PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic

Storyboard Design of Android-Based Learning Multimedia Integration Application Using Standard Process Tutorial Model

2023-03-29T01:43:03+00:00

Bina Pribadi Islam is a subject taught in Islamic elementary schools with the aim of improving students' spiritual well-being through guidance from teachers or mentors. Islamic elementary schools have an educational system designed by the Ministry of National Education and adapted to Islamic law. In the process of learning Bina Pribadi Islam, there is a need for a strategy to increase students' motivation and interest by using a multimedia application that includes elements such as text, audio, graphics, video, and animation tailored to the standard process tutorial model. To create an interactive multimedia application, multimedia design should be prepared in accordance with the tutorial model. Therefore, to produce a good application, a storyboard design needs to be created first that is tailored to the tutorial model to facilitate the application's development. Based on the storyboard design created according to the tutorial model, three main menus are produced as the characteristic features of the tutorial model, namely introduction, tutorial material, and exercises. Each menu produces several sub-menus tailored to the material in the Bina Pribadi Islam subject.

Pi Hole on SOE Computer Network using Raspberry Pi 3 Model B+ to Optimize Bandwidth Management and Improve Employee Performance

2023-03-29T01:56:53+00:00

State-Owned Enterprises (BUMN) are government agencies that currently have computer networks and are supported by internet services, which are always used in the work process of BUMN employees. Along with the development of the Internet of Things (IoT) devices, good internet service is very much needed by BUMN as it will affect the performance of BUMN employees. However, the problem that often occurs in internet services in BUMN is slow internet speed, which hinders the work process of BUMN and decreases the performance of BUMN employees. It should be noted that good internet service depends on the bandwidth used, so it is very important to have good bandwidth management applied to the BUMN computer network. So far, BUMN have done several things related to bandwidth management, ranging from access restrictions, even distribution of bandwidth, and the implementation of an authentication system to connect to the BUMN internet network. However, some of these things are still not enough to guarantee no wasteful use of bandwidth, which occurs because when operating some work-supporting websites, various types of digital ads will automatically appear, consuming a significant amount of bandwidth. Therefore, in this Action Research study, a Pi Hole to control digital ads was implemented that can automatically appear and use large amounts of bandwidth. By using Raspberry Pi 3 Model B+, the development of Pi Hole will limit digital ads from appearing when accessing websites or other IoT devices used by BUMN so that bandwidth usage will be more optimal in BUMN work processes. This will also improve the performance of BUMN employees, where with maximum bandwidth, the work process of BUMN can be accelerated.

The Influence of Youtube Ads on Purchase Intention

2023-03-29T02:07:48+00:00

The high number of social media users on YouTube has made many companies interested in advertising on the platform. However, many YouTube users tend to skip the ads that are displayed. The main objective of this research is to determine the factors within YouTube ads that have an influence on Purchase Intention. This study uses a quantitative research method, with variables including Informativeness, Entertainment, Customization, Irritation, Advertising Value, Flow Experience, Brand Awareness, and Purchase Intention. The results of this research show that Informativeness has a significant influence on Advertising Value but not on Flow Experience. Meanwhile, Entertainment and Customization have a significant influence on both Advertising Value and Flow Experience, and Advertising Value, Brand Awareness, and Flow Experience have a significant influence on Purchase Intention. As for Irritation, this variable does not have a significant influence on Advertising Value and Flow Experience.

Optimization of Random Forest Prediction for Industrial Energy Consumption Using Genetic Algorithms

2023-03-29T02:37:53+00:00

Abstract

Saving electrical energy consumption in industries is crucial; hence, the prediction of industrial energy consumption needs to be performed. The random forest method can be applied to steel industry data to predict energy consumption. The purpose of this prediction is to increase energy savings in industries and optimize the performance of the random forest method. The results of the random forest show that the algorithm can predict energy consumption in industries effectively; however, it needs further optimization to achieve better predictions. Therefore, the genetic algorithm method will be used to optimize the previous method. The optimization results indicate that it is successfully conducted in terms of accuracy and kappa level. This optimization is beneficial to society, especially industrial companies.

Cluster Analysis Using Principal Component Analysis Method and K-Means to Find Out the Compliance Group of Property Tax

2023-03-29T03:00:58+00:00

Abstract

The village of Kendal has experienced a decline in local income due to the high rate of property tax arrears, with 226 taxpayers (19% of residents) known to have outstanding payments. Additionally, with 1,159 separate residents residing in 10 block areas with varying tax amounts, it has become increasingly difficult for the Village Apparatus to profile taxpayers based on their characteristics. To overcome these problems, a data analysis model based on Machine Learning technology will be developed using the Principal Component Analysis (PCA) Method combined with the K-Means method. The objective of this study is to create a cluster analysis model that can accurately map the characteristics of taxpayers, making it easier for the Village Apparatus to identify and assist residents who need to pay their property tax. This proposed solution will also simplify the reporting process to the central government regarding the estimated regional revenue sourced from property tax.

EfficientNetV2M for Image Classification of Tomato Leaf Deseases

2023-03-29T03:29:40+00:00

Favorable climatic conditions make tomato plants (Solanum Lycopersicon) a widely cultivated horticultural crop in Indonesia. However, the increase in tomato production is often accompanied by a decrease in both the quantity and quality of the plants, which can be caused by a variety of factors such as bacteria, fungi, viruses, and insects like Late Blight and Two-Spotted Spider Mite diseases that attack the tomato leaves. To help farmers identify leaf diseases that have similar characteristics, this study employs image processing with the Convolutional Neural Network (CNN) algorithm and transfer learning models. Specifically, the study uses the EfficientNetV2M transfer learning architecture which has superior parameter efficiency and training speed compared to other transfer learning models. Additionally, this study conducts four experimental scenarios on preprocessing, including green channel + CLAHE, green channel + Gaussian Blur, CLAHE without green channel, and Gaussian Blur without green channel. The dataset used in this study includes 5,176 images with three labels: Tomato Healthy, Tomato Late Blight, and Tomato Two-Spotted Spider Mite. These images were used to train and produce models, which were then tested using a different dataset from the trained dataset. The testing dataset included 30 image samples divided into three labels. Based on the test results of the four models with different scenarios, the best model was found to be the one with the green channel preprocessing scenario + CLAHE, which was able to precisely predict all 30 image samples with high accuracy.

Identification of Website-Based Product Sales Frequency Patterns using Apriori Algorithms and Eclat Algorithms at Rio Food in Bekasi

2023-03-29T08:18:01+00:00

Sales reports that are not managed automatically may hinder businesses from accurately determining their progress in the short or long term. With increasing community needs for a product, business owners have an opportunity to market their products to a larger audience. The abundance of data highlights the need for information to produce patterns that can be used as a reference for making decisions in buying products on the website. Data mining algorithms can provide support for analysis, which can help avoid inaccurate business progress reports. In this study, the Apriori and Eclat algorithms were applied to analyze frequent itemsets in association rule mining. The dataset used in this study consists of 20 transaction data from frozen food sales. The results showed that the combination of Nugget and Chicken Sausage itemsets were the most frequent, with higher support, confidence, and lift ratio values than the others. These results can be used as product recommendations that are most in demand by customers.