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The Development of Education Character Policy and Programs in Information Society of Kampung Cyber Yogyakarta Muhammad Amirrudin; Harun Harun; Muhammad Yasid; Surur Roiqoh; Fatkhul Sani Rohana
Jurnal Iqra' : Kajian Ilmu Pendidikan Vol 6 No 2 (2021): Jurnal Iqra' : Kajian Ilmu Pendidikan
Publisher : Institut Agama Islam Ma'arif NU (IAIMNU) Metro Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25217/ji.v6i2.1326

Abstract

This ariticle presents studies about the Strengthening Character Education policy and practised in Kampung Cyber Yogyakarta's information society. The aim of this research was to describe how character education policy materializes in Kampung Cyber community's efforts in developing character education programs. The research was a qualitative research with a case study approach. The data were obtained through interviews, observation and documentation in the field directly. The results were divided into two things according to the main study. First, related to the dimensions and second related to the results of character education development in Kampung Cyber. The results show that the development of character education in Kampung Cyber covered five primary characters and targeted three fundamental problems: foundational problems, structural problems and operational problems. In general, the product of character education in Kampung Cyber was positive, because they can increase social-communal awareness, improve religious practice, and the synergy of character education and its natural habituation. Keywords: Education Character Policy, Strengthening Education Character
Critical Success Factors in Implementing Employee Information System BasedOn E-Government in The Bureau of Public Affairs at The Regional SecretariatOf West Java Province Dea Melati; Entang Adhy Muhtar; Elisa Susanti
Jurnal Manajemen Pelayanan Publik Vol 4, No 1 (2020): Jurnal Manajemen Pelayanan Publik
Publisher : Universitas Padjadjaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24198/jmpp.v4i1.28003

Abstract

This research aimed to identify critical success factors in the implementation of EGovernment based on employee management information system in the Bureau of Public Affairs at the Regional Secretariat of West Java Province. Employee management information system is a process on managing information through the use of available resources within the organization. The formulation of the problem in this study is in its implementation in which various kinds of obstacles were found such as the difficulties in operating digital-based information system applications by each employee, also the inaccuracy of available data in information system. Qualitative method was used in this research by collecting data through literature review study, field research and interviewing four informants. They were the Head of the Public Affairs Bureau at the Regional Secretariat of West Java Province, the Head of Household Administration and Staffing, the administrator staff for management information system and a civil servant within the General Affairs Bureau. The research shows that the implementation of employee management information system based on e-government in the Bureau of Public Affairs at the Regional Secretariat of West Java province is not optimal because it has not been supported by competent human resources in the implementation of technology-based management information system therefore data accuracy is difficult to be achieved.  
Geographic Information Systems for Crime Prone Areas Clustering Heti Mulyani; Jajang Nurjaman; Muhammad Nugraha
JOIN (Jurnal Online Informatika) Vol. 5 No 2 (2020)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v5i2.599

Abstract

Crime is one of the problems that is quite complicated and very disturbing to the community. Crimes can occur at different times and places, making it difficult to track which areas are prone to such actions. K-means algorithm is used to cluster prone areas and Geographic Information System is used to map crime-prone areas. Web-based application is developed with the PHP programming language. The data used is quantitative data in the form of the number of crimes committed and the coordinates of the cases. The attributes of the crime used consist of five parameters: theft, mistreatment, rape, women and child protection cases and fraud. The results of this study are clustering areas into 3 cluster and mapping prone areas that is safe area, safe enough area and prone area. From the overall crime data for 2019 in Purwakarta district, it was found that 68.75% was safe, 18.75% was quite safe and 12.5% was prone area.
FoFA: Diet Information for Children with Autism with Semantic Technology in Android Based Application Lutfi Aristian Febrianto; Dewi Wisnu Wardani; Ardhi Wijayanto
JOIN (Jurnal Online Informatika) Vol. 5 No 2 (2020)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v5i2.615

Abstract

The number of people with autism in Indonesia increases by 0.15% or 6,900 children per year. One of the actions that can be done to overcome developmental disorders of children with autism is to do Feingold and Failsafe Diet, Specific Carbohydrate Diet (SCD diet), and Casein-Free Gluten Free diet (CFGF diet) on foodstuffs given to children with autism. There is a need for socialization and presentation of information regarding the regulation of food items given to children with autism. Currently, there is no presentation of information in the form of mobile-based applications as a forum for parents to exchange information, especially those that utilize semantic technology. By utilizing semantic technology, the Food For Autism (FoFA) application was created to share knowledge for users related to food and beverage diet menus for children with autism. The test results show that the application of FoFA can apply semantic technology related to diet and food diets for children with autism.
Enhancement Design of Emotional Regulation of Students in Prevention of Pornographic Trends Through Information Services Solin, Ridwan; Firman, Firman; Syahniar, Syahniar
Journal of ICSAR Vol 4, No 1 (2020): January
Publisher : Department of Special Education

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

When this study was conducted, students were exposed to access to information via the internet, which negatively impacted pornography behavior. One example of media that counselors can do to improve student emotional regulation is designing guidelines for implementing attractive information services. This study aims to increase the regulation of student emotions in the prevention of pornographic tendencies through information services. This research uses research and development (R & D). The research model uses a 4-D development model. The type of data collected in this study is the type of data validity and suitability according to students' needs. The instrument of data collection in this study used a Likert scale questionnaire and group discussion. The study population was students of SMK Negeri 1 Padang. The study sample was a class XI student of SMK Negeri 1 Padang. The study results found that providing information service guidelines to improve student emotion regulation in preventing the tendency of pornography was effective in increasing the regulation of students' emotions in preventing pornographic tendencies.
Penerapan Metode Building Information Modeling (BIM) Pada Pembangunan Gedung Integrated Laboratory for Natural Science and Food Technology Universitas Jember Agam Risza Adhitama; Anik Ratnaningsih; Willy Kriswardhana
Jurnal Rekayasa Sipil dan Lingkungan Vol 4 No 2 (2020): Jurnal Rekayasa Sipil dan Lingkungan
Publisher : Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/jrsl.v4i2.11683

Abstract

Universitas Jember built high rise building and had a high complexity of work, it requires a construction project management to simplify and minimize errors in its process. Project management performance can be described through the concept of Building Information Modeling (BIM). The application of BIM method in this study used Revit Architecture for software support to obtain volume at each job in the monitoring process to determine MC0 and termin setting processes. The data used namely shop drwaning / forcon which is used as a reference in model. Building modeling in this study is divided into 3 modeling phases, namely lower structure modeling, upper structure and architecture. Based on the model, a tie beam volume was 26.74 m3 with reinforcement was 4,361 kg, 1st floor column concrete modeling was 52.87 m3 with reinforcement was 12.176,39 kg and perimeter wall volume on the 1st floor was 320.71 m2. The error that appeared in the calculation of the concrete volume in the BIM modeling with the conventional method is 0% while the error that appears in the reinforcement calculation is 0-0.042%.
A forecasting of stock trading price using time series information based on big data Soo-Tai Nam; Chan-Yong Jin; Seong-Yoon Shin
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 3: June 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i3.pp2548-2554

Abstract

Big data is a large set of structured or unstructured data that can collect, store, manage, and analyze data with existing database management tools. And it means the technique of extracting value from these data and interpreting the results. Big data has three characteristics: The size of existing data and other data (volume), the speed of data generation (velocity), and the variety of information forms (variety). The time series data are obtained by collecting and recording the data generated in accordance with the flow of time. If the analysis of these time series data, found the characteristics of the data implies that feature helps to understand and analyze time series data. The concept of distance is the simplest and the most obvious in dealing with the similarities between objects. The commonly used and widely known method for measuring distance is the Euclidean distance. This study is the result of analyzing the similarity of stock price flow using 793,800 closing prices of 1,323 companies in Korea. Visual studio and Excel presented calculate the Euclidean distance using an analysis tool. We selected “000100” as a target domestic company and prepared for big data analysis. As a result of the analysis, the shortest Euclidean distance is the code “143860” company, and the calculated value is “11.147”. Therefore, based on the results of the analysis, the limitations of the study and theoretical implications are suggested.
Thriving information system through business intelligence knowledge management excellence framework Abdul Karim Mohamad; Mailasan Jayakrishnan; Mokhtar Mohd Yusof
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 1: February 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i1.pp506-514

Abstract

In the current digitalization dilemma of an organization, there is a need for the business intelligence and knowledge management element for enhancing a perspective of learning and strategic management. These elements will comprise a significant evolution of learning, insight gained, experiences and knowledge through compelling theoretical impact for practitioners, academicians, and scholars in the pertinent field of interest. This phenomenon occurs due to digitalization transformation towards industry revolution 5.0 and organizational excellence in the information system area. This research focuses on the characteristic of a comprehensive performance measure perspective in an organization that conceives information assessment and key challenges of Business Intelligence and Knowledge Management in perceiving a relevant organizational excellence framework. The dynamic research focusing on the decision-making process and leveraging better knowledge creation. The future of organization excellence seemed to be convergent in determining the holistic performance measure perspective and its factors towards industry revolution 5.0. The research ends up with a typical basic excellence framework that will mash up some characteristics in designing an organizational strategic performance framework. The output is a conceptual performance measure framework for a typical decision-making application for organizational strategic performance management dashboarding.
Spatial information of fuzzy clustering based mean best artificial bee colony algorithm for phantom brain image segmentation Waleed Alomoush; Ayat Alrosan; Ammar Almomani; Khalid Alissa; Osama A. Khashan; Ahmad Al-nawasrah
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 5: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i5.pp4050-4058

Abstract

Fuzzy c-means algorithm (FCM) is among the most commonly used in the medical image segmentation process. Nevertheless, the traditional FCM clustering approach has been several weaknesses such as noise sensitivity and stuck in local optimum, due to FCM hasn’t able to consider the information of contextual. To solve FCM problems, this paper presented spatial information of fuzzy clustering-based mean best artificial bee colony algorithm, which is called SFCM-MeanABC. This proposed approach is used contextual information in the spatial fuzzy clustering algorithm to reduce sensitivity to noise and its used MeanABC capability of balancing between exploration and exploitation that is explore the positive and negative directions in search space to find the best solutions, which leads to avoiding stuck in a local optimum. The experiments are carried out on two kinds of brain images the Phantom MRI brain image with a different level of noise and simulated image. The performance of the SFCM-MeanABC approach shows promising results compared with SFCM-ABC and other stats of the arts.
Local information pattern descriptor for corneal diseases diagnosis Samer Kais Jameel; Sezgin Aydin; Nebras H. Ghaeb
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 6: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i6.pp4972-4981

Abstract

Light penetrates the human eye through the cornea, which is the outer part of the eye, and then the cornea directs it to the pupil to determine the amount of light that reaches the lens of the eye. Accordingly, the human cornea must not be exposed to any damage or disease that may lead to human vision disturbances. Such damages can be revealed by topographic images used by ophthalmologists. Consequently, an important priority is the early and accurate diagnosis of diseases that may affect corneal integrity through the use of machine learning algorithms, particularly, use of local feature extractions for the image. Accordingly, we suggest a new algorithm called local information pattern (LIP) descriptor to overcome the lack of local binary patterns that loss of information from the image and solve the problem of image rotation. The LIP based on utilizing the sub-image center intensity for estimating neighbors' weights that can use to calculate what so-called contrast based centre (CBC). On the other hand, calculating local pattern (LP) for each block image, to distinguish between two sub-images having the same CBC. LP is the sum of transitions of neighbors' weights, from sub-image center value to one and vice versa. Finally, creating histograms for both CBC and LP, then blending them to represent a robust local feature vector. Which can use for diagnosing, detecting.

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