fundus image from MESSIDOR and Retina Image Bank. Results show, average value of PSNR noisy image 20.75, PSNR denoised image 31.8, SSIM noisy image 0.92, SSIM denoised image 0.99, MSE noisy image 0.0084, MSE denoised image 0.0007.
Detection and Identification Indonesia License Plate Using Background Subtraction Based on Area
Authors: Damayanti F , Dewi W K , Rahmanita E , Rachmad A R 
Published: July 2020

Abstract
The increasing number of vehicles, especially four-wheeled vehicles in big cities, raises traffic problems, including toll roads. With a fast transaction process at the entrance of the toll road, it can reduce the queue of traffic congestion. For this reason, it is necessary to use a vehicle number character recognition image processing application. In this study, an application for license plate character recognition was made on vehicle images starting from the plate detection process using background subtraction. Next is the segmentation process of each character and feature extraction process using area-based features extraction. For the character recognition process, use the K-Nearest Neighbor method. The data used in this study were 50 vehicle images with each of them having 3 distances namely 50 cm, 75 cm and 100 cm. The results of this research trial showed the best level of accuracy for the detection of license plate locations is 94%, the best accuracy of segmentation per character is 71.79% and 82.59% is the best accuracy of character recognition.
Augmented Reality-Marker Detection Measurement on Heroes of Surabaya Mobile Games
Authors: Kusumaningsih Ari , Angkoso Cucun Very , Ubaidillah Ahmad 
Published: July 2020

Abstract
— Different arrangement in selling freemium programming application is the In-App Purchase (IAP) technique, where clients can download and enjoy the application for free; however, there are premium highlights that must be paid. We use Augmented Reality (AR) innovation into the IAP framework in the buying system of the game application, Heroes of Surabaya (HOS). The application allows user keeps run and play on the Android mobile system, but it will require AR marker cards to enable the premium feature on it. This investigation plans to test the effectiveness of AR marker cards that proposed as a substitute for computerized cash on the purchasing system of the game application. From the experimental results, the distance of the marker and the light factor are the main factors for the success-rate of the detection of the AR marker.
Mobile Expert System for Dengue Fever Based on Certainty Factor Method
Authors: Khozaimi Ach. 
Published: July 2020

Abstract
The development of information technology more rapidly, it can be used to study the dangers of dengue fever and know the type of symptoms that resemble dengue fever. In this research, the design and implementation of multimedia-based android application in which there are components of text, images, and animation. The purpose of designed and built application “Dengue Alert” to help users learn and do the prevention of dengue fever. Besides this application also provides information how to deal with dengue fever. This application was developed by utilising Certainty Factors method as a method of decision support. The result of this research is a mobile application that 97.6% can predict Dengue Hemorrhagic Fever (DHF) so that DHF can be detected early.
Prediction of Student Acceptance Based on Android
Authors: Syakur Muhammad Ali , Sari Rochman Eka Mala 
Published: July 2020

Abstract
State universities are the hope of most students who want to continue their education to a higher level after high school / equivalent. To enter college, students must take the selection test held by the desired university. For state universities the selection test is held simultaneously and simultaneously called the SBMPTN (Joint Selection to Enter State Universities). This selection is carried out nationally and the participants are all students who want to get the opportunity to enter a state university. To get results that are as expected, the participants must make some preparations including the Try Out. By doing SBMPTN Try Out, it is expected that participants can compete with other participants and can graduate according to their choice. Try Out can be done at the place of tutoring that holds it or by buying a book containing Try Out questions. Along with the development of Smartphone technology, a prediction system will be created from the results of an Android-based SBMPTN Try Out that will provide information on study programs and universities that are likely to receive. SBMPTN participant candidates can practice questions anywhere and anytime. The method that will be used is the Fisher-Yates Shuffle, which functions to scramble the questions.
Subject Scheduling Using Genetic Algorithms (Case Study: SMK Negeri 1 Labang-Madura-Indonesia)
Authors: Sari Rochman Eka Mala , Syakur Muhammad Ali , Imamah  , Rachmad Aeri 
Published: July 2020

Abstract
The manually scheduling system is considered less effective and efficient because it requires a long time. Problems will become more complex if the number of components or data used is increasing. The schedule is expected not only not to experience clashes, but also to adjust to some limitations that must be met. Genetic Algorithm is one of the heuristic search algorithms that are very well used in solving optimization problems. The problem of scheduling genetic algorithms is considered to have good performance in finding the optimal solution. Genetic Algorithms implement an evolutionary process by randomly producing chromosomes from each population These chromosomes produce a solution to the problem raised, namely scheduling subjects. The conclusion of this study is to be able to arrange the schedule of subjects efficiently, by overcoming obstacles such as clashing schedules without eliminating the constraints that must be met.
Implementing Method of Empirical Mode Decomposition based on Artificial Neural Networks and Genetic Algorithms for Crude Oil Price Forecasting
Authors: Herawati S , Djunaidy A 
Published: July 2020

Abstract
Fluctuations in crude oil prices can affect a country’s economic policies. The movement of crude oil prices tends to be nonlinear and non-stationary. One forecasting method that is intended to accommodate these traits is forecasting that integrates empirical mode decomposition (EEMD) ensemble methods based on artificial neural networks and genetic algorithms. In the EEMD method, a white noise signal is added to compensate for the mixture mode that can be formed. Each IMF and residue generated in the decomposition process are used as input to a feedforward neural network (FNN) artificial neural network to obtain forecasting models from each IMF and residue. The genetic algorithm is integrated with the FNN to avoid overfitting, the formation of local optima solutions, and the sensitivity of the selection of FNN parameters. The data in this study uses West Texas Intermediate (WTI) and Brent oil prices. The results of the performance comparison trials for several combination forecasting methods can be concluded that the forecasting results that integrate the EEMD method with JST-GA provide better results compared to the forecasting method that integrates EMD with ANN and EEMD with ANN. The forecasting method developed in this study resulted in forecasting with RMSE / Dstat values of 0.0257 / 61.5936% and 0.0270 / 72.0930% respectively for daily and monthly data from WTI oil types; and the RMSE / Dstat value of 0.0229 / 58.8128% and 0.0300 / 81.5789% respectively for daily and monthly data from the type of Brent oil.
Implementation of RC4 Cryptography Algorithm for Data File Security
Authors: Doni A F , Maria O A H , Hanif S 
Published: July 2020

AbstractCommunication in the digital age plays an important role, a person can carry out various transactions or exchange data practically and quickly. So as to pose a great risk to information security, ranging from misuse of access or unauthorized authority, modification, change of information, destruction to theft, this is in accordance with the main principles of data and information security ranging from Confidentiality, Integrity, Authentication, and Availability. In research that has been done using RC4 Cryptography Algorithm for Encryption and Decryption in Data Files shows that the RC4 algorithm can run well and is able to secure the authenticity of the data so it is not easily changed by people who are not responsible or people who do not have good access rights in the form text or files in several pdf, doc, Docx, Xls, xlsx or text file formats and directly affect the execution time of encrypted and decrypted files.
Comparison of Data Mining Algorithm Performance on Student Savings Dataset
Authors: Negara Y D P , Doni A F 
Published: July 2020

Abstract
Sabilillah Educational Cash Unit is a unit within the sabilillah educational foundation which is engaged in education. The stored cash processing data will be utilized using data mining so that it can be used as a decision support for finding information that is useful in evaluating the data used. Various methods contained in the data mining, the authors will make a comparison of the method techniques from the data mining. The use of the decision tree and, K-means method is implemented using the Rapid Miner application, which will later be analysed of each of these methods to determine the strategy to look for students who have the potential to save the hajj savings. This research was conducted with a group of data to determine the percentage value of precision, recall and accuracy. The results of this study that the C.4.5 method has a better value than other methods on the recall and accuracy, while the K-Means method has a precision value better than the other methods.
Performance of Microstrip Patch Omnidirectional Antenna with Stripline on Unmanned Aircraft System
Authors: Tholabi A T , ubaidillah A , Lancana H P 
Published: July 2020

Abstract
The paper is very important in designing of antenna applied for Unmanned Aircraft System (UAS) currently uses frequency spectrum allocation in the 902-928 MHz band for telemetry communication and at 2.4 GHz for radio control communication, both are irrelevant because they have the potential to be interfered with by GSM and WiFi communication. Therefore, the payload will be placed on one of the mobile service frequency allocations according to the regulation of TASFRI 2014, which is 3370 - 3400 MHz. So, we need antenna design that can work at that frequency. Because this antenna will be placed on a moving payload then needs antenna design that has minimal dimensions and omnidirectional radiation patterns is needed. This paper results that the microstrip patch omnidirectional antenna can be applied for UAS and can be optimized by stripline method.
Decision Support System for Determination of Development of Small and Medium Industries Using VIKOR
Authors: Jauhari Achmad , Suzanti Ika Oktavia , Yunitarini Rika 
Published: July 2020

Abstract
As a basis for regional economic growth, the existence of small and medium industries is very influential for people’s lives. But on the other hand the parties involved are very rarely optimize their potential, because of the many small and medium industries owned by the community, especially in Bangkalan Madura. One effort to overcome difficulties in optimizing the potential of small and medium industries is the application of determining the priority for the development of SMEs. This application uses the VIKOR method with the criteria of Investment Value, Production Capacity, Production Value, Value of Raw Materials and Labor. VIKOR is a ranking method using a multi-criteria ranking index based on a certain measure of proximity to the ideal solution. So this application will choose a small and medium industry that is suitable for assistance in its development. The test results show that from making this application using the Vikor method has an accuracy rate of 73%.
Web Service for Search Engine Bahasa Indonesia (SEBI)
Authors: Husni  , Suzanti Ika Oktavia , Pramudita Yoga Dwitya , Putro Sigit Susanto , Heryawan Lukman 
Published: July 2020

Abstract
The purpose of this research is to produce an Indonesian language search engine (SEBI) that is in accordance with the objectives of the 2016 KKNI-based curriculum. SEBI 2017 is one of the complete search engines that is able to collect web pages from the internet, do preprocessing, build indexes, handle query and categorize documents. SEBI 2017, as a prototype has shortcomings, namely time and access. Based on this, the researchers built a new architecture called the SEBI API (2018). In the SEBI API architecture (2018), the ease and breadth of access, as well as the integration of data from various applications and different owners. RESTful API added to SEBI allows SEBI to be accessed from various access devices using various programming languages, libraries or frameworks that support REST API client (consumer) functions. Broadly speaking, the 2018 SEBI architecture has been equipped with RESTful API (provider) and client (consumer) functions. After testing by entering keywords, the results show that the SEBI API architecture (2018) has been able to correct the weaknesses contained in the SEBI architecture (2017)