Android Version Research Articles

Runtime Permission Issues in Android Apps: Taxonomy, Practices, and Ways Forward

Android introduces a new permission model that allows apps to request permissions at runtime rather than at the installation time since 6.0 (Marshmallow, API level 23). While this runtime permission model provides users with greater flexibility in controlling an app's access to sensitive data and system features, it brings new challenges to app development. First, as users may grant or revoke permissions at any time while they are using an app, developers need to ensure that the app properly checks and requests required permissions before invoking any permission-protected APIs. Second, Android's permission mechanism keeps evolving and getting customized by device manufacturers. Developers are expected to comprehensively test their apps on different Android versions and device models to make sure permissions are properly requested in all situations. Unfortunately, these requirements are often impractical for developers. In practice, many Android apps suffer from various runtime permission issues (ARP issues). While existing studies have explored ARP issues, the understanding of such issues is still preliminary. To better characterize ARP issues, we performed an empirical study using 135 Stack Overflow posts that discuss ARP issues and 199 real ARP issues archived in popular open-source Android projects on GitHub. Via analyzing the data, we observed 11 types of ARP issues that commonly occur in Android apps. For each type of issues, we systematically studied: (1) how they can be manifested, (2) how pervasive and serious they are in real-world apps, and (3) how they can be fixed. We also analyzed the evolution trend of different types of issues from 2015 to 2020 to understand their impact on the Android ecosystem. Furthermore, we conducted a field survey and in-depth interviews among the practitioners from open-source community and industry, to gain insights from practitioners’ practices and learn their requirements of tools that can help combat ARP issues. Finally, to understand the strengths and weaknesses of the existing tools that can detect ARP issues, we built <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ARPBench</small> , an open benchmark consisting of 94 real ARP issues, and evaluated the performance of three available tools. The experimental results indicate that the existing tools have very limited supports for detecting our observed issue types and report a large number of false alarms. We further analyzed the tools’ limitations and summarized the challenges of designing an effective ARP issue detection technique. We hope that our findings can shed light on future research and provide useful guidance to practitioners.

Development of an eHealth Tool for Capturing and Analyzing the Immune-related Adverse Events (irAEs) in Cancer Treatment.

Immunotherapy has revolutionized the treatment of many different types of cancer, but it is associated with a myriad of immune-related adverse events (irAEs). Patient-reported outcome (PRO) measures have been identified as valuable tools for continuously collecting patient-centered data and are frequently used in oncology trials. However, few studies still research an ePRO follow-up approach on patients treated with Immunotherapy, potentially reflecting a lack of support services for this population. The team co-developed a digital platform (V-Care) using ePROs to create a new follow-up pathway for cancer patients receiving immunotherapy. To operationalize the first 3 phases of the CeHRes roadmap, we employed multiple methods that were integrated throughout the development process, rather than being performed in a linear fashion. The teams employed an agile approach in a dynamic and iterative manner, engaging key stakeholders throughout the process. The development of the application was categorized into 2 phases: "user interface" (UI) and "user experience" (UX) designs. In the first phase, the pages of the application were segmented into general categories, and feedback from all stakeholders was received and used to modify the application. In phase 2, mock-up pages were developed and sent to the Figma website. Moreover, the Android Package Kit (APK) of the application was installed and tested multiple times on a mobile phone to proactively detect and fix any errors. After resolving some technical issues and adjusting errors on the Android version to improve the user experience, the iOS version of the application was developed. By incorporating the latest technological developments, V-Care has enabled cancer patients to have access to more comprehensive and personalized care, allowing them to better manage their condition and be better informed about their health decisions. These advances have also enabled healthcare professionals to be better equipped with the knowledge and tools to provide more effective and efficient care. In addition, the advances in V-Care technology have allowed patients to connect with their healthcare providers more easily, providing a platform to facilitate communication and collaboration. Although usability testing is necessary to evaluate the efficacy and user experience of the app, it can be a significant investment of time and resources. The V-Care platform can be used to investigate the reported symptoms experienced by cancer patients receiving Immune checkpoint inhibitors (ICIs) and to compare them with the results from clinical trials. Furthermore, the project will utilize ePRO tools to collect symptoms from patients and provide insight into whether the reported symptoms are linked to the treatment. V-Care provides a secure, easy-to-use interface for patient-clinician communication and data exchange. Its clinical system stores and manages patient data in a secure environment, while its clinical decision support system helps clinicians make decisions that are more informed, efficient, and cost-effective. This system has the potential to improve patient safety and quality of care, while also helping to reduce healthcare costs.

Development of an IOS-Based Baby Meal Planner Application

The Baby Meal Planner (BMP) application has been developed by the authors since 2020, and in 2022 BMP version 2.0 has been redeveloped. The BMP Version 2.0 application has been equipped with a cut-off point for the baby’s nutritional status with the latest references, calculation of energy and nutrient needs for babies up to 24 months of age, calculation of food needs for MPASI up to 24 months of age, and is equipped with MP-ASI recipes for up to 24 months of age. 24 months. Currently, the Android version of the BMP application has been used by more than 5,000 people, received a rating of 4.9, has 3 copyright certificates, has been published in SINTA-indexed journals, has been processed in international journal reviews, and has been reached to the public in community service activities. Along with the increase in smartphone users with the iPhone Operating System (IOS) operating system, the purpose of this research is to develop an IOSbased Baby Meal Planner Application. The research will be carried out for 8 months from April to December 2023, in collaboration with the Kebon Kalapa Village, Central Bogor District, Bogor City through the PKK and Posyandu as partners in the research. Research activities consist of a preparatory process in the form of discussion activities with partners, licensing, and preparation of proposals. Application development activities include developing application features, processing complementary food menus, and outreach to the community. The method used in application development is the Forward Chaining Method. The output of this study is the IOS-based Baby Meal Planner application, which can be downloaded from the App Store, with a level of technology readiness at level 7 (TKT 7).

Execution Recording and Reconstruction for Detecting Information Flows in Android Apps

Security researchers utilize taint analyses to uncover suspicious behaviors in Android apps. Current static taint analyzers cannot handle ICC, reflection, and lifecycles dependably, increasing the result verification cost. On the other hand, current dynamic taint trackers accurately detect execution paths. However, they depend on specific Android versions and modified devices, reducing their usability and applicability. In addition, they require app exercise every time running the taint analysis. This paper presents a new dynamic taint tracker called T-Recs, tracking information flows by recording and reconstructing the app execution. First, before the taint analysis, the app’s runtime data are obtained by instrumenting logging code into the app’s bytecode and running the app to be independent of specific Android versions and devices. Then, T-Recs performs the taint analysis accurately with the logged data and separately from the app exercise. This paper is an extended version of our work published. Previously, T-Recs’ accuracy was mainly evaluated in privacy leak detection. The results show that T-Recs outperforms compared analyzers, which are FlowDroid (w/ and w/o IC3), Amandroid, DroidSafe, and TaintDroid (w/ and w/o IntelliDroid). This paper also involves DroidRA and IccTA. This paper shows that T-Recs detects ICC- and reflection-related leaks missed by FlowDroid in popular Google Play apps. The other static analyzers fail to analyze most of the apps. These experiments also indicate an advantage of T-Recs: its users can re-execute T-Recs’ taint analysis without re-exercising the app. T-Recs’ app-runtime overhead and parallel execution performance were also evaluated, and the results are acceptable.

Development of Augmented Reality-Based Learning Media on Mechanical Wave Material

Augmented reality is one of the most potential technologies for education. Especially in learning Physics for material that is not real. Wave material is one of the appropriate topics if we study it using augmented reality media. The purpose of this research is to develop, validate, and check the reliability of augmented reality-based learning media on mechanical wave material. This research is an R&amp;D research using the ADDIE-type instructional design model. This augmented reality-based media was designed using the Blender, Vuforia, and Unity applications. The Blender application is used to create 3D wave models, Vuforia to create markers, and Unity to create the final application that is displayed on students' androids. This research has produced a 46-page wave material physics module that is integrated with an augmented reality application consisting of 17 markers about waves. The size of the application is 222 Mb with the Apk format on Android version 4.1 Jelly Bean and a 13 MP camera. After testing the validity with 3 experts (experts), namely media experts, material experts, and pedagogic experts as well as 3 expert users (expert users), the average value of an expert and user experts is 4.5 and 4.8 with a maximum score of 5. Media This was also assessed as good by 20 student responses. So that this learning media can be said to be valid according to experts, expert users, and users.

Teknologi React Native Pada Aplikasi Mobile Pemilihan Anggota Terbaik dan Pencatatan Point Bank Sampah

The increase in people's consumption patterns in the Kalirejo area, Central Lampung has an impact on increasing the volume of waste. The Sidodadi Trash Bank is an alternative in the context of waste management at the community level. Sidodadi Trash Bank in its management requires recording activities and rankings for all its members which are calculated every year with the aim of providing rewards for the best members. Recording and ranking activities are still done manually, therefore a Decision Support System (SPK)-based application is presented to facilitate the activities of the Sidodadi Trash Bank. This application can be used for administrators and also all members of the Sidodadi Trash Bank. This application was created using visual studio software and Simple Additive Weighting (SAW) method. The results of the calculation of the SAW method on the data of five members manually proved to be the same as the results of the system calculations, namely 0,99, which was won by Novita Sari. Testing Device was carried out on Android versions 7.1.1 Nougat, 7.1.2 Nougat, 8.0.0 Oreo, 8.1 Oreo, and 9.0.0 Pie and all worked. From the test results, it is found that the application runs well at least on the Android 5.0 Lollipop version.

APP constraint analysis approach to select mobile devices for compatibility crowdtesting

AbstractThe compatibility issues caused by Android fragmentation have become a vital task in the development of Android applications. To locate those issues, thousand of crowd testers run apps on different devices with different configurations to achieve the largest coverage, which might be costly and time‐consuming. Since existing approaches to selecting optimal devices are device‐side analysis without the information of the internal structures of apps, app‐side analysis that flags the essential devices for testers has remained elusive. To mitigate this gap of compatibility crowdtesting, this paper proposes an app constraint analysis approach named CompatDroid to generate the optimal device set to guide crowd testers. By evaluating 46 benchmark apps on 14 SDK versions, the optimal device sets are successfully generated, and CompatDroid only needs no more than 7 Android versions to achieve almost the same code coverage (i.e., 33.13%) testing on all 14 android versions (i.e., 34.65%) in 36 of 46 apps, which indicates that it can drastically reduce the consumption of test resources while losing little test coverage. On a larger dataset, CompatDroid successfully analyzes 98.3% of 645 apps, in which the median number of the optimal SDK versions set is 2.5 versions, and 68.92% of those apps contain the constraints of SDK version (i.e., SDK version) while 84.86% of them do not have the constraints of hardware information (i.e., model name and manufacture name).

User Behavior of a Publicly Available, Free-to-Use, Self-guided mHealth App for Depression: Observational Study in a Global Sample.

Reducing the burden of depression is a global health concern. Self-guided mobile health (mHealth) apps are one approach to address this problem. However, there is little research on self-guided mHealth apps in a global sample or on how they are used in the real world. These gaps in our knowledge must be addressed to bring the promise of mHealth apps for reducing the global burden of depression closer to reality. The purpose of this study is to examine the naturalistic user behavior of MoodTools, a publicly available, free-to-use, self-guided mHealth app designed to improve symptoms of depression, in a global community sample. Mobile analytics data were collected from all unique downloads of the Android version of MoodTools between March 1, 2016, and February 28, 2018. Due to the deidentification and data aggregation process, no demographic or personal identifying information was tied to individual user data. All information was stored in aggregated, anonymized data files on Google Analytics' storage database. Google's software development kit was used to securely capture data about the number of downloads, location of downloads, number of app sessions, frequency and duration of app sessions, time between app sessions, and user retention, allowing for examination of which app's tools were viewed and for how long, including Information (psychoeducation), Test (self-monitoring using the Patient Health Questionnaire [PHQ-9]), Thought Diary (targeting negative cognitions), Activities (behavioral activation), Videos (curated from YouTube), and Safety Plan (safety plan development and links to quickly access crisis management resources). MoodTools was used by 158,930 people from 198 countries, including countries where English was not the primary language and in low- and middle-income countries. After the initial download, 51.14% (n=81,277) of users returned to the app after the initial download, and retention rates decreased with each subsequent app session. The typical person used the app for 3 sessions for a total of 12 minutes over 90 days. The most frequently visited tools were Test and Thought Diary (n=393,549, 24.32%). On average, users completed and reviewed the results of the PHQ-9 for 49 seconds and 53 seconds, respectively, and spent 3 minutes and 5 seconds on Thought Diary. Self-guided mHealth apps could be one approach (among the many needed) to reduce the burden of depression. Observational data collected in this study show a global interest in MoodTools, including in low- and middle-income countries and countries where English is not the primary language. Future research is needed to determine whether people who use self-guided apps experience improvement in depressive symptoms, and if so, what "dosage" provides a meaningful benefit.

Analysis of Digital Data by File Signature Method on Android Version 9

Objective: The use of smartphones has exponentially increased over the past decade. Nowadays the use of a cellphone has not just been restricted to make calls, but it's also actively used to connect people throughout the globe through social media and sharing multimedia files over the internet. Smartphones have made these things possible and easily available with just a single touch. But along with this development and digitalization, an increase in the rate of cybercrime has also surfaced, which includes crime like illicit possession, distribution, and modification of multimedia files. Hence, smartphones are seen as a rich source of evidence-based on the crimes discussed. This process is carried out to analyze smartphone‟s multimedia files to determine their origin and to verify if the multimedia files originated from the same device or transferred through any process. Methods: An examiner must analyze, recover, and authenticate the files stored in a smartphone device. Android version 9 was used for analysis since it is the most common and abundant platform generally found in most people‟s phones. Examination of computer file is achieved by analyzing the file in hexadecimal editor software, the software used in this analysis is HxD. Results: File signature and metadata analysis of smartphones‟ multimedia files was performed to render the source of the files. Conclusion: The conducted file signature and metadata analysis clearly stated that by using hexadecimal editor softwareHxD origin and source of smartphones‟ multimedia file can be rendered.

User Friendly Android-based Contact Application: Case of Accessible Contact in Educational Organization

Abstract: In a digital era, people prefer to use smart gadgets and it is growing to be instrumental in daily lives. The features of the smartphone are also evolving, leading to effectiveness for end users. With such an aim, an android-based contact application was developed that would benefit an organization. As an interim measure, this application is based on Jigme Namgyel Engineering College under the Royal University of Bhutan. Currently, this organization do not have a 'contact application' that can be used as a digital phonebook. Therefore, the entire faculty, staff, and students have to search for contact details through person-to-person communication leading to several inconveniences. This android base application called JNEC Contact made contact detail of the college’s staff available and accessible to staff and students without an internet connection. This application is implemented specifically for JNEC to ease the difficulties of acquiring contact information of faculty and staff. The application titled JNEC Contact has other features such as text messages and mail-to-direct correspondence. It is known to be more comfortable, efficient, and user-friendly to find a contact, unlike the phonebook. The current version of the application has limited compatibility with the android version only, but it can be developed for IOS phones in the future.

The Design and Implementation of a Libyan Salary Mobile Application using Flutter

Mobile applications have become widespread in many aspects of our daily lives. Many people do most of their work via their phones, such as online banking, shopping, etc. Due to many individuals being unaware of their salary details, this paper presents a design and implementation of a Libyan salary application” الراتب” using Flutter (cross-platform). The application allows users to know details of their salaries, including bonuses and deductions according to the salary schedule of each ministry or sector. The application currently contains salary schedules for ten ministries. The implementation consists of the following four steps: data collection of laws and payroll tables for each ministry to use as a local database for the salary application, design of friendly-use application screens using Flutter, integration of the mobile application with Firebase) backend platform by Google), and finally, preparing and deploying an Android and web version of the salary application. The results that were obtained from reviewers in the Google Play Store were satisfactory. There is an increasing local demand to add other ministries to the application. The citizens of the local community encourage providing such a service, which is considered the first of its kind. The application reached more than 100k downloads in less than a year, and the average rating is 4.5 out of 5 in the Google Play Store at the time of writing this paper.

Evaluation of chatbot-delivered interventions for self-management of depression: Content analysis

BackgroundConversational agents (CAs) or chatbots are increasingly used for depression, anxiety, and wellbeing management. CAs are considered acceptable and helpful. However, little is known about the adequacy of CA responses. This study assessed the structure, content, and user-customization of mental health CA dialogues with users with depression or at risk of suicide. MethodsWe used content analysis to examine the dialogues of CAs previously included in three assessments of mental health apps (depression education, self-guided cognitive behavioural therapy, and suicide prevention) performed between 2019 and 2020. Two standardized user personas with depression were developed to interact with the CA. All conversations were saved as screenshots, transcribed verbatim, and coded inductively. ResultsNine CAs were included. Seven CAs (78%) had Android and iOS versions; five CAs (56%) had at least 500,000 downloads. The analysis generated eight categories: self-introduction, personalization, appropriateness of CA responses, conveying empathy, guiding users through mood-boosting activities, mood monitoring, suicide risk management, and others. CAs could engage in empathic, non-judgemental conversations with users, offer support, and guide psychotherapeutic exercises. LimitationsCA evaluations were performed using standardized personas, not real-world users. CAs were included for evaluation only if retrieved in the search strategies associated with the previous assessment studies. ConclusionAssessed CAs offered anonymous, empathic, non-judgemental interactions that align with evidence for face-to-face psychotherapy. CAs from app stores are not suited to provide comprehensive suicide risk management. Further research should evaluate the effectiveness of CA-led interventions in mental health care and in enhancing suicide risk management strategies.

Mobile Device Security Evaluation using Reverse TCP Method

Security evaluation on Android devices is critical so that users of the operating system are protected from malware attacks such as remote access trojans that can steal users' credential data. Remote access trojan (RAT) attacks can be anticipated by detecting vulnerabilities in applications and systems. This study simulates a remote access trojan attack by exploiting it until the Attacker gains full access to the victim's device. The episode is carried out with several steps: creating a payload, installing applications to the victim's device, connecting listeners, and performing exploits to retrieve important information on the victim's device. Test material using Android 12, problems occurred when trying to install the application because a harmful warning will appear from Play Protect due to not using the latest version of privacy protection which causes the application to be indicated as malware and the like. On Android 11, the application injected with the backdoor was successfully installed on the device and successfully accessed by the attacker. Attackers also get vital information, including system information, contacts, call logs, messages, and full access to the victim's device system directory. Based on this research, it is expected that Android device users constantly update the Android version on the device they are using.

Forensic Analysis of TikTok Alternatives on Android and iOS Devices: Byte, Dubsmash, and Triller

TikTok has consistently been one of the most used mobile apps worldwide on any mobile operating system. However, despite people’s enjoyment of using the application, there have been growing concerns about the application’s origins and alleged privacy violations. These allegations have become such a big problem that the former President of the United States, Donald Trump, expressed a desire to ban the TikTok application from being offered on US application stores like Google’s Play Store and Apple’s App Store. This remark sent TikTok users into a frenzy to find alternatives before the ban took effect. To this end, several alternative applications for TikTok have surfaced and are already garnering millions of users. In this paper, we identified three popular alternatives to the TikTok application (Byte, Dubmash, and Triller) and forensically analyzed each on smartphones of Android version 8 and iOS version 13. We focused on identifying forensically relevant artifacts that may be helpful to investigators in the event of a criminal investigation, should these or similar apps fall under scrutiny. We used Magnet AXIOM Process and Cellebrite UFED 4PC for acquisition, and Magnet AXIOM Examine and DB Browser for SQLite for analysis and reading. The investigation resulted in successful extraction of expected yet unique data points, plain text sensitive data, directories and format. These results lead to a discussion about identifying and comparing these app’s privacy concerns to that of TikTok, as formulated from the literature.

Design of the Student Attendance Management System Based on the Internet of Things Technology

The IoT refers to the linking of items to a network through message-generating devices; in the connection process, communication and information circulation are carried out through the information dissemination medium to realize intelligent identification, tracking, supervision, and other functions. Attendance management is a system for assessing employee attendance, including being late, leaving early, and asking for leave. Student attendance refers to the attendance rate of students in class. This article aimed to study the design and research of the student attendance management system based on the Internet of things technology, and use this system to accurately record students’ attendance and develop good habits for students. An effective attendance management company has been developed to enhance the collection of information for student management in universities, to keep track of teachers’ and students’ teaching attendance in real time, and to connect teachers and students in real time using computer technology. Access to the Android version of the software speeds up the collection and processing of information and can play an important role in improving the efficiency of personnel management. On the basis of analysing the operation logic of the attendance system, matching programs and the attendance system software are designed. The experimental results of this article show that the attendance rate of students with utilitarian personality is the highest, as high as 70%; the attendance rate of students with helpless personality is 13%; the attendance rate of students who follow the current personality accounted for 10%; and the attendance rate of nonmotivated students accounted for 7%. It can be seen from this that personality is an important factor affecting students’ attendance rate. The attendance rate of positive psychology with goals is the highest, and the attendance rate of students without clear goals is the lowest. The student attendance management system of the Internet of things technology has been applied in practical work, but with the continuous construction and development of the school, the continuous improvement of new software and hardware, and the emergence of new needs in practical work, the student attendance management system is easy to crash when processing a large amount of data at the same time.

Validation of the Mobile App Version of the EQ-5D-5L Quality of Life Questionnaire Against the Gold Standard Paper-Based Version: Randomized Crossover Study.

BackgroundStudy participants and patients often perceive (long) questionnaires as burdensome. In addition, paper-based questionnaires are prone to errors such as (unintentionally) skipping questions or filling in a wrong type of answer. Such errors can be prevented with the emergence of mobile questionnaire apps.ObjectiveThis study aimed to validate an innovative way to measure the quality of life using a mobile app based on the EQ-5D-5L questionnaire. This validation study compared the EQ-5D-5L questionnaire requested by a mobile app with the gold standard paper-based version of the EQ-5D-5L.MethodsThis was a randomized, crossover, and open study. The main criteria for participation were participants should be aged ≥18 years, healthy at their own discretion, in possession of a smartphone with at least Android version 4.1 or higher or iOS version 9 or higher, digitally skilled in downloading the mobile app, and able to read and answer questionnaires in Dutch. Participants were recruited by a market research company that divided them into 2 groups balanced for age, gender, and education. Each participant received a digital version of the EQ-5D-5L questionnaire via a mobile app and the EQ-5D-5L paper-based questionnaire by postal mail. In the mobile app, participants received, for 5 consecutive days, 1 question in the morning and 1 question in the afternoon; as such, all questions were asked twice (at time point 1 [App T1] and time point 2 [App T2]). The primary outcomes were the correlations between the answers (scores) of each EQ-5D-5L question answered via the mobile app compared with the paper-based questionnaire to assess convergent validity.ResultsA total of 255 participants (healthy at their own discretion), 117 (45.9%) men and 138 (54.1%) women in the age range of 18 to 64 years, completed the study. To ensure randomization, the measured demographics were checked and compared between groups. To compare the results of the electronic and paper-based questionnaires, polychoric correlation analysis was performed. All questions showed a high correlation (0.64-0.92; P<.001) between the paper-based and the mobile app–based questions at App T1 and App T2. The scores and their variance remained similar over the questionnaires, indicating no clear difference in the answer tendency. In addition, the correlation between the 2 app-based questionnaires was high (>0.73; P<.001), illustrating a high test-retest reliability, indicating it to be a reliable replacement for the paper-based questionnaire.ConclusionsThis study indicates that the mobile app is a valid tool for measuring the quality of life and is as reliable as the paper-based version of the EQ-5D-5L, while reducing the response burden.

ANALISA KEGUNAAN DAN KEMUDAHAN LAYANAN MOBILE JKN PADA UPTD PUSKESMAS DEPOK DENGAN USE QUESTIONNAIRE DAN IPA

Android applications are required to have quality and attractive appearance so that the information submitted can be received by users well in addition to attracting visitors to continue to access the android application. The features provided by the Android application must function properly according to its purpose, in addition to the ease and convenience of users in using or running the content in the Android application. All of these are aspects that are necessary in the development of an android application. The JKN Mobile Application is a form of digital transformation of the BPJS Health business model, which was originally in the form of administrative activities carried out at Branch Offices or Health Facilities, transformed into an application that can be used by participants anywhere at any time without time constraints (self service). Currently, there are&gt; 1,000,000 users of the Android version of the JKN Mobile Application and the iOS version of the JKN Mobile Application of&gt; 2,000 users. To find out whether the android application can be said to be of quality, it can be tested on everything in the android application. In testing the quality of the android application, the method used is the Use Questionnaire and Importance Performance Analysis (IPA) by using a questionnaire that is submitted to the specified respondents. Based on the gap analysis, it was found that Mobile JKN users at the UPTD Puskesmas Depok felt that the application still needed to be improved.

Analysing Content Ratings of Google Apps with Ensemble Learning

Google Play was launched under the name of Android Market and made its reputation known all over the world. The mobile application market, which is a package manager developed by Google for Android users, contains applications that appeal to many areas and age ranges. The wide area in which applications spread and the data flow, which has reached the level of being called “big data”, has started to attract the attention of researchers. The excessive increase in the number of applications makes it difficult for parents to follow up on the content. In order to provide content rating of applications on Google Play, it is needed to be classified by machine learning methods. In this study, content rating classification was made by analyzing “Category, Rating, Reviews, Size, Installs, Type, Genres, Last Updated, Current Version, Android Version” features of 10757 applications on Google Play, Ensemble Learning methods (Adaboost, Bagging, Random Forest, Stacking), Logistic Regression, Artificial Neural Network, K-Nearest Neighbors algorithms.

Development of Online Service Booking Mobile Application Using Android Studio

This research is all about an application developed in order to make household services more manageable and easy like never before. We have developed an application for Online Service Booking native android application using android studio new version. This paper will also describe the working principle of this app. Admin panel of the application has been developed in PHP language with the help of Code Igniter framework a perfect tool to develop this kind of application. PHPMYADMIN has been used for the development of the database. Also we have used the hosting facility provided by 000webhost to deploy our code onto the server. Google firebase has been used for connecting our both the application as well as the admin panel all together. This application has many type of services. User can choose services according to their need and convenience. They can also select the date and time and the payment modes as per their preference.

Android-Based Introduction to Agricultural Crops and Pests

The number of farmers in Indonesia continues to increase during the pandemic. However, this increase was not accompanied by good literacy related to plants and pests. The main factor is the increasing amount of information that is not credible. This research was conducted to provide alternative solutions for farmers or the community, especially novice farmers in obtaining plant and pest information through an android application. This application was developed using the Kotlin programming language on Android Studio with the Waterfall Development Method. Based on the results of functional testing, the application can run well and pass all test scenarios using the Black Box method and can run on smartphones with Android 5.0 to 9.0 systems, without closing the possibility of a new Android version.