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This study analyzes the impact of employee performance on customer satisfaction in using the PLN Mobile application at PT PLN (Persero) Unit Induk Wilayah Maluku and Maluku Utara. The study employs simple linear regression analysis, utilizing t-tests and F-tests to assess the significance of the relationship between variables. The findings reveal that employee performance has a positive and significant effect on customer satisfaction, with a regression coefficient of 0.787 and a significance value of < 0.001. The F-test results indicate that the regression model is valid and effectively explains variations in customer satisfaction, with an F-value of 1834.299, significantly exceeding the critical F-table value. Additionally, the high coefficient of determination (R²) suggests that most variations in customer satisfaction can be explained by employee performance. This study confirms that optimizing employee performance is a key factor in improving customer satisfaction, particularly in digital services such as PLN Mobile. Therefore, PT PLN (Persero) must enhance employee competence and service quality to support digital transformation and meet customer expectations.

The digital era brings new challenges and opportunities in Arabic language learning, so the development of innovative and adaptive curriculum-based teaching materials is very important. This article discusses innovations in the development of Arabic language teaching materials that utilize digital technology, such as multimedia, mobile applications, and interactive e-learning platforms, to create a more effective, engaging, and contextual learning experience. With a qualitative approach and case studies in secondary education environments, this study shows that the integration of technology in teaching materials can increase students' interest, motivation, and understanding of Arabic. In addition, this article identifies various obstacles, such as limited infrastructure and teacher readiness, and provides recommendations for sustainable development that is inclusive and responsive to the needs of the times. These findings are expected to be the basis for the development of Arabic language teaching materials that are relevant to the curriculum and able to answer the demands of learning in the digital era.

This study examines the implementation of a hybrid learning model to enhance sharia marketing skills through social media and mobile applications among creative economy actors. By combining online and face-to-face learning, the model aims to provide flexibility and a comprehensive learning experience aligned with sharia principles such as honesty and business ethics. This literature review analyzes supporting factors, challenges, and the effectiveness of hybrid learning in the context of sharia-based digital marketing. Findings indicate that hybrid learning significantly improves digital competencies and sharia marketing skills, provided there is adequate technological infrastructure, adaptive curriculum, and sufficient mentoring. Social media and mobile applications are proven effective tools for market expansion, yet challenges in technology access and digital literacy must be addressed to fully optimize digital marketing potential in accordance with Islamic values. The study offers strategic recommendations for developing relevant and practical sharia marketing training in the digital era.

The video editing training using the CapCut application at SMA Plus Nurul Mubin aimed to enhance students' digital skills in line with the competency demands of today's creative industry era. The training was conducted through hands-on learning, involving direct practice in various video editing techniques, from basic to advanced levels. Evaluation results showed that participants experienced a significant improvement in video editing skills, although several technical obstacles such as device and application limitations were encountered. In general, the training was considered successful in enhancing creativity, technical abilities, and participants' readiness to produce innovative digital content. These findings support previous studies that emphasize the effectiveness of mobile application-based training in improving the competitiveness of the younger generation in the workforce. Through the optimal use of CapCut, participants are expected to be more adaptive to future developments in digital technology.

This study aims to examine the effectiveness of the LingoDeer application as a learning medium for basic level Japanese language learners. A quantitative approach was employed using a One Group Pretest Posttest design involving 50 students from the Vocational School of IPB University. The research instrument consisted of pretest and posttest assessments focusing on three key areas: vocabulary, grammar, and reading skills. Based on the results of the paired sample t-test, a significant improvement was found in all aspects after the use of the application, with the average score increasing from 60.97% to 81.25%. The greatest improvement was observed in vocabulary, followed by reading and grammar. These findings suggest that LingoDeer, with its structured learning system, spaced repetition feature, and interactive exercises, can effectively support the development of Japanese language skills at the beginner level. This study is expected to serve as a reference for educators in selecting appropriate technology-based learning tools to enhance language acquisition.

This study uses a qualitative method with a case study approach to analyze the marketing strategies employed by Bank Syariah Indonesia (BSI) in increasing market share through the utilization of information technology. In the rapidly evolving digital era, the use of information technology has become a crucial factor for Islamic financial institutions to reach a wider customer base and provide more effective and efficient services. This study examines how BSI integrates digital technology into its marketing strategies, including the use of online platforms, mobile banking applications, and social media for product education and promotion. The findings reveal that the utilization of information technology not only improves service accessibility but also strengthens customer relationships through more personal and responsive interactions. This strategy contributes to increased customer loyalty and expands BSI’s market share amid competition in the Islamic banking industry. This study provides valuable insights for developing digital marketing in the Islamic financial sector that is adaptive to technological advancements.  

The rapid advancement of digital technology has transformed the landscape of language learning, particularly in the post-pandemic era where self-directed learning through mobile applications and online platforms is increasingly common. This study explores the effectiveness of two popular digital tools LuvLingua and YouTube in supporting independent Japanese language learning among Indonesian university students. LuvLingua offers a structured, gamified approach suitable for beginners, while YouTube provides authentic and contextual exposure through real-life content. Using a descriptive quantitative method, this research involved twelve students from non-language majors who actively use both platforms to study Japanese. The findings reveal that each platform has distinct advantages: LuvLingua excels in foundational vocabulary and pronunciation, whereas YouTube significantly enhances listening skills and cultural understanding. The combination of both platforms yields optimal learning outcomes, although success heavily depends on learners’ motivation, discipline, and time management. This study contributes to the growing body of research on technology-assisted language learning and provides practical recommendations for learners, educators, and content developers.

English proficiency is vital for academic and professional success in Indonesia, but students often struggle with writing. Descriptive text composition is challenging due to its intricate structure and linguistic elements. To overcome these challenges, the researcher suggests utilizing the Miro Application, a digital whiteboard tool known for fostering interactive collaboration and effectiveness in dynamic learning activities. The study aims to assess Miro's impact on enhancing 8th grade students' descriptive text writing skills at SMP Negeri 2 Sutojayan. The study utilizes a quantitative experimental approach, specifically a pre-experimental design, conducted at SMP Negeri 2 Sutojayan over one month, from November to December 2023. The population includes all 8th grade students, with a purposive sample of 31 students from a single recommended class. This research, conducted with 8th-grade students at SMP Negeri 2 Sutojayan, employed a one-group pre-test post-test design. Data analyses covered normality, homogeneity, and paired sample t-tests. Normality test values (0.095 and 0.088) aligned with good data distribution. Homogeneity test (0.067) affirmed data homogeneity, indicating methodical soundness. The hypothesis test for Miro Application based learning impact yielded a significant result (0.000 < 0.05). Miro Application significantly affected post-test scores, presented digitally via mobile phones. Finally, The Miro Application demonstrated effectiveness in enhancing descriptive text writing skills.

Handling drug abuse is one of the main focuses in the Prevention and Eradication of Drug Abuse and Illicit Trafficking (P4GN) efforts in Indonesia. In this context, medical and social rehabilitation plays an important role as a recovery effort for addicts to return to optimal functioning in society. This community service activity uses a qualitative approach with a combination of observation, interview, and digital-based direct intervention methods in handling medical and social rehabilitation for drug abusers. This community service activity successfully implemented a digital-based medical and social rehabilitation strategy in supporting the P4GN program with a smart power approach. A web-based information system and mobile application designed to facilitate registration, monitoring, and mentoring of rehabilitation patients were successfully developed. This system provides easy access to information for the community and drug abusers to register and obtain rehabilitation services efficiently without having to come directly to the rehabilitation facility. The digital rehabilitation system is integrated with national electronic medical record platforms (such as SIRENA and the Ministry of Health's SATU SEHAT service), thus facilitating coordination between institutions and ensuring continuous monitoring of client health during and after the rehabilitation period. This community service activity successfully demonstrated that the handling of medical and social rehabilitation in a digital-based P4GN strategy with a smart power approach is an effective solution in an effort to realize a drug-free society. The smart power approach that integrates hard power (law enforcement) and soft power (prevention, community empowerment, and rehabilitation) with the support of digital information technology can improve the accessibility, effectiveness, and quality of rehabilitation services.

Research aims to design and develop a boiler system for heating Marine Fuel Oil (MFO) 180 CST by integrating Internet of Things (IoT) technology to enhance efficiency and operational monitoring. The methods used include boiler system design, selection of types and materials according to international standards, and the implementation of an optimal combustion system. IoT sensors are strategically placed to monitor key parameters such as temperature, pressure, and fluid flow in real-time. The collected data is transmitted to a cloud platform, enabling remote monitoring and automated performance analysis through a web or mobile-based application.. The research results indicate that IoT integration in the boiler system improves fuel heating efficiency, optimizes energy consumption, and facilitates easier monitoring and process control. Testing includes pressure tests, combustion efficiency, steam capacity, and material durability, with real-time monitoring to support performance analysis and early problem detection. Operational data evaluation allows for design adjustments or system settings to further enhance energy efficiency. With this innovation, the boiler system can operate more optimally, support energy efficiency, and facilitate predictive maintenance for sustainable industrial operations. The implementation of IoT in this system is expected to improve safety, effectiveness, and automation in boiler management, making it a more reliable and modern solution.

This study aims to design and build a hydraulic system capable of operating hatch opening and closing automatically and manually, with the application of Internet of Things (IoT) technology to monitor and control the system remotely. This system is designed to improve efficiency and ease of hatch operation on ships or other industrial applications, as well as prevent fires in cargo due to several factors such as unintentional negligence of the ship's crew and also weather factors with increasing temperatures. Where the automatic system uses a rain sensor to optimize time and energy, while manual control remains available as a backup option. This design involves the integration of hydraulic actuators, rain drop sensors, microcontrollers, and IoT communication modules that allow users to control and monitor the position of the hatch through a web-based application or mobile device. In compiling this scientific paper, researchers use experimental methods. This study shows the results that testing will be carried out directly by researchers, by testing the performance of the prototype of the automatic and manual hatch opening and closing hydraulic system design tool based on IoT by testing the effectiveness of the control system and sensor performance. In conclusion, this system successfully combines hydraulic and IoT technology to create an efficient, safe, and easy-to-use solution in practical applications.

Public service is an essential element that reflects the quality of governance in Indonesia, particularly in population administration, which includes the issuance of important documents such as ID cards (KTP), family cards (KK), birth certificates, and death certificates. Along with technological advancements, Indonesia launched the Digital Population Identity (IKD) application to improve efficiency and reduce reliance on physical documents. This study aims to evaluate the positive public’s response of the IKD application in Singosari District, Malang Regency, as well as to identify the challenges and factors influencing the implementation of this policy. The research method used is descriptive qualitative research with approaches such as interviews, observations, and documentation. The findings show that although the IKD application facilitates the administrative process, there are still challenges such as a lack of public’s response, limited mobile device availability, and technical issues with the application. Socialization through social media and the improvement of operator capacity are key supporting factors for the success of the implementation. This study contributes theoretically to the development of E-Governance concepts and practically highlights the importance of digital education for the public. It is suggested that enhanced socialization for groups less familiar with technology, improved supporting infrastructure, and training for service operators are necessary to ensure the success of the IKD application in population administration services in Singosari District.

This study aims to analyze the effectiveness of Drops app in improving Japanese vocabulary acquisition among beginners. Based on the theory of cognitivism, the study used a descriptive qualitative method with a sample of 21 subjects who answered 11 questions through a Google Form survey. Results showed that the use of Drops significantly increased the average vocabulary score by 43 % (from 28.5 to 40.7), which was influenced by the integration of gamification features and spaced repetition mechanism in the application. The majority of respondents (76 %) reported high satisfaction with ease of use, learning motivation, and effectiveness of visual illustrations, consistent with previous research on audiovisual and gamification-based mobile apps. However, about 24 % of respondents recorded medium to low scores on motivational aspects and interface appearance, indicating the need for UX/UI enhancements to expand adoption. Demographic statistics revealed the average age of respondents to be 18.38 years (Q1=17; median=18; Q3=20), confirming that teenagers and pre-adults are the main group of Drops users. The findings provide recommendations for both language education practitioners and app developers to optimize design and features to maximize vocabulary learning effectiveness.

Image classification is a key field in digital image processing with broad applications, such as object recognition and disease detection. The use of artificial neural network architectures, such as MobileNetV2, has significantly advanced pattern recognition in large datasets. However, in small datasets, challenges related to accuracy and generalization are often encountered. This study explores an RGB-based approach utilizing MobileNetV2 for image feature extraction and Support Vector Machine (SVM) as the classifier. MobileNetV2 is applied to extract features from RGB images, which are then further processed by SVM to determine image classes. The results indicate that this model achieves an accuracy of 91.67%, precision of 0.9163, recall of 0.9167, and F1-score of 0.9161. Based on the confusion matrix analysis, the model effectively distinguishes between classes, despite slight overlaps. This research contributes to the development of intelligent image classification systems that can be applied in various fields, including the food industry. With these achievements, the RGB approach integrating MobileNetV2 and SVM has proven effective in enhancing image classification accuracy, even with relatively small datasets. These findings open opportunities for applying similar methods in other image processing tasks that require high accuracy in object or disease detection and classification.

The development of an Android mobile application for automatic cataract detection using Convolutional Neural Network (CNN) and TensorFlow has been conducted. The aim of this research is to provide an easily accessible solution for the public to detect cataracts early, thereby reducing the negative impact of this eye condition. The CNN method is utilized to recognize cataract patterns through image data, with TensorFlow serving as the primary development platform. Preprocessing steps and data processing are implemented to enhance the detection accuracy and address variations in eye images. Evaluation indicates that the application is capable of detecting cataracts with satisfactory accuracy, making it a potential tool for cataract prevention and early management. In conclusion, this application enables rapid and efficient cataract detection, improving the accessibility of eye care and contributing to enhancing overall quality of life for communities by providing early intervention and treatment options.

This paper aims to overcome the problem of manual financial recording that is still commonly used by MSMEs, which often causes data loss and inefficiency in financial management. To answer this challenge, researchers developed a mobile-based financial recording application using Flutter and a number of available supporting packages. This application is designed to be able to record and store income and expenditure data directly on the user's mobile device, making it easier for MSMEs to monitor their financial condition in real time. The development was carried out using a waterfall model approach, which includes the stages of analysis, design, implementation, and testing. To test the functional performance of the application, the Black Box testing method is used to assess the accuracy and reliability of the features without looking at the internal code structure. The test results show that all features can function as they should and the application is considered effective in supporting digital MSME financial recording.

The increasing waste problem requires innovative solutions that are efficient and sustainable. This study aims to design and build an Internet of Things (IoT) based garbage cleaning robot that can be monitored and controlled remotely. This system is designed by utilizing a microcontroller as the main brain, sensors to detect the presence of garbage, and an IoT-based communication module that allows monitoring and control of the robot via mobile devices or the web. Based on the results of the analysis and testing carried out, this study shows that the use of ESP8266 in the RC Trans Robot motor control with the Blynk application has succeeded in significantly increasing system efficiency. The system successfully responds to user input via a mobile application and can control the movement of the robot in real-time. The performance of the robot system controlled via a WiFi network shows good stability in various test scenarios. The robot can operate effectively within a distance that matches the range of the WiFi network, with fast control response and reliable communication.

This study aims to analyze digital technology-based Islamic Religious Education (PAI) learning strategies in an effort to enhance religious literacy and strengthen Islamic values in the lives of modern students. Using a literature research method, this study collects and analyzes various literature sources, such as books, scientific journals, articles, and related documents, that discuss the integration of digital technology in PAI learning. The results indicate that digital technologies, such as e-learning, social media, mobile applications, gamification, and virtual reality, play a significant role in creating more interactive, engaging, and effective learning processes. This strategy not only improves students' understanding of religious materials but also helps them internalize Islamic values in their daily lives. Additionally, digital technology enables access to a wider range of learning resources, encourages personalized and adaptive learning, and opens opportunities for more participatory collaboration and discussion. However, the implementation of this strategy also faces challenges, such as the digital divide, infrastructure limitations, and a lack of digital competence among educators. Therefore, collaborative efforts are needed to address these challenges, including training for educators, improving access to technology, and curriculum adjustments. Overall, this study concludes that digital technology-based PAI learning strategies are an effective approach to enhancing religious literacy and strengthening Islamic values in the lives of modern students, while also preparing the younger generation to face global challenges while adhering to Islamic principles.

This community service activity (PKM) aims to improve the ability of teachers and students at SMP, SMA, and SMK in Negeri Weet to use the socrative platform or application as a medium for digital learning and assessment. The method used in this activity is the service learning method, which is divided into material presentation, interactive discussions, simulations, and training on using the Socrative application. In using this application in the classroom, teachers can provide quizzes directly to students, as it can be accessed using computers or students' mobile phones. This application not only helps students learn but also makes it easier for teachers to provide assessments. Using this application in the classroom also provides benefits, such as building good interactions between teachers, students, and classmates. This is supported by several features that facilitate teachers and students, including quick questions, space race, and exit ticket, polling, and discussion. Thus, activities in the learning space become more lively and enjoyable. This PKM activity involved 23 participants, consisting of 7 teachers and 16 students representing the three schools. The results of the activity show that teachers and students were very enthusiastic and active in following the material presentation sessions, discussions, simulations, and training. This activity had a positive impact on improving teachers' and students' abilities in using digital learning technology and assessment.

This research presents a personalized, context-aware recommender system to suggest Places of Interest (POIs) using a hybrid approach combining Bayesian inference and collaborative filtering. The system explicitly addresses the cold-start problem that new users face and improves recommendation accuracy by considering contextual variables such as user mood, budget, companion, and location. The system collects real-time contextual inputs for new users with no historical data and applies Bayesian inference to generate relevant POI suggestions. As users begin to interact and provide ratings, the system progressively shifts to a collaborative filtering mechanism, leveraging cosine similarity to identify similar users within comparable contexts. The recommender system focuses on three categories of POIs: restaurants, hotels, and landmarks. These locations are retrieved through the Google Maps API, and only mapped locations are considered. The system was implemented on Android devices and evaluated through a user study involving 25 participants from diverse backgrounds, including software developers, IT students, and general users. Evaluation metrics such as normalized Discounted Cumulative Gain (nDCG) and classification accuracy were used to assess recommendation quality. Results demonstrate that the system performs better than traditional methods, with nDCG improvements reaching up to 83 percent. Users reported high satisfaction regarding the recommendations' accuracy, ease of use, and contextual relevance. While the system offers significant improvements, it also has certain limitations. Its dependency on Google Maps data may restrict its scope, and using only four contextual factors limits the system’s adaptability to more complex user preferences. Future enhancements could include additional dynamic contexts such as weather, POI popularity, and time-related trends, as well as integrating more advanced models to increase personalization and flexibility in real-world applications.