Android-based Mobile Application Research Articles

Efhamni: A Deep Learning-Based Saudi Sign Language Recognition Application.

Deaf and hard-of-hearing people mainly communicate using sign language, which is a set of signs made using hand gestures combined with facial expressions to make meaningful and complete sentences. The problem that faces deaf and hard-of-hearing people is the lack of automatic tools that translate sign languages into written or spoken text, which has led to a communication gap between them and their communities. Most state-of-the-art vision-based sign language recognition approaches focus on translating non-Arabic sign languages, with few targeting the Arabic Sign Language (ArSL) and even fewer targeting the Saudi Sign Language (SSL). This paper proposes a mobile application that helps deaf and hard-of-hearing people in Saudi Arabia to communicate efficiently with their communities. The prototype is an Android-based mobile application that applies deep learning techniques to translate isolated SSL to text and audio and includes unique features that are not available in other related applications targeting ArSL. The proposed approach, when evaluated on a comprehensive dataset, has demonstrated its effectiveness by outperforming several state-of-the-art approaches and producing results that are comparable to these approaches. Moreover, testing the prototype on several deaf and hard-of-hearing users, in addition to hearing users, proved its usefulness. In the future, we aim to improve the accuracy of the model and enrich the application with more features.

Development of Android-Based Mobile Learning Media Using ADDIE Model on Static Fluid Topics for High School 11th Grade Students

This research and development study aimed to create a mobile learning application based on the Android platform to facilitate the teaching and learning of static fluid concepts. The ADDIE (Analysis, Design, Development, Implementation, and Evaluation) model was employed as the framework for the research methodology. The data collection instruments included validation questionnaires completed by subject matter experts, media experts, physics teachers, and students. These were administered during small-group and large-group trials conducted with 11th-grade science students at MAN 1 Lotim. The end product was an Android-based learning app that received an overall good rating with a total score of 82. Evaluation by media experts deemed it good, with a score of 60 out of a maximum of 75. Physics teachers who validated the app rated it as very good/effective with a score of 52. During the large group trial with students, the app gained a high score of 1759, averaging 4.31 which falls into the very interesting category. Based on the validation results and feedback obtained, it can be concluded that the Android-based mobile learning application developed in this study is suitable, effective, and practical to be utilized as an instructional tool for teaching static fluid concepts to high school 11th-grade students in physics education programs.

Perancangan Sistem Emergency Call untuk Pengendara Bermotor Berbasis Mobile

The progress of land transportation, especially motorized vehicles, has a great influence on people's welfare. Currently motorized vehicles have a large contribution to the development of transportation in Indonesia. The increasing number of vehicles always results in problems such as flat tires, running out of petrol or breaking down and the number of these incidents always increases. When problems occur on the highway, drivers always have difficulty finding locations and information about relevant places in order to ask for help with the problems they are facing. This research aims to enable motorized vehicle users to have an Android-based mobile application that is useful for providing location information and related parties to speed up the rescue process. The application that will be developed has a emergency call feature for users to service providers or relevant locations according to the driver's problem. Not only that, this system is also a business platform for those who want to join the merchant feature in it. In this mobile application study, the author will utilize the Google Maps API so that he can search and recommend the nearest place for motorists to seek help. This research was carried out from the analysis, design, implementation, to testing stages.

Constructing an elderly health monitoring system using fuzzy rules and Internet of Things

Monitoring the health of the elderly using wearable sensors and Internet of Things (IoT) devices necessitates the collection of data from various sources, thereby increasing the volume of data to be gathered at the monitoring center. As previously elucidated, the system exhibits high accuracy in measuring variables such as blood oxygen saturation (BOS) and heart rate (HR), as well as demonstrating proficient accuracy in implementing fuzzy rules to detect the “stable” or “unstable” condition of elderly patients. Therefore, by integrating wearable sensors and IoT devices into the elderly health monitoring system, we can enhance the quality of monitoring and provide more timely healthcare solutions tailored to the elderly population’s needs. The integration of fuzzy rules and IoT technology into the elderly health monitoring system offers an efficient and effective solution for continuous health surveillance. In this research, we integrated fuzzy rules and IoT technology into the elderly health monitoring system using parameters such as BOS and HR, through the integration of MAX30100 sensors and ESP32 microprocessors. The implementation of fuzzy rules resulted in nine rules indicating whether an elderly patient is in a “stable” or “unstable” condition. The methodology involved (1) component preparation, (2) device accuracy analysis, (3) fuzzy rule development, (4) Android-based mobile application development, (5) fuzzy rule accuracy analysis, and (6) cost analysis. Experimental results indicated a device accuracy of 98.89% in measuring BOS and HR variables compared to medical devices and a fuzzy rule accuracy of 96% in detecting whether the patient’s condition is “stable” or “unstable.” Based on the experimental findings, the elderly health monitoring system provides a user-friendly, precise, and cost-effective solution to enhance the quality of life for the elderly population.

Smartphone-based colorimetric detection platform using color correction algorithms to reduce external interference

Smartphone-based digital image colorimetry is a powerful, fast, low-cost approach to detecting target analytes. However, lighting conditions and camera parameters easily affect the detection results, significantly curtailing its applicability in multiple scenarios. In this study, an Android-based mobile application (SMP-CC) is developed, which offers a comprehensive package that includes image acquisition, color correction, and colorimetric analysis functions. Using a custom color card, a built-in algorithm in SMP-CC can minimize the color difference between the standard color block image captured by different smartphones under different lighting conditions and the standard value by an LS171 colorimeter less than 4.36. The algorithm significantly eliminates the impacts of external lighting conditions and differences in cell phone models. Furthermore, the feasibility of SMP-CC was verified by successful colorimetric detection of urine pH, glucose, and protein, demonstrating its potential in smartphone-based digital image colorimetry.

Android-Based Mobile Learning Application Using App Inventor on Computer Operating System Material: The Development and Validity Study

Mobile learning apps are widely acknowledged for their effectiveness in enhancing learning results. This study aims to develop and validate an Android-based mobile learning app for computer operating system principles. Using the user-friendly App Inventor platform known for visual programming, it integrates interactive modules and multimedia for diverse learning styles. The study adopted a Research and Development approach following the ADDIE model (analysis, design, development, implementation, and evaluation). The research was conducted at Universitas Negeri Padang and Universitas Muhammadiyah Muara Bungo and involved 10 participants. The analysis of questionnaire-based data conducted by media and material experts categorized the Android-based learning media as "Appropriate", achieving an over-all average of 82.51% and 82.29%, respectively. Meanwhile, student evaluations rated this media as "Feasible" with a score of 82.72%. In conclusion, the development of this Android-based mobile learning application for computer operating system material demonstrates significant potential as an innovative educational tool. The validation process highlighted its potential effectiveness and offered valuable recommendations to enhance its educational value. These findings make a meaningful contribution to the ongoing discourse surrounding the integration of technology-driven learning approaches into traditional education, benefiting educators and developers seeking to create impactful mobile learning experiences.

Exploring community satisfaction in building an innovative android-based mobile survey application for people travelling to Mentawai Island

This research aims to develop and evaluate an android-based mobile survey application to measure passenger satisfaction with transportation service standards to Mentawai Island. The application that has been developed will help in the evaluation process so that the improvement of sea transportation services can be improved. This study used the 4D development model and involved 30 passengers of the Mentawai Fest Ship as research subjects. The research instruments used were a validation questionnaire and a practicality test. A survey of public satisfaction with transportation services to Mentawai Island using an Android-based application will be developed, implemented, and evaluated. The results show that the application effectively meets the community's needs, shows high validity, and provides a convenient feedback mechanism for users. Overall, these findings contribute to efforts aimed at improving the quality of transportation services and the overall passenger experience.

ENSS (Expanded Nursing Stress Assessment) version 1,0: An Android-Based Mobile Application Efficient Stress Assessment in Nurses

The nursing profession is a profession that is prone to experiencing stress. Long work duration in accompanying patients is one of the factors that causes stress in nurses. To anticipate work-related stress problems, it is necessary to periodically identify the level of stress experienced by nurses. The use of mobile applications needs to be developed for easy and efficient stress assessment Android-based which are expected to help nurses identify the stress they are experiencing. The aim of this study was to developing a stress assessment application android-based to identify stress levels efficiently and effectively. This research uses design Research and Development (R&D) with a product development and validation approach through use trials on 34 nurses with a sampling method that is the total sample. Test use using the instrument System Usability Scale (SUS). The research developed an Android-based stress analysis application called ENSS version 1.0 with login features, stress questionnaire main menu and load interpretation. The test was tested by respondents with a score of 74.78 in the category of Acceptable or Admissible. The ENSS application has been developed and is suitable for use in the identification of stress levels in nurses. The application of ENSS is an assessment of the stress level of nursing so that proper management can be carried out.

Early detection of sweet potato weevil (Cylas formicarius) and scab diseases (Sphaceloma batatas) outbreak based on android application

Sweet potato weevil and scab disease are major pests and diseases that become obstacles for increasing sweet potato production in Indonesia. Recently, the incidence of both pest and disease attacks can be detected earlier by using an android-based mobile application. This study aims to assemble an android-based mobile application for early detection of the outbreak of sweet potato weevil and scab disease. This research was conducted in in Malang Regency, East Java, from September to December 2022. Research was carried out by survey, observation, literature studies, and interview with the leaders of farmer association, sweet potato farmers, and local agricultural extension staff. All basic data and supporting data as a trigger for the occurrence of the weevil and scab disease have been collected from the several sample areas. The information was arranged in clusters according to the priority of each variable then was entered into the android studio. The user must enter the supporting data based on the application program to find out the percentage of sweet potato weevil and scab disease. Understanding the predictive value of the incidence of major pests and diseases is required, so farmers can anticipate earlier and prepare appropriate, effective and efficient control technology. An-android mobile application version 1 for early detection of pest and disease which was successfully assembled was expected to be greatly assist sweet potato farmers for maintain their cultivation from yield losses due to C. formicarius and scab which can reduce the quantity and quality by up to 100%.

Development of an internet of things-based weather station device embedded with O<sub>2</sub>, CO<sub>2</sub>, and CO sensor readings

Weather station devices are used to monitor weather parameter conditions, such as wind direction, speed, rainfall, solar radiation level, temperature, and humidity. This article discusses the design of a customized weather station embedded with gas concentration readings, whereby the gas concentration measurement includes oxygen (O<sub>2</sub>), carbon dioxide (CO<sub>2</sub>), and carbon monoxide (CO). The measurements and data processing of input sensors were transmitted to an Arduino Uno microcontroller, and the input data were then remitted to Wemos D1 Mini to be uploaded to a cloud server. Furthermore, the gas sensors' characterization methods were also considered to reveal the obtained results of accuracy, precision, linearity, and hysteresis. An android-based mobile application was also designed for monitoring purposes. The system in our experiment utilized an internet connection with a field station, base station, and database server.

Goods Storage Rental Application (YourStorage) Using the React Native Framework

The increase in online business today with quite high transactions means that business actors who sell their merchandise through marketplaces need temporary storage space that does not have a place to store goods. Based on this, the aim of this research is to build a goods storage rental application to make it easier for business actors to rent storage space online with flexible time periods. This type of research is quantitative research where the system development method uses SCRUM and the software architecture used is service-oriented (Microservice). The results of this research are in the form of an Android-based mobile application and as many as 75% of business respondents feel that the “YourStorage” application can help, 68.75% (22) of respondents stated that the application could help in controlling where goods are stored and 71.87% (23) of respondents stated that the application could make it easier to store goods according to required size

Development of Home-based Rehabilitation Mobile App for Autism Spectrum Disorder

Autism Spectrum Disorder (ASD) children experienced postural balance disorders that significantly affects their quality of life. It is believed that poor gross motor development leads to the bare social interaction which is the core weakness of ASD. However, treatment expenses for ASD children such as movement therapy requires high cost. This may be due to the limited access to the rehabilitation facilities and medical professionals to evaluate the patient well-being. In this study, Android-based mobile application of home-based therapy intervention for ASD children as the main user where mainly monitored by the therapists and caretaker is developed. This mobile app includes movement modules which intended to conduct the therapy routine via the character animations and audio. Users can evaluate motor performance and psychological well-being of the patients which designed for both in-house and clinical settings. Based on the qualitative measurements, it is shows that the average System Usability Scale (SUS) score is 86.25% which indicates good usability.

Development and Usability of ‘Skeletopedia’ Mobile Application for Human Skeletal System

This study aimed to develop an android-based mobile learning application, Skeletopedia based on the cognitive constructivism and cognitive theory of multimedia learning and evaluated its usability as an educational tool for Form Five Biology students. The Skeletopedia was developed according to ADDIE model. It was designed to aid the Form 5 students in understanding and remembering the Latin terminology of human skeletal system as well as allowing them to visualise the human skeleton through three-dimensional augmented reality skeletal models. Two biology teachers were appointed to assess the face and content validity of the questionnaire and Skeletopedia, while 97 Form Five Biology students from Mara Junior Science College (MJSC) FELDA Trolak were selected as respondents for the field study. The usability questionnaire developed in this study had obtained high validity (κ = 1.00, CVI = 1.00) and reliability (Cronbach’s Alpha Coefficient = 0.970). The ‘Skeletopedia’ application had acquired high validity in terms of face validity (κ = 1.00) and content validity (CVI = 1.00). The findings show that perception of students on the design of the Skeletopedia have a mean score of 3.637 (SD = 0.443), the mean score for the content is 3.598 (SD = 0.444), the efficiency (mean = 3.650, SD = 0.434), and usefulness (mean = 3.652, SD = 0.430). In conclusion, Skeletopedia has a high content validity and reliability value. Students' perception of the Skeletopedia also has a high mean value. The findings of this study implied that the Skeletopedia is appropriate and effective to be used as a self-learning tool ubiquitously in enhancing students’ understanding of human skeletal system without time and space constraints due to its portability and flexibility.

Sistem Manajemen Daya Listrik Pada Pengamanan Kendaraan Berbasis Android

The power safety system is a series of monitoring and control technologies in the form of features designed to anticipate and increase power safety for drivers and maintain the stability of the vehicle's electrical system while driving. Several power security systems are generally found in most vehicles. Power security systems are a feature in maintaining the vehicle's electrical condition in addition to security devices for a machine against criminal acts such as theft on vehicles which are increasingly common nowadays so it is hoped that it will be able to minimize the shortage of power system requirements on the machine with control and monitoring carried out using an Android-based mobile application. For this reason, this research will create a power monitoring application and security system for vehicle engines in anticipation of additional power consumption when installing engine security against criminal acts through application-based control. The output produced in this research is an Android mobile application as well as a security system device along with power consumption calculations.

Recommendation System for Mobile Applications Tour Guide and Travel Services using Demographic Filtering and Content-Based Filtering Methods based on Android

This research aims to build a tourism service recommendation system by providing recommendations for tour guides and tourism destinations using machine learning recommendation system methods. The recommendation system method in this research uses the demographic filtering method to recommend tour guides using a model with three stages, namely filtering, scoring and sorting the tour guide data category. At the scoring stage, it is carried out using a decision-making system method using the Simple Additive Weighting method to weight the tour guide value with the weighting value of each criterion in the tour guide data. This research also applies a content-based filtering method using a model with two stages, namely training and recommendation. The training stage uses tf-idf weighting and the recommendation stage uses cosine similarity to recommend tourism spots based on the similarity of metadata for each item. In using the recommendation system, the data will focus on collecting tour guide data and data on tourist attractions selected by the user. This data will be processed by a recommendation system using demographic filtering and content-based filtering methods. Through the Simple Additive Weighting method in demographic filtering and tf-idf weighting with consistent similarity in content-based filtering, this research found personalized recommendation results so that the level of accuracy of the recommendation results becomes more personal and accurate. The results of this research provide a recommendation system for tourist guides and tourist attractions which is implemented into an Android-based mobile application that can be used to meet tourists' needs.

Android Application for Tomato Leaf Disease Prediction Based on MobileNet Fine-tuning

Tomato is one of the most well-known and widely cultivated plants in the world. The result of tomato production is affected by the conditions of the plants when they are grown. It may decrease due to leaf plant disease caused by climate change, pollinator decrease, microbial pets, or parasites. To prevent this, an image-based application is needed to identify tomato plant disease based on visually unique patterns or marks seen on leaves. In this paper, we proposed a CNN fine-tuned model based on MobileNet architectures to identify tomato leaf disease for mobile applications. Based on the results tested by K-fold cross-validation, the best accuracy achieved by the proposed model is 97.1%. Additionally, the best average precision, recall and F1 Score are 99.8%, 99.8%, and 99.5%, respectively. The model with the best results is also implemented into Android-based mobile applications.

Penerapan Algoritma Dijkstra dalam Pemetaan UMKM Berbasis Android

This study uses the Java programming language and the Android platform to map Micro, Small, and Medium-Sized Enterprises (MSMEs) in the Deli Serdang area using the Dijkstra algorithm. The purpose of this MSME mapping is to give consumers utilizing a mobile-based Geographic Information System (GIS) information about the closest location of MSMEs. A software development methodology combining quantitative and qualitative methodologies is used in this study. Data about the location of MSME's was gathered via surveys and conversations with company owners. Using SketchUp software, this data was then processed and examined in order to create a visual representation of the locations of MSMEs in the Deli Serdang region. Additionally, Java was used in the development of Android-based mobile applications to provide an interactive and user-friendly display. The location of MSMEs is listed on this application, along with suggestions for the quickest path from the user's current location to the MSMEs they wish to visit. According to the study findings, the Dijkstra algorithm has been successful in recommending the shortest route and fastest travel time to MSMEs, enabling users of this application to locate MSME sites with accuracy and speed. Additionally, users may view comprehensive details about each MSME, including a description of the company, its hours of operation, and contact information. It is anticipated that this application will improve the area of Deli Serdang's information accessibility for tourists and prospective MSME customers. Aside from that, it is envisaged that it will boost MSMEs' competitiveness and promote them while supporting regional economic expansion.

Dijkstra's Algorithm in Mapping UMKM Deli Serdang Based on Android

This study aims to implement Dijkstra's algorithm in mapping Micro, Small and Medium Enterprises (MSMEs) in the Deli Serdang area using the Android platform with Java language. This MSME mapping aims to provide information on the nearest MSME location to users by using a mobile-based Geographic Information System (GIS). This study uses a software development approach with quantitative and qualitative methods. MSME location data was collected through surveys and interviews with business owners. This data is then processed and analyzed using the SketchUp software to build a visual model of MSME locations in the Deli Serdang area. In addition, an Android-based mobile application was developed using the Java programming language to provide an interactive and easy-to-use interface. This application provides information on the location of UMKM as well as recommendations for the closest route from the user's location to the UMKM you want to visit. The results of the study show that Dijkstra's algorithm has succeeded in producing recommendations for the closest route and travel time to MSMEs, so this application can assist users in finding MSME locations quickly and accurately. Users can also view detailed information about each MSME, such as business descriptions, hours of operation, and contacts to contact. This application is expected to increase the accessibility of information for visitors and potential MSME consumers in the Deli Serdang area. In addition, it is hoped that it can help increase the competitiveness and promotion of MSMEs and provide support for local economic growth.

Android-based Mobile Application with Rapid Application Development model for Village Administration Services

Village administration services are essential in a village's progress and villagers' satisfaction with village officials. There are many villages in Indonesia where services still need to be more optimal because they have limitations in disseminating information, unclear procedures, and the status of service applications that cannot be monitored. Mobile-based applications can optimize village administration services, which can bridge between villagers and village officials. From the results of several previous studies, the Rapid Application Development (RAD) model is relevant to be applied in designing Android-based village service applications with the Flutter framework. The SHA-512 algorithm is implemented to increase security by hashing passwords to strengthen database security in village service applications. The application produced in this research has been tested using the User Acceptance Test (UAT) method, and it was concluded that this system is suitable for use by villagers and improves Cihuni village services.

The NeoRoo mobile app: Initial design and prototyping of an Android-based digital health tool to support Kangaroo Mother Care in low/middle-income countries (LMICs).

Premature birth and neonatal mortality are significant global health challenges, with 15 million premature births annually and an estimated 2.5 million neonatal deaths. Approximately 90% of preterm births occur in low/middle income countries, particularly within the global regions of sub-Saharan Africa and South Asia. Neonatal hypothermia is a common and significant cause of morbidity and mortality among premature and low birth weight infants, particularly in low/middle-income countries where rates of premature delivery are high, and access to health workers, medical commodities, and other resources is limited. Kangaroo Mother Care/Skin-to-Skin care has been shown to significantly reduce the incidence of neonatal hypothermia and improve survival rates among premature infants, but there are significant barriers to its implementation, especially in low/middle-income countries (LMICs). The paper proposes the use of a multidisciplinary approach to develop an integrated mHealth solution to overcome the barriers and challenges to the implementation of Kangaroo Mother Care/Skin-to-skin care (KMC/STS) in LMICs. The innovation is an integrated mHealth platform that features a wearable biomedical device (NeoWarm) and an Android-based mobile application (NeoRoo) with customized user interfaces that are targeted specifically to parents/family stakeholders and healthcare providers, respectively. This publication describes the iterative, human-centered design and participatory development of a high-fidelity prototype of the NeoRoo mobile application. The aim of this study was to design and develop an initial ("A") version of the Android-based NeoRoo mobile app specifically to support the use case of KMC/STS in health facilities in Kenya. Key functions and features are highlighted. The proposed solution leverages the promise of digital health to overcome identified barriers and challenges to the implementation of KMC/STS in LMICs and aims to equip parents and healthcare providers of prematurely born infants with the tools and resources needed to improve the care provided to premature and low birthweight babies. It is hoped that, when implemented and scaled as part of a thoughtful, strategic, cross-disciplinary approach to reduction of global rates of neonatal mortality, NeoRoo will prove to be a useful tool within the toolkit of parents, health workers, and program implementors.