Jurnal Online Informatika
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Location Selection Query in Google Maps using Voronoi-based Spatial Skyline (VS2) Algorithm
Get PDFGoogle Maps is one of the popular location selection systems. One of the popular features of Google Maps is nearby search. For example, someone who wants to find the closest restaurants to his location can use the nearby search feature. This feature only considers one specific location in providing the desired place choice. In a real-world situation, there may be a need to consider more than one location in selecting the desired place. Assume someone would like to choose a hotel close to the conference hall, the museum, beach, and souvenir store. In this situation, nearby search feature in Google Maps may not be able to suggest a list of hotels that are interesting for him based on the distance from each destination places. In this paper, we have successfully developed a web-based application of Google Maps search using Voronoi-based Spatial Skyline (VS2) algorithm to choose some Point Of Interest (POI) from Google Maps as their considered locations to select desired place. We used Google Maps API to provide POI information for our web-based application. The experiment result showed that the execution time increases while the number of considered location increases
Sentiment Analysis about Large-Scale Social Restrictions in Social Media Twitter Using Algoritm K-Nearest Neighbor
Get PDFSentiment analysis is a data processing to recognize topics that people talk about and their sentiments toward the topics, one of which in this study is about large-scale social restrictions (PSBB). This study aims to classify negative and positive sentiments by applying the K-Nearest Neighbor algorithm to see the accuracy value of 3 types of distance calculation which are cosine similarity, euclidean, and manhattan distance for Indonesian language tweets about large-scale social restrictions (PSBB) from social media twitter. With the results obtained, the K-Nearest Neighbor accuracy by the Cosine Similarity distance 82% at k = 3, K-Nearest Neighbor by the Euclidean Distance with an accuracy of 81% at k = 11 and K-Nearest Neighbor by Manhattan Distance with an accuracy 80% at k = 5, 7, 9, 11, and 13. So, in this study the K-Nearest Neighbor algorithm with the Cosine Similarity Distance calculation gets the highest point
Prediction Model for Soybean Land Suitability Using C5.0 Algorithm
Get PDFSoybean is one of the protein main sources that can be used for consumption in tempeh, tofu, milk, etc. Based on projection results, soybean production and consumption balance in Indonesia, in 2018-2022, it is estimated that deficit will increase by 6.18% per year. So, it\u27s necessary to guide soybean land suitability, which can be carried out by evaluating existing land suitability to support soybean farming expansion and production. This study conducted an analytical study to evaluate soybean land suitability using C5.0 algorithm based on land and weather characteristics. The C5.0 algorithm is an extension of spatial decision tree, an ID3 decision tree extension. Dataset is divided into two categories: explanatory factors representing seven land characteristics (drainage, land slope, base saturation, cation exchange capacity, soil texture, soil pH, and soil mineral depth) and two weather data (rainfall and temperature), and a target class represent soybean land suitability in two study areas, namely Bogor and Grobogan Regency. The result generated two land suitability models with the best model obtained accuracy for training data 98.58%, while testing data was 97.17%. The best model rules are 69 rules that do not involve three attributes: cation exchange capacity, soil mineral depth, and rainfall
Enhancement of White Blood Cells Images using Shock Filtering Equation for Classification Problem
Get PDFMedical image processing has developed rapidly in the last decade. The autodetection and classification of white blood cells (WBC) is one of the medical image processing applications. The analysis of WBC images has engaged researchers from medical also technology fields. Since WBC detection plays an essential role in the medical field, this paper presents a system for distinguishing and classifying WBC types: eosinophils, neutrophils, lymphocytes, and monocytes, using K-Nearest Neighbor (K-NN) and Logistic Regression (LR). This study aims to find the best accuracy of pre-processing images using original grayscale, shock filtering, and thresholding grayscale. The highest average accuracy in classifying WBC images in the conducting research is 43.54% using the LR algorithm from 2103 images. It is obtained from the combination of thresholding grayscale image and shock filtering equation to enhance the quality of an image. Overall, using two algorithms, KNN and LR, the classification accuracy can increase up to 12%
Implementation of Fuzzy C-Means for Clustering the Majelis Ulama Indonesia (MUI) Fatwa Documents
Get PDFSince the Indonesian Ulema Council (MUI) was established in 1975 until now, this institution has produced 201 edicts covering various fields. Text mining is one of the techniques used to collect data hidden from data that form text. One method of extracting text is Clustering. The present study implements the Fuzzy C-Means Clustering method in MUI fatwa documents to classify existing fatwas based on the similarity of the issues discussed. Silhouette Coefficient is used to analyze the resulting clusters, with the best value of 0.0982 with 10 clusters grouping. Classify fatwas based on the similarity of the issues discussed can make it easier and faster in the search for an Islamic law in Indonesia
A Fast Dynamic Assignment Algorithm for Solving Resource Allocation Problems
Get PDFThe assignment problem is one of the fundamental problems in the field of combinatorial optimization. The Hungarian algorithm can be developed to solve various assignment problems according to each criterion. The assignment problem that is solved in this paper is a dynamic assignment to find the maximum weight on the resource allocation problems. The dynamic characteristic lies in the weight change that can occur after the optimal solution is obtained. The Hungarian algorithm can be used directly, but the initialization process must be done from the beginning every time a change occurs. The solution becomes ineffective because it takes up a lot of time and memory. This paper proposed a fast dynamic assignment algorithm based on the Hungarian algorithm. The proposed algorithm is able to obtain an optimal solution without performing the initialization process from the beginning. Based on the test results, the proposed algorithm has an average time of 0.146 s and an average memory of 4.62 M. While the Hungarian algorithm has an average time of 2.806 s and an average memory of 4.65 M. The fast dynamic assignment algorithm is influenced linearly by the number of change operations and quadratically by the number of vertices
Comparison of Machine Learning Classification Methods in Hepatitis C Virus
Get PDFThe hepatitis C virus (HCV) is considered a problem to the health of societies are the main. There are around 120-130 million or 3% of the world\u27s total population infected with HCV. Without treatment, most major infectious acute evolve into chronic, followed by diseases liver, such as cirrhosis and cancer liver. The data parameters used in this study included albumin (ALB), bilirubin (BIL), choline esterase (CHE), -glutamyl-transferase (GGT), aspartate amino-transferase (AST), alanine amino-transferase (ALT), cholesterol (CHOL), creatinine (CREA), protein (PROT), and Alkaline phosphatase (ALP). This research proposes a methodology based on machine learning classification methods including k-nearest neighbors, naïve Bayes, neural network, and random forest. The aim of this study is to assess and evaluate the level of accuracy using the algorithm classification machine learning to detect the disease HCV. The result show that the accuracy of the method NN has a value of accuracy are high, namely at 95.12% compared to the method KNN, naïve Bayes and RF in a row amounted to 89.43%, 90.24%, and 94.31%
Design of an Information System for Class Scheduling a Web-Based Lecture Schedule (Case Study: Faculty of Engineering and Science, Ibn Khaldun University)
No full textDuring the Covid-19 pandemic, the lecture process was carried out online, so it impacted other academic activities such as the preparation of lecture schedules. The results of observations at the Faculty of Engineering and Science found that the practice of lecture schedules was carried out manually, such as the schedule coordination process was carried out face-to-face between study programs, faculties, and lecturers to overcome conflicts in the use of rooms and teaching time. Changes in the teaching schedule need to be re-checked on the use of the room and the lecturer\u27s teaching time because it has not been documented with the information system. Hence, this study aims to build an information system for preparing lecture schedules using the Greedy Best First Search Method based on the willingness of lecturers to teach. The system was developed using the RAD (Rapid Application Development) and testing using BlackBox testing. The results of this study succeeded in building a lecture scheduling information system that was able to generate lecture schedules automatically and quickly without having to coordinate face-to-face to support online lectures during the Covid-19 pandemic.Classroom scheduling that is managed conventionally will be a problem for every university. The results of observations at the Faculty of Engineering and Science, Ibn Khaldun University, found the problem that scheduling was done manually. Lecturers need a long time and decisions to adjust their time and teaching availability because the management of the Study Program must conduct several coordination meetings between lecturers, the infrastructure division, and between study programs. The documentation of the implementation of the SOP for the lecture schedule is still not well recorded. Therefore, in this study, building an automation information system for lecture schedule preparation using the Greedy Best First Search method, based on the lecturers\u27 willingness to teach. The system development stage uses the RAD (Rapid Application Development) approach, and testing uses Blackbox testing. This study succeeded in building a web-based lecture scheduling information system so that the lecture schedule preparation process became automatic and fast
Interactive Digital Catalog for Canopy Workshop Using Augmented Reality
Get PDFThis research study develops a product promotion method for a canopy roofs. The development of this method is to apply a 3-dimensional (3D) catalog using Augmented Reality (AR) technology. By utilizing Augmented Reality technology, sellers do not need to create markets or miniature products that are commonly used to provide examples to consumers to save costs, attract consumer interest, and display objects that appear natural. Based on the tests that have been done, it is concluded that implementing Augmented Reality in the canopy sales promotion media using the Luther development method with the stages of analysis, design, implementation, testing, and maintenance. Implementation of Augmented Reality in canopy sales promotion media uses concept data from the types of canopies included in the Augmented Reality-based application, namely stainless and hollow types made using a 3D blender program. A marker as a sign to bring up 3D objects in the application. Markers are created using Photoshop and entered the database so that they can be stored online. System testing uses the BlackBox testing method where the program\u27s functionality is running as desired
Determinant Factors in the Implementation of Information Technology Strategic Management to Academicians\u27 Performance in Higher Education Institution
Get PDFThis study aimed to understand the determinant factors of information technology (IT) strategic management to individual (lecturer) performance using data samples from selected higher education institutions in Indonesia. Since the use of IT innovation in (HEI) is often considered a lens representing the strength of strategy, competitiveness, and quality within a corporate view, it is vague on its impact on individual performance. The investigation included data collection based on an online survey conducted on 325 respondents to investigate the relationship between strategic factors, elaborated into several relevant criteria. The results of statistical data processing showed that of all the strategic factors involved, the business model and strategic alignment categorized in high determinations in influencing academicians\u27 performance at HEI