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                  <text>International Journal of Interactive Mobile Technologies (iJIM)</text>
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                <text>Minhat, Mohammad Hazwan Hakim</text>
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                <text>Leaf identification image is consistently a difficult task when using computer vision. The convolutional component extraction methods on images have their impediment and limitation, such as low accuracy, are not adaptable and less promising when converted to genuine application. The reasons are the lack of dataset needed to build a recognition model. Likewise, using the computer as a tool is bothering as it restricts the task in the research lab only. Convolutional Neural Network (CNN) shows a great solution for the computer version. Subsequently, this project utilizes the CNN’s properties to solve the image classification task, and the CNN model chosen is run in Phyton coding in TensorFlow Lite. It is similar to TensorFlow’s running code, but this project focused on building an Android application. It can perform faster and produce high accuracy results. There are four types of leaves involved in this project: betik, kari, pudina, and cengal. As a result, the model could reach around 99% accuracy with a 0.176 error rate. Ultimately, an Android application called Leaf identification is created. The model is sent and integrated into the apps that work with a concentrated information base to help put away and deal with the pictures. Hence, an Android leaf image identifier using CNN is proposed to solve the stated problem and is believed to contribute to education and research.</text>
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                <text>Copyright (c) 2022 Hazwan Hakim, Sharifa, Dr Kadir , Umi Fadlillah</text>
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                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 16 No. 15 (2022); pp. 62-77</text>
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                <text>Considering that application security is an important aspect, especially nowadays with the increase in technology and the number of fraudsters. It should be noted that determining the security of an application is a difficult task, especially since most fraudsters have become skilled and professional at manipulating people and stealing their sensitive data. Therefore, we pay attention to trying to spot insecurity apps, by analyzing user feedback on the Google Play platform and using sentiment analysis to determine the apps level of security. As it is known, user reviews reflect their experiments and experiences in addition to their feelings and satisfaction with the application or not. But unfortunately, not all of these reviews are real, and as is known, the fake reviews do not reflect the sincerity of feelings, so we have been keen in our work to filter the reviews to be the result is accurate and correct. This study is useful for both users wanting to install android apps and for developers interested in app optimization.</text>
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                <text>Copyright (c) 2021 Abeer Aljumah, Amjad Altuwijri, Thekra Alsuhaibani, Afef Selmi, Nada Alruhaily</text>
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                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 15 No. 24 (2021); pp. 123-133</text>
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                <text>1865-7923</text>
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                <text>Android Apps Security Assessment using Sentiment Analysis Techniques: Comparative Study</text>
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                <text>Lakshmanarao, A.</text>
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                <text>Shashi, M.</text>
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                <text>Android is the most widely used operating system in smartphones. Mobile users can download and access apps easily from the play store. Due to lack of security awareness and risk associated with mobile apps, malware apps would be downloaded by normal users in general. The consequences after installing a malware app are unpredictable. Malware apps can gather user personal data, browsing history, user profiles, user sensitive data like passwords. Hence, android malware detection is essential for providing security to mobile users. Android malware detection using machine learning is done either by extracting static features (opcodes, permissions, intents, system commands) or by extracting dynamic features (log behavior, system calls, dataflow). In this paper, opcode sequences are extracted from malware and benign apps, and Recurrent Neural Networks are proposed on extracted sequences. Benign apps are collected from the play store, apkpure.com and malware apps are collected from the virus share website. The proposed Recurrent Neural Network model could achieve 96% accuracy for android malware detection.</text>
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                <text>Copyright (c) 2021 A Lakshmanarao, M Shashi</text>
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                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 16 No. 01 (2022); pp. 145-157</text>
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                <text>1865-7923</text>
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                <text>Android Malware Detection with Deep Learning using RNN from Opcode Sequences</text>
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                <text>Alani, Mohammed M.</text>
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                <text>Having a share of over 80% of the smartphone market, Android has become an important mobile operating system that is used by billions of users on daily basis. With the widespread use of smartphones in general, and Android in specific, privacy concerns grow with that expansion in the user base. With the millions of applications being downloaded by users daily, it is becoming increasingly difficult to differentiate between the good and the bad in terms of security and privacy. In this paper, we present the results of a survey conducted among 4027 Android users worldwide. This survey was conducted to measure the awareness of Android users regarding their privacy. The study measures the users' interaction with the permissions required by different applications they install. The results of the survey show apparent weakness in the awareness of Android users regarding the privacy of their data.</text>
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                <text>Nunuk Hariyati</text>
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                <text>Digital technology has enabled the dissemination of all types of information, replacing traditional formats with automated systems. As a result of the development of digital technology, the library has also entered a new era, which is then called the digital library era. Digital library is considered as one form of modern library where the dependence will be on modern technology in the conversion of information and data to digital formats to achieve greater effectiveness and efficiency in storing and processing information and then transmitting it. Therefore, the purpose of this study is to develop an Android-Based Digital Library Application at the Department of Education Management, State University of Surabaya. This study uses the research and development method proposed by Borg and Gall by applying the nine stages. The results of this study indicate that the development of an Android-Based Digital Library Application at the Education Management Department, State University of Surabaya has been successfully implemented with the results of the trial getting an average percentage above 80% which is included in the very feasible category to be implemented. Even so, evaluation and monitoring must continue to be carried out to prevent errors or problems that may occur, as well as material to continue developing this Android-Based Digital Library Application.</text>
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                <text>Copyright (c) 2022 mohammad syahidul haq, Muchlas Samani, Karwanto, Nunuk Hariyati</text>
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                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 16 No. 11 (2022); pp. 224-237</text>
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                <text>1865-7923</text>
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                <text>Herawati, Septy Nur</text>
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                <text>Learning media is one of the important components in the process of implementing learning, especially during the current pandemic. But in reality there are still few teachers who use media in the learning process, causing student learning outcomes to decline. Interactive media which is one of the media that can be used to attract students' attention by combining systems ranging from text, images, videos, and audio/sound can provide new experiences for students in learning. This study aims to determine student learning outcomes after using android-based interactive learning media in social science subjects. The population group consisted of 70 students from several schools in Cluster 2, Cipinang Muara Village. Then samples were taken using the Slovin formula to get 60 samples of fourth grade students. This study uses experimental research methods and uses a single group pre test - post test. The collected data were analyzed through t test. The results showed that android-based interactive media had a positive effect on student learning outcomes. Students experienced a significant increase in learning outcomes by using this media. In addition, students feel more interested and easier to understand the material by using this application. The results showed that android-based interactive media had a positive effect on student learning outcomes. Students experienced a significant increase in learning outcomes by using this media. In addition, students feel more interested and easier to understand the material by using this application. The results showed that android-based interactive media had a positive effect on student learning outcomes. Students experienced a significant increase in learning outcomes by using this media. In addition, students feel more interested and easier to understand the material by using this application.</text>
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                <text>https://online-journals.org/index.php/i-jim/article/view/25739</text>
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                <text>Copyright (c) 2022 Sujarwo Sujarwo, Septy Nur Herawati, Tunjungsari Sekaringtyas, Desy Safitri, Arita Marini, Sri Nuraini, Taufik Rihatno</text>
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                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 16 No. 07 (2022); pp. 4-21</text>
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                <text>1865-7923</text>
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                <text>Android-Based Interactive Media to Raise Student Learning Outcomes in Social Science</text>
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                <text>Ben Rshed, Mohammed</text>
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                <text>Many companies, such as Aramex, FedEx, and SMSA, offer product delivery services. However, the delivery process through these companies is costly and/or requires the customer’s physical attendance at the company to get the sent shipments. There is a persistent need to improve the delivery process in Saudi Arabia to reduce the effort, cost, and time that the customer spends to get the shipped products. This paper presents a new delivery approach in Saudi Arabia by developing an Android-based MobApp that allows the customers to use their mobile devices to send and receive shipped products at their doorstep by submitting online requests through the developed MobApp. The proposed MobApp, named as Door-to-Door (D2D) product delivery MobApp, guarantees fast and costless service among its competitors. The MobApp will provide its customers a reliable delivery process. It aims to provide a domestic delivery chain with whomever to wherever within Saudi Arabia. In addition, the proposed delivery MobApp allows the customers to create, update and track the delivery orders. Moreover, the proposed D2D delivery MobApp is easy to install and use, it provides a friendly GUI and has a powerful steady performance.</text>
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                <text>International Association of Online Engineering (IAOE), Vienna, Austria</text>
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            <elementTextContainer>
              <elementText elementTextId="28175">
                <text>Copyright (c) 2018 Samer Atawneh, Mohammed Ben Rshed, Mohammed Ben Rshed, Khalid Aldossari, Khalid Aldossari, Abdulrhman Basuliman, Abdulrhman Basuliman, Mohammed Alamri, Mohammed Alamri</text>
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                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 13 No. 03 (2019); pp. 125-142</text>
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                <text>1865-7923</text>
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                <text>MobApp</text>
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                <text>delivery process</text>
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                <text>This study aimed to develop an Android learning media on the concept of redox as an effective, efficient, practical, real-time learning media and in accordance with the facilities owned by students and evaluate the quality and usability of the app. The approach used in this research was a quantitative approach in the form of development research, while the model used was the Hannafin and Peck (1988) model. The data of this study were collected from the process of development, expert evaluations (expert reviews), and small group evaluation. 20 students of the chemistry education study program at a university in Indonesia volunteered to use and evaluate the app, Data was collected by using questionnaires. The results indicated that the quality of the application obtained from expert review was 94.7%. Furthermore, the small group evaluation shows that the usability of RedoksPro version 1.1 scored 86.7. The Android-based learning media of redox concept (RedoksPro application version 1.1) could be utilized as a mobile learning resource in learning the specific concept of reduction and oxydation reactions.</text>
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                <text>Copyright (c) 2022 Muhammad Nazar, Rusman Rusman, Kana Puspita, Husnul Yaqin</text>
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                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 16 No. 03 (2022); pp. 123-135</text>
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                <text>1865-7923</text>
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                <text>Android-Based Mobile Learning Resource for Chemistry Students in Comprehending the Concept of Redox Reactions</text>
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                <text>Novaliendry, Dony</text>
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                <text>Sanita, Debi</text>
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                <text>Putra, Dino Adi</text>
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                <text>Feiyska Nasution, Marsinah Dewi</text>
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                <text>Digital and communication technology has developed in combination with globalization to ensure quick connectivity and distribution of information. In particular, the quality of education is one of the education challenges that have become a target for urgent solutions.  From the various conditions and potentials that exist, efforts that can be made concerning quality improvement in schools are to develop a student-oriented learning system (children center) and facilitate student’s needs for learning needs that are challenging, active, creative, innovative, practical, and fun by developing and apply learning based on Information and Communication Technology. This research was generated using the media development method, which refers to Four-D development, which consists of four stages: Define, Design, Develop, and Disseminate, carried out in high school. Vocational class XI Computer and Network Engineering. In this study, the test subjects were students of class XI Computer and Network Engineering at SMK Negeri 8 Padang. The three validator’s assessment as a whole, the validator test assessment of Android-Based Learning Media is 94.28%. The validity level can be interpreted as being Very Valid to use. Overall, the practicality assessment of Android-Based Learning Media as a learning resource is 88.46%, so that the level of practicality can be interpreted as Very Practical to use. The evaluation of Android-Based Learning Media's effectiveness of 90.86%, so that the level of significance can be interpreted as Very Good for use.</text>
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                <text>Copyright (c) 2021 Debi Sanita, Dony Novaliendry, Asrul Huda, Dino Adi Putra, Marsinah Dewi Feiyska Nasution, Rezi Septiardi Putra, Rizka Novri Hidayati</text>
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                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 15 No. 20 (2021); pp. 83-100</text>
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                <text>1865-7923</text>
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                <text>Methods</text>
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                <text>Android-Based Network Services Application Learning Media for Vocational High Schools</text>
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                  <text>International Journal of Interactive Mobile Technologies (iJIM)</text>
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                <text>Mohamed Hadi Habaebi</text>
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                <text>Ahmad Shahmi Mod Rofi</text>
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                <text>Md Rafiqul Islam</text>
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                <text>Ahmed Basahel</text>
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                <text>LoRaWAN wireless communication channels are often impacted by noise and interference over long-range causing loss of a received signal. One of the main drawbacks of using existing propagation models is less accurate as these models in designing the communication link are tailored to simplify the estimation. In this paper, an artificial intelligent real time path loss model is proposed. It is capable of processing complex variables over a short period of time. Providing it with enough data, the model is able to learn channel behavior and predict the path loss accurately. Results of the model are benchmarked against classical statistical curve fitting models where RMSE values are also compared and indicating that the artificial intelligent model has better accurate prediction.</text>
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                <text>https://online-journals.org/index.php/i-jim/article/view/30095</text>
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                <text>10.3991/ijim.v16i11.30095</text>
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                <text>International Association of Online Engineering (IAOE), Vienna, Austria</text>
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                <text>https://online-journals.org/index.php/i-jim/article/view/30095/11403</text>
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                <text>Copyright (c) 2022 Mohamed Hadi Habaebi, Ahmad Shahmi Mod Rofi, Md Rafiqul Islam, Ahmed Basahel</text>
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                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 16 No. 11 (2022); pp. 91-106</text>
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                <text>1865-7923</text>
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                <text>Artificial neural network, LoRAWAN channel, artificially intelligent, LoRa propagation loss models</text>
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                <text>ANN-based LoRaWAN Channel Propagation Model</text>
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