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  • UI/UX Design Using User-Centered Design Method on Staycation Website

    Authors: Herry Saputra, Mohamad Algipani, Alfi Naga Mulya, Halena Fauziah Zafira

    DOI: 10.1109/INCITEST64888.2024.11121477

    Abstract

    This study focuses on creating a UI/UX design for a web-based Staycation (You Can Stay Plus Staycation) application. This research is a UI/UX design for Staycation, which can help users find hotels, apartments, and houses. The method used for the staycation application is User-Centered Design (UCD) method. UCD method focuses on user needs which the designs developed through can be optimized and focus on end-user needs. This research aims to create a friendly design that is easy to use and comfortable. This design is expected to make it easier for users to find vacation spots and places to stay. It can be concluded that with this application, users can find it easier to find vacation spots and places to visit. © 2024 IEEE.

    Author keywords

    – ; UCD; UI/UX design; web-based staycation

    This article can be accessed at https://www.scopus.com/pages/publications/105015654435

  • Augmented Reality Based Indoor Navigation System using Point Cloud Localization for Efficient Item Search in Warehouse

    Authors: Richi Dwi Agustia, Laurentyus Bryan Hermanto, Hanhan Maulana

    DOI: 10.1109/INCITEST64888.2024.11121513

    Abstract

    Locating specific items within expansive warehouse spaces poses a significant challenge, particularly when items are dispersed across different sections. Traditional 2D map-based navigation lacks depth and detail, leading to inefficiencies as workers spend considerable time navigating to find items within an expansive warehouse. The study aims to develop an AR-based navigation system using point cloud technology, using ARCore and Immersal SDK for mapping and localization. ARCore utilized to tracks the device’s position and orientation in 3D space, aiding in AR experiences by overlaying navigation cues in real-time. The Immersal SDK is used to enable spatial and visual mapping, integrating digital content with the physical environment through point cloud localization. To conduct pathfinding analysis, the navmesh in Unity is used, combined with the Catmull-Rom spline interpolation algorithm to create smooth navigation paths. To map a space, in this case, a warehouse, an immersal mapper is used, where a camera captures objects in the real world in the form of a point cloud. Each point in the point cloud reflects latitude and longitude. This point cloud will be stored in immersal cloud services for use in the localization process after the point cloud is processed through Unity software. Testing results indicate the application effectively assists navigation, offering smooth trajectory adjustments around obstacles, though it currently lacks rerouting capabilities when paths are blocked. Time efficiency testing revealed that the application significantly reduces the time taken to locate items compared to the manual method, the mean time taken for each task was consistently lower in the group that used the app compared to the group that did not. Specifically, the time reduction was more pronounced for more time-intensive tasks, such as Item 3, where the mean completion time decreased from 458.75 seconds without the app to 208.25 seconds with the app. The average distance taken for all items is consistently lower in the group using the application compared to the group not using it, the average distance for Item 3 decreased from 151.21 meters without the application to 69.3 meters with the application. The ANOVA test was conducted to show the significant effect between those using the application and those not using it. The results indicated that the p-value was below 0.05, which significantly suggests that the application helps reduce the time and distance taken when searching for items. © 2024 IEEE.

    Author keywords

    Augmented reality; immersal mapper; immersal SDK; navigation mesh; pathfinding

    This article can be accessed at https://www.scopus.com/pages/publications/105015876318

  • Prediction Models of Acceptance Student Scholarships in University for Students K-12 Using Decision Tree Learning

    Authors: Agus Nursikuwagus, Tono Hartono, Agus Setiana, Muhammad Agil Alfariski, Refaldi Satria Gumelar, Muhammad Rizdky Maulady

    DOI: 10.1109/INCITEST64888.2024.11121501

    Abstract

    Receiving scholarships for high school students is one of the key processes in obtaining scholarships at a university; therefore, the process of monitoring and evaluating scholarship recipients at the high school level is very necessary. We haven’t used machine learning for prediction yet. A fair and suitable process is crucial to support the justification candidate. This research aims to provide prediction learning models based on the proposed dataset. We leveraged classification techniques like decision trees base, naive bayes learning, and support vector learning. As a result of the task, we received a variety of accuracy levels, ranging from tree learning to support vector machine. Each model presents accuracy values of 1.00,1.00, 1.00,0.81, and 0.99, in that order. SVM outperforms the other models, particularly in reducing false predictions. The dataset consists of 547 instances, with 70% of them in the training dataset and 30% in the testing dataset. Future research can leverage deep learning methods or large language machines. Providing the tuning parameter is crucial for enhancing classification accuracy. © 2024 IEEE.

    Author keywords

    classification learning; confusion matrix; decision tree; models; prediction

    This article can be accessed at https://www.scopus.com/pages/publications/105015870242

  • The Utilization of Data Visualization in Klinik Keluarga within the Cianjur District

    Authors: Alif Finanditha, Dian Dharmayanti, Juliadit Syahputra

    DOI: 10.1109/INCITEST64888.2024.11121481

    Abstract

    The objective of this research is to develop effective and efficient visualizations to assist the Promkes & Marketing Coordinator, and Warehouse Coordinator in acquiring the necessary information in a more quick and precise manner to improve the decision-making process. Based on the results of interviews conducted with the Promkes & Marketing Coordinator, the Warehouse Coordinator said that the current form of information presentation is a graph. However, this form of presentation has not helped the Promkes & Marketing Coordinator and Warehouse Coordinator perform their duties and misinterpret the information. With so much data that needs to be processed, this results in the Promkes & Marketing Coordinator and Warehouse Coordinator taking longer to get information, which hinders the tasks of the Promkes & Marketing Coordinator and Warehouse Coordinator. In this research, the method used adapts from 7 steps of data visualization adapted to the research to build a good visualization according to the needs. The knowledge extraction process is performed using descriptive statistics and data mining techniques. The implementation of the visualization design is done through the creation of a prototype, which is then tested through the usability testing method. The test results indicate that the data visualization prototype enables health promotion & marketing and warehouse coordinators to grasp the necessary information more swiftly. © 2024 IEEE.

    Author keywords

    data mining; data visualization; usability testing

    This article can be accessed at https://www.scopus.com/pages/publications/105015855737 

  • Exhaust Gas Detection System in Cabin Car Based on Internet of Things

    Authors: Dedena Hirawan, Audy Revi Nugraha

    DOI: 10.1109/INCITEST64888.2024.11121491

    Abstract

    Driving a car is a daily transportation activity carried out by the Indonesian people. Currently, there is no feature on the car to check and provide warnings about the air quality in the cabin. The purpose of this study is to build an exhaust gas detection system in the car cabin by analyzing the air using the MQ-135 and MQ-7 sensors. This study uses a prototyping model for software and hardware development. The prototyping model is quite effective at every stage, from data collection stage to system testing and implementation stage. This study focuses on developing a system to detect exhaust gases inside car cabins, as there is currently no feature in cars to monitor cabin air quality. The system uses MQ-135 and MQ-7 sensors to analyze air quality and detect harmful gases such as Carbon Monoxide (CO), Carbon Dioxide (CO2), Ammonia (NH3), and Nitrogen Oxides (NOx), which result from fossil fuel combustion. If gas levels exceed safe limits, the system provides a warning and recommends opening the windows to improve air circulation. The goal is to help maintain healthy air quality in car cabins, preventing negative health impacts on passengers, and allowing car owners to monitor vehicle conditions for safe daily use. © 2024 IEEE.

    Author keywords

    Car Cabin; Detection System; Exhaust Gas; Internet of Things

    This article can be accessed at https://www.scopus.com/pages/publications/105015892910

  • Utilization of Database Replication for Performance Improvement and Backup of Higher Education Academic Information System Database

    Author: Andri Heryandi

    DOI: 10.1109/INCITEST64888.2024.11121494

    Abstract

    Currently, a higher education institution has an Academic Information System to support the implementation of educational processes. Over time, as the information system is used, the amount of stored data also increases. This leads to slower database services, which subsequently affects the performance of the information system. In terms of security, a database must also be prepared to face potential attacks or disruptions that could be damaging. Therefore, the database used in an information system must support steps to minimize the impact of such attacks or disruptions, for example, through backup measures. However, implementing backup procedures in a database can impact the overall performance of the information system, such as causing downtime during the backup process. This research creates a database server architecture that can enhance database performance (availability, speed, and security), thereby improving the performance of the academic information system while also supporting the backup process without compromising the performance of the system information using database replication technology. © 2024 IEEE.

    Author keywords

    academic information system; backup; database; replication; security

    This article can be accessed at https://www.scopus.com/pages/publications/105015890567

  • Tempeh Chips Production Optimization System using the Simplex Method

    Authors: Gentisya Tri Mardiani, Rina Susanto

    DOI: 10.1109/INCITEST64888.2024.11121428 

    Abstract

    In producing tempeh chips, the company has limitations such as the availability of raw materials and daily production capacity. The simplex method is used to calculate the optimal amount of production in one day and find out how many products are produced. The aim of this research is to assist Production Managers in calculating the amount of production time carried out and knowing the optimal number of products produced from each production. Based on the results of this analysis has been implemented then the application of the Simplex Method can be implemented to produce 1x production of salty tempeh chips and 2x production of sweet tempeh chips with a total production of 3500 kilos per day so that the company can maximize the use of raw materials, machines and production capacity and optimize the number of products produced. The system to be built has three users, namely Production Manager, Production Staff, and Warehouse Staff. The output of the system that will be built is to assist the Production Manager in calculating optimal production requirements every day, as well as assisting in making production plan decisions for each day. © 2024 IEEE.

    Author keywords

    decision making system; optimization; production; raw material; simplex method

    This article can be accessed at https://www.scopus.com/pages/publications/105015779398

  • Comparative Analysis of Interactive Map Data Loading Using the GeoJSON Method for West Java New Entrepreneurs

    Authors: Angga Setiyadi; Eko Budi Setiawan

    DOI: 10.1109/INCITEST59455.2023.10396976

    Abstract

    The purpose of this study is to analyze interactive maps using the GeoJSON method and without using GeoJSON for new entrepreneurs in West Java. The flow of the stages of this research consists of three parts, namely analyzing the code, implementing the code, and testing the code that has been created using GeoJSON and without GeoJSON. The results obtained in this study are using GeoJSON to display data on an interactive map faster than without using GeoJSON. The downside of using GeoJSON on an interactive map is that the app developer is more likely to write down the source code on loading the interactive map. © 2023 IEEE.

    Author keywords

    Comparative Analysis; GeoJSON; Interactive Map; New Entrepreneurs

    This article can be accessed at: https://www.scopus.com/pages/publications/85185197883

  • Implementation of the K-Means Clustering Technique Using RFM Attributes to Enhance Donor Retention at Masjid Nusantara

    Authors: Iqbal Muhammad Farisi, Sri Supatmi

    DOI: 10.1109/INCITEST64888.2024.11121472

    Abstract

    The efforts aimed at donor retention are a fundamental aspect of Customer Relationship Management (CRM) strategies that enhance organizational effectiveness. This research concentrated on entities that have traditionally emphasized the acquisition of new donors over the retention of current donors, a methodology that can hinder long-term viability. By categorizing donors and formulating targeted retention strategies, this research seeks to redirect the emphases from donor acquisition to retention, by using the K -Means clustering methodology along with the RFM (Recency, Frequency, Monetary) framework. The descriptive research adopting a quantitative paradigm followed the CRISP-DM process, which included the data selection, preprocessing, transformation, processing, and analysis stages. The data analysis found four distinct clusters of donors, each of which is equipped with customized retention strategies based on their respective RFM scores. These strategies of retention contribute to pragmatic outcomes by empowering organizations to increase donor loyalty, improve donor engagement, and ultimately, facilitate their mission of building and maintaining mosques. This study demonstrates that prioritizing donor retention, which is supported by an empirically based methodology, has potential to enhance an organization’s performance and sustainable success. © 2024 IEEE.

    Author keywords

    CRISP-DM; CRM; Data Analysis; Donor Retention; K-Means Clustering; RFM

    This article can be accessed at https://www.scopus.com/pages/publications/105015849404

  • A Spherical Fuzzy TOPSIS Entropy Weighted for Failure Mode and Effects Analysis

    Authors: Gabriel Sianturi; Agus Riyanto; M. Yani Syafei; Julian Robecca; Alam Santosa

    DOI: 10.1109/INCITEST59455.2023.10396868

    Abstract

    The aim of this paper is to implement a Spherical Fuzzy Sets (SFS) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) approach in the Failure Mode and Effects Analysis (FMEA) process. The SFS can provide a larger domain for decision-makers to assign independent membership degrees, non-membership degrees, and hesitancy degrees. The SFS are combined with TOPSIS to obtain the rank all of the failure modes with respect to their distances to ideal solutions and relative closeness ratios. In addition, the entropy objective weight for SFS is integrated into SFS TOPSIS for determining the risk factors weights. The proposed approach is utilized to prioritize and rank the potential failure of an injection molding machine. The implementation of SFS-TOPSIS and entropy objective weight approach can overcome the vagueness and uncertainty of data during FMEA evaluation process and improve FMEA to be more flexible and reasonable. © 2023 IEEE.

    Author keywords

    entropy; fmea; injection molding; spherical fuzzy sets; topsis

    This article can be accessed at: https://www.scopus.com/pages/publications/85185197336