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Integrating Analysis of Quality Management of Higher Education: Analytical Hierarchy Process and Multiple Linear Regression
Full text linkThe study focus on to determine factors of the quality management on the higher education and analysis the effect of important factors of quality management. Factors of quality management in this study which covering of human resources, facilities and infrastructure, leadership, and organization. Sample study using students from several private universities in Lampung Province. Analysis method using integrating analysis by Analytical Hirarchy Method (AHP) and Multiple Regression Linear (MLR). Correlation test using the product moment stated quality management of higher education have a strong relationship to human resources, has a moderate relationship with infrastructures, and a weak relationship to the leadership and organizing. The result by multiple regression linear method reveal that significant effect on human resources, facilities and infrastructure, leadership and organizational on Quality Management in higher education. While, AHP method suggestion the result that the most important in Quality Management of Higher Education is a human resources owned by a higher education. This evidence contribute to the decision makers in universities which is priority and have to improve the quality of higher education managemen
Classification of Mint Leaf Types Based on the Image Using Euclidean Distance and K-Means Clustering with Shape and Texture Feature Extraction
No full textMint is a plant that has many benefits and uses. However, some people are not familiar with the types of mint leaves because they cannot tell the difference. Actually, if you look closely, mint leaves have their own characteristic shape and texture. However, most people judge mint leaves to have a shape similar to other leaves so it is difficult to tell them apart. This paper aims to classify the types of mint leaves using the Euclidean distance algorithm and K-Means clustering with shape and texture feature extraction. The K-Means Clustering Algorithm functions as a segmentation so that the image to be classified can be separated from other objects. In the feature extraction process, metric and eccentricity parameters are used. Meanwhile, for texture feature extraction, use the parameters in the Gray Level Co-occurence Matrix (GLCM). Furthermore, the classification process uses the Euclidean Distance algorithm which has a function to represent the level of similarity between two images by taking into account the distance value from the identified image. Based on the results of the evaluation using a confusion matrix by calculating precision, recall and accuracy, the precision value is 82%, recal is 84% ​​and accuracy is 83%
Online Learning Service Application Using Flutter Framework and Laravel
Full text linkOnline learning is a concept of learning that is carried out online or through the internet network. Very advanced technology in the modern era and globalization makes various activities carried out efficiently and can be done using only gadgets. Technological developments in the field of education with the use of e-learning in learning activities in schools, colleges, courses and even online communities have started to use concepts like this.
This study uses Flutter to create applications for users and consultants in conducting online consultations on android devices. The author uses a collection of widgets that have been provided by flutter to create components in the user interface such as buttons, input text, text, icons, and others.
In this study, we use the Laravel framework to create an admin dashboard and provide a Restful API for android applications to handle database management on the server. The author uses Laravel's features to build a fullstack application that handles requests, routing, controllers, services, models, and views
Application of Data Mining for Student Department Using Naive Bayes Classifier Algorithm
Full text linkSMAN 02 Negeri Agung does not have a system that can assist schools in determining majors. The problem that occurs is that SMAN 02 Negeri Agung, when doing majors, still uses existing data, for example, using a majoring interest questionnaire, there are questions about the interests that students want, and the values of their junior high school report cards, which consist of Indonesian, Mathematics, Science, Social Studies, and English. However, there are still many students who choose majors not based on their interests or historical grades, such as following friends' choices. This can hinder student academic activities in the future, which will affect the value and development of student potential. With this major system, it is hoped that it can help schools and students minimize errors in determining and choosing a major. Based on the problems described above, the authors want to apply the Naïve Bayes method, which will produce a high level of accuracy in determining new student majors more effectively and efficiently
The Stocks Saving Simulation based on Historical Data Web-based
No full textThis study aims to simulate the calculation of saving stocks based on historical data for the past 10 years for the period January 2010 - January 2020, because saving simulations based on historical data are still very rare, so a simulation application for saving stock calculations based on historical data is made that can help customers. investors in simulating the calculation of saving stocks so that it can be used as learning to determine how to save the right way that can produce a good return. This application is created using a waterfall model. From the application made, it is expected to know the good return results of the 10 issuers used in this study, and in making basic applications on user requirements obtained through several respondents through online questionnaires and processed with requirement elicitation techniques. With the application of a stock saving calculation simulation application, it is hoped that it can be a lesson for investors in saving stocks and can also be a lesson for potential investors and can also make it easier for investors to do calculations because the calculation process is computerized
Collaborative E-Learning for Tangerang Vocational High School
Full text linkInformation technology is no stranger in modern times. The emergence of various learning media has promoted the application of communication and information technology learning media called e-learning in vocational high schools (SMK). E-learning is learning that uses technology. The E-Learning of Tangerang Vocational High School (SMK) uses independent E-Learning learning media. In this research, the methods used are descriptive qualitative and descriptive statistical analysis. The research goal is to develop a collaborative E-Learning learning model for Tangerang Vocational High School (SMK) as a learning model. The sample included 375 students and 22 vocational high schools (SMK) Tangerang
Electronic Attendance with Android-Based QR Code at STMIK Pringsewu to Improve Student and Lecturer Discipline in Lectures
Full text linkTechnology can be used in various fields. One of them is in the field of Education. In this case, it can be done to process databases, and process academic information data, for example: lecture systems, assessment systems, curriculum information, education management or learning materials. It can also implement the system gradually starting from a smaller scope to expanding, making it easier to manage the use of IT in the process of providing education. Electronic Attendance with an Android-based QR code is an application which is able to read the QR code from each user or student scanned by the lecturer in the attendance list process for a course. The development of the Electronic Attendance system with QR code based on Android uses the Software Development Life Cycle (SDLC) system and is described by the Data Flow Diagram (DFD), Entity Relationship Diagram (ERD) and Flowchart models followed by web design using Hypertext Preprocessor (PHP) programming, and My Structured Query Language (MySQL), Javascript, and Cascading Style Sheet (CSS) which produces responsive websites and is converted with android studio into application
An Automatic Environment Monitoring System Using a MobileNet Transfer Learning
Full text linkThe universities have an important role to encourage and support the Sustainable Development Goals (SDGs). UIN Alauddin Makassar as one of the universities in Indonesia establishes a green campus program to support it. An automatic environment system was built to ensure the cleanliness of the university environment. A comfortable and healthy work environment is expected can improve the productivity and motivation of the academic civities. The system was built using a MobileNet architecture that using a transfer learning approach. It can detect the cleanliness level of the environment which consists of three classes: “Cleanâ€, “Less_Cleanâ€, and “Dirty†in real-time. The dataset used to train the model was obtained by capturing images of the environment around the university. The best result of the model was achieved by using an Adam optimizer with applying a dropout in the last layer of the network. The total accuracy of the model is about 83%
Information System Design of Online Motorcycle and Car Repair Shop Using Dijkstra Method
Full text linkNow more people are using motorized vehicles. In addition, the use of technology is also increasing, people are increasingly experiencing fast-paced services. However, in the midst of busy society and online services, some services still have to be done manually, one of which is register for a motorcycle or car repair shop. There are still many people difficult to find the right, closest, and comfortable with the needs of their vehicle. With the existing problems, a vehicle service ordering system is needed that can serve the community quickly and practically, which can be accessed by many people, especially in Tangerang City. With a vehicle service ordering system for motorcycles or car repairshop, people can easily find a repair shop that is the closest to their location and can order without having to wait in long queues. The design of the system for the closest repair shop locations uses the Dijkstra method. The workings of Dijkstra's Algorithm is to create a path to one optimal node at each step. Dijkstra's algorithm has the property to find the point whose distance from the starting point is the shortest. To find out whether the system has been accepted and has met the requirements, the system is tested using the User Acceptance Test (UAT) method, and from the test results, 85.1% of users are satisfied with the system
Decision Support System Determines The Quality Of The House In Pringsewu District Using The WASPAS Method
Full text linkThe quality of the Flats is a concern of every citizen and related health offices who need healthy flats. To determine the quality of a flat is declared healthy or unhealthy, three criteria are used, including: housing components, housing facilities, and behavior. In this study, 5 samples were used to determine the quality of the flats, from the calculation results obtained 2 houses that were declared healthy and 3 houses were declared unhealthy. The WASPAS method is applied to determine the quality priority of healthy flats. In this study, researchers used several criteria including area, environment, infrastructure, location, security. The alternatives in this study are, Flat A, Flat B, Flat C, Flat D and Flat E. From these calculations, the results obtained from the analysis determine a healthy apartment using the WASPAS (Weight Aggregated Sum Product Assessment) method. The following: 1. Flat A gets a score of 6.0144, 2. Flat B gets a score of 6.0117, 3. Flat C gets a score of 5.5871, 4. Flat E gets a score of 5.1253. 5. Apartment D received a score of 4,8253.5.
From the calculation results, the WASPAS method can be an input for the related health offices to follow up on the priority of healthy flats so that it is easier for people to choose healthy flats