The rapid evolution of digital technology has reshaped workforce training paradigms, with Artificial Intelligence (AI) emerging as a transformative tool. This study investigates the opportunities and challenges of implementing AI-based training systems to enhance workforce skills in the digital era. Data were collected through surveys, in-depth interviews, and focus group discussions involving industry practitioners, AI developers, and workers. The results indicate a training effectiveness average of 70.2% (SD = 9.8) and satisfaction levels averaging 75.4% (SD = 8.5). Logistic regression analysis revealed a significant positive relationship between AI adoption and skill improvement, with a success probability of 68.9%. Despite these promising outcomes, challenges such as limited digital infrastructure, low digital literacy, and resistance to technology adoption persist, particularly in developing regions. This study provides strategic recommendations for inclusive digital transformation, emphasizing collaborative efforts between governments, private sectors, and educational institutions. These findings contribute to theoretical and practical knowledge for advancing AI-based training systems and fostering a sustainable, equitable workforce transformation.

Power efficiency and real-time performance are two essential aspects in the development of Internet of Things (IoT) systems, especially for temperature monitoring applications operated continuously with limited energy resources. This study aims to compare two widely used microcontroller platforms—ESP32 and Raspberry Pi Pico W—in the context of an IoT-based temperature monitoring system using the DHT22 sensor and Wi-Fi communication. A quantitative experimental approach was employed, including measurement of average power consumption, system response time, and initial booting time over more than 100 operation cycles. The results show that Raspberry Pi Pico W consumes significantly less power (90 mA) than ESP32 (160 mA). However, ESP32 outperformed in real-time response, recording an average latency of 240 ms, while Pico W recorded 310 ms. Pico W also demonstrated faster boot time (950 ms) compared to ESP32 (1500 ms), which is beneficial in deep sleep scenarios. These findings highlight a trade-off between power efficiency and system responsiveness. This study contributes practically by providing a technical basis for selecting suitable microcontroller platforms based on application-specific needs. The results may serve as a reference for developing energy-efficient and responsive embedded systems, particularly in agriculture, healthcare, and smart home sectors.

Tujuan Utama:  Tujuan utama dari penelitian ini adalah untuk menyediakan User-Interface (UI) berbasis web yang dapat mengatasi tantangan dan memberikan kontrol data secara real-time. Oleh karena itu, kami telah membuat prototipe User Interface yang dapat mendemonstrasikan konsep situs web pengelola IoT dan memberikan bukti penerapan konsep tersebut. Platform yang diusulkan dimaksudkan untuk berkontribusi dalam meningkatkan persepsi pengguna terhadap perangkat IoT. Background problem: Dengan kemajuan yang berkembang dalam teknologi Internet of Things (IoT), yang menggabungkan berbagai perangkat dengan fungsi, kemampuan, dan protokol komunikasi yang berbeda, penting untuk menyediakan platform yang memungkinkan pengguna IoT untuk berinteraksi dengan perangkat IoT mereka secara langsung dan dapat kelola mereka dengan mudah melalui platform itu dari berbagai lokasi kapan saja untuk melindungi privasi mereka saat menggunakan perangkat IoT. Metode Penelitian: Metode eksperimental dan survei digunakan dalam penelitian ini untuk mengevaluasi persepsi pengguna terhadap penggunaan sebuah platform yang menggabungkan semua perangkat IoT mereka dan memungkinkan mereka mengelola perangkat berdasarkan preferensi mereka melalui platform tersebut dan melindungi privasi mereka. Temuan: Temuan menunjukkan perlunya membuat platform di mana pengguna dapat mengontrol berbagai perangkat IoT dari jarak jauh. Ini juga menunjukkan bahwa prototipe situs web adalah platform yang mudah digunakan, dan dapat digunakan dengan mudah tanpa pengalaman teknis apa pun. Pengguna dapat mengakses informasi tentang perangkat IoT yang terhubung serta mengontrolnya. Kesimpulan: Prototipe dapat digunakan untuk mendemonstrasikan konsep aplikasi web yang diusulkan, sementara hasil survei menunjukkan kebutuhan untuk platform yang mudah digunakan untuk mengontrol perangkat IoT dari jarak jauh dan meningkatkan persepsi privasi pengguna di lingkungan IoT.

Intrusion Detection Systems (IDS) are an efficient defense against network attacks as well as host attacks as they allow network/host administrators to detect any policy violations. However, traditional IDS are vulnerable and unreliable for new malicious and genuine attacks. In other case, it is also inefficient to analyze large amount of data such as possibility logs. Furthermore, for typical OS, there are a lot of false positives and false negatives. There are some techniques to increase the quality and result of IDS where data mining is one of technique that is important to mining the information that useful from a large amount of data which noisy and random. The purpose of this study is to combine three technique of data mining to reduce overhead and to improve efficiency in intrusion detection system (IDS). The combination of clustering (Hierarchical) and two categories (C5, CHAID) is proposed in this study. The designed IDS is evaluated against the KDD'99 standard Data set (Knowledge Discovery and Data Mining), which is used to evaluate the efficacy of intrusion detection systems. The suggested system can detect intrusions and categorize them into four categories: probe, DoS, U2R (User to Root), and R2L (Remote to Local). The good performance of IDS in case of accuracy and efficiency was the result of this study.

Using different programming languages when software advancement is a familiar method in current software advancement. Nevertheless, using various languages that can hinder developer capacity is not widely known. This research simulated an unplanned controlled study examining the adoption of various languages in the situation of a directory programming task. Participants in this study were given programming tasks written in Java and one of three SQL-like embedded languages.  Simple “SQL” over authority, “Java” program only, and a more Java-like hybrid embedded language. Furthermore, to transcribe the responses to the online quest and the participators' “task” solutions, the participators' eye movements were also recorded with an eye tracker.
 “Eye Tracker” or in this study call as “Eye-Trc” is the methodology of the study of software development that has developed nowadays and grants more in-depth info about how developers accomplish programming tasks. This Eye-Trc method is used as a data collection method in this study. Eye-Trc data was get by thirty-one participators (university background and Industrial Background) for different programming tasks. To analyze the impact of inter-group inconstant and professional experience and in-group “task” variables on the dependent variable Time in completion, this study used a mixed model ANOVA. The outcome of this study indicates that an important impact on productivity was not found, this is different from the initial research because of the language used.
However, the same effect was found from the participators' expertise in programming activity indicating that more competent programmers were easy to full fill “polyglot programming tasks” more efficiently. In addition, it was raised that participators viewed the specimen code with the same proportion (time) for bringing “task” reckless of skills or language alternative provided. dominant-stage exploration management also remains mostly consistent over the experiences or language alternatives. Overall, it can be concluded that the programming stage of the linguist doesn’t have an important impact. The top-stage strategies that participators used came to be identical reckless of the language alternative presented to them. As a suggestion for future research, the impact of various characteristics of polyglot programming languages should be studied in depth for the conclusions reached to remain correct across various polyglot programming contexts.

Intrusion Detection Systems (IDS) are an efficient defense against network attacks as well as host attacks as they allow network/host administrators to detect any policy violations. However, traditional IDS are vulnerable and unreliable for new malicious and genuine attacks. In other case, it is also inefficient to analyze large amount of data such as possibility logs. Furthermore, for typical OS, there are a lot of false positives and false negatives. There are some techniques to increase the quality and result of IDS where data mining is one of technique that is important to mining the information that useful from a large amount of data which noisy and random. The purpose of this study is to combine three technique of data mining to reduce overhead and to improve efficiency in intrusion detection system (IDS). The combination of clustering (Hierarchical) and two categories (C5, CHAID) is proposed in this study. The designed IDS is evaluated against the KDD'99 standard Data set (Knowledge Discovery and Data Mining), which is used to evaluate the efficacy of intrusion detection systems. The suggested system can detect intrusions and categorize them into four categories: probe, DoS, U2R (User to Root), and R2L (Remote to Local). The good performance of IDS in case of accuracy and efficiency was the result of this study.

Pemetaan wilayah wilayah pemasaran menjadi salah satu alat yang dapat digunakan untuk menggambarkan suatu kegiatan usaha untuk mengetahui sasaran yang tepat dalam pelaksanaannya di wilayah kerja tertentu. Penelitian ini mencoba merancang pemetaan wilayah pemasaran, diharapkan dengan penelitian ini dapat meningkatkan rencana strategis pemasaran yang tepat sasaran. Sehingga dapat membantu manajemen Dealer X cabang demak dalam menentukan kebijakan pemasarannya. Dalam pemetaan ini menggunakan software QGis untuk pemetaan. Hasil dari penelitian ini adalah peta keluaran yang dapat digunakan sebagai bahan pertimbangan bagian pemasaran untuk memetakan wilayah pemasaran yang ada di wilayah yang ditentukan.