The Global Research Network for Verified Scholars

Penyadapan komunikasi elektronik tanpa dasar hukum dan prosedur yang sah dapat menimbulkan persoalan serius mengenai perlindungan privasi, keamanan informasi, serta akuntabilitas penggunaan kewenangan negara. Persoalan tersebut menjadi semakin penting ketika teknologi intersepsi berada dalam lingkungan institusi penegak hukum. Penelitian ini mengkaji aspek hukum dari pemberitaan mengenai dugaan penyadapan ilegal terhadap Presiden Republik Indonesia dan sejumlah pejabat pada November 2026. Fokus kajian meliputi batas kewenangan intersepsi, akses terhadap sistem elektronik, pengelolaan bukti digital, pertanggungjawaban individual, serta pembedaan antara dugaan tindak pidana penyadapan dan tindak pidana makar. Kajian dilakukan secara kualitatif-deskriptif dengan membedakan informasi publik yang diberitakan, dugaan yang memerlukan pembuktian, dan kesimpulan hukum yang menjadi wewenang peradilan.

This study explores the implementation of an intelligent energy management system for industrial buildings, leveraging the capabilities of artificial intelligence (AI) technologies. The approach integrates advanced data analytics, machine learning algorithms, and real-time monitoring to optimize energy consumption, enhance operational efficiency, and reduce costs. Key components include the deployment of sensors, implementation of AI-driven optimization algorithms for dynamic control of energy-consuming systems. The system also incorporates demand response strategies, automated control systems, and continuous learning mechanisms to adapt to changing conditions and user behavior. User engagement interfaces are designed to promote energy-efficient practices, and integration with renewable energy sources enhances sustainability. The study highlights the potential for significant cost savings, reduced environmental impact, and improved regulatory compliance through the intelligent management of industrial building energy based on AI technologies. To enhance the efficiency of energy-saving practices in industrial buildings by integrating artificial intelligence technology. This integration is used to analyze and manage the intelligent energy-saving systems in these buildings, ultimately leading to a reduction in energy consumption. The paper delves into the circuit structure, workflow, and functionality of energy-saving systems, explaining how they control electrical equipment and the specific hardware components involved. The paper also employs collected data to create a predictive model for energy consumption. Finally, an intelligent management system for conserving energy in industrial buildings is developed, considering various constraints and optimization criteria. The study's data analysis results indicate that this artificial intelligence-based energy-saving system is effective and has a significant impact on the overall energy management of industrial buildings.

The growth of mushrooms demands a very close monitoring of the environmental factors like temperature, humidity and air quality in order to achieve the best outcome in terms of growth and produce. These parameters are usually difficult to monitor and control manually, which results in decreased productivity and crop losses due to the possibility of human error. The paper gives a proposal of an IoT-based smart environmental management system on the cultivation of mushrooms that would allow automated monitoring, control and remote supervision of the mushroom farming huts. The proposed system combines temperature, humidity, gas, and fire sensors with a NodeMCU microcontroller to measure environmental conditions on the continuous basis. An automated water spraying mechanism and control logic is turned on when the humidity or temperature is out of range of predefined threshold values in order to restore the optimum conditions. This is achieved by enabling the turning on of an exhaust fan in the event of the harmful gases or smoke as well as fire detection turning on the water pump and ventilation system to avoid possible dangerous events. One can also manually operate the system from our mobile device itself as per our need. IoT connectivity transfers sensor data and system status to a mobile application enabling real-time monitoring, alert notifications, and manual control where necessary. The suggested system enhances the efficiency of the cultivation, safety, lowered human intervention, and contributes to sustainable farming practices related to mushroom cultivation as a result of intelligent environmental management.

The rising adoption of clean energy sources, grows the requirement to integrate these sources with electric vehicles (EVs) has led to the emergence of a need for advanced power-electronic interfaces which can ensure high efficiency, reliability and dynamic performance. This paper presents an advanced adopted integrated power electronics interface (IPEI) for EV applications where Bloom Energy and the Bloom Box solid oxide fuel cell (SOFC) system is the clean energy source for battery charging and power supply. The proposed IPEI consists of a bidirectional multidevice interleaved DC/DC converter (BMDIC) and an eight-switch inverter (ESI) to enable an integrated power conversion architecture for traction, regenerative braking, battery charging and grid-interactive operating modes. In the Bloom Box, the interconnected SOFC units are stacked to produce electrical power, and the power-electronic interface, a proposed design, conditions the power before delivering it to the EV battery. To realize current sharing, increase in the effective ripple frequency, reduction in current and voltage ripples, and reduction of passive component size, the BMDIC adopts the phase-shifted interleaved switching. To achieve good powertrain control, indirect field-oriented control (IFOC) using particle swarm optimization (PSO) is used for traction and regenerative braking, whereas dual-loop control is applied for the BMDIC and PWM current control is employed when the battery is being charged and discharged with PI compensators. The simulation and experimental results illustrate superior dynamic response, decreased semiconductor switching stress, decreased current and voltage ripples, improved power factor performance, and decreased input current total harmonic distortion (THD). The integrated architecture also enhances system reliability and the number of components and physical space needed for the EV powertrain.

Kekerasan Seksual Berbasis Elektronik (KSBE) di Indonesia telah mencapai tingkat yang mengkhawatirkan. Data Komnas Perempuan (CATAHU 2025) menunjukkan bahwa dari 1.091 kasus KBGO, sebanyak 977 kasus (90%) merupakan KBGO bersifat seksual. Sementara itu, data SAFEnet (2024) mencatat 1.902 laporan, dengan 23,24% korban adalah anak-anak. Meskipun Indonesia telah memiliki UU No. 12 Tahun 2022 tentang Tindak Pidana Kekerasan Seksual (UU TPKS) yang secara khusus mengatur KSBE, implementasinya masih menghadapi tantangan besar. Riset ini bertujuan memetakan titik-titik terputus (disconnects) dalam rantai perlindungan hukum korban KSBE di Indonesia. Menggunakan pendekatan yuridis-empiris (sosio-legal) dengan metode analisis dokumen dan studi literatur, riset ini mengidentifikasi tiga area kesenjangan utama: (1) konflik norma antara UU TPKS dan UU ITE dalam praktik penegakan hukum; (2) kesenjangan kapasitas aparat penegak hukum dan layanan forensik digital di daerah; (3) ketidakjelasan batas tanggung jawab platform digital. Riset ini menyimpulkan bahwa diperlukan harmonisasi regulasi, penguatan kapasitas penegak hukum, dan penetapan standar tanggung jawab platform yang terukur. Riset ini disusun oleh Ujang Trisno sebagai Direktur Riset Data Cyber Indonesia.

Kemampuan AI generatif dalam menghasilkan teks yang meyakinkan telah menjadi pedang bermata dua di bidang keamanan informasi. Di satu sisi, AI mempercepat analisis dan deteksi ancaman. Di sisi lain, fenomena halusinasi AI—di mana model menghasilkan informasi yang salah namun terlihat sangat kredibel—menciptakan risiko baru yang serius. Riset ini bertujuan menganalisis risiko halusinasi AI terhadap keamanan informasi melalui pendekatan literatur-kontekstual. Metode yang digunakan adalah Analisis Literatur Berbasis Risiko (Risk-Based Literature Analysis), yang menggabungkan sintesis literatur, pemetaan risiko, dan analisis kasus kontekstual. Hasil kajian menunjukkan bahwa halusinasi AI dapat diklasifikasikan ke dalam tiga tingkat risiko: (1) Kesalahan Informasi Ringan (misalnya salah menyebutkan tanggal CVE); (2) Fabrikasi Referensi dan Data (misalnya membuat CVE fiktif atau referensi palsu); dan (3) Eksploitasi Aktif (misalnya Slopsquatting, yaitu eksploitasi halusinasi paket perangkat lunak). Studi empiris juga menunjukkan bahwa manusia sulit mendeteksi halusinasi karena bias kognitif terhadap teks yang meyakinkan. Riset ini menyimpulkan bahwa halusinasi AI harus diperlakukan sebagai risiko keamanan kritis, bukan sekadar cacat produk, dan merekomendasikan penerapan protokol verifikasi berlapis serta pelatihan kritis bagi analis keamanan. Riset ini disusun oleh Ujang Trisno sebagai Direktur Riset Data Cyber Indonesia.

Sistem Pemantauan Karhutla Berbasis Satelit dan Kecerdasan Buatan: Evaluasi Integritas Data dan Kerentanan Informasi di Indonesia

Generation Z employees in technology-intensive workplaces increasingly seek meaningful work while facing uncertainty about job continuity and future skill relevance. How these contrasting work experiences relate to affective and normative commitment remains unclear in Malaysia’s information technology (IT) and digital sector. We analysed responses from 182 Generation Z employees using partial least squares structural equation modelling (PLS-SEM) to assess relationships among meaningful work, job insecurity, job satisfaction, affective commitment, and normative commitment. Meaningful work was positively associated with job satisfaction and both commitment dimensions, whereas job insecurity showed negative associations with all three outcomes. Higher job satisfaction was also associated with stronger affective and normative commitment. Bootstrap confidence intervals supported indirect associations of meaningful work and job insecurity with both commitment dimensions through job satisfaction, while the corresponding direct associations remained significant, a pattern consistent with complementary partial mediation. From a Job Demands–Resources (JD-R) perspective, the findings illustrate the concurrent roles of meaningful work as a job resource and job insecurity as a job demand in relation to job satisfaction and organisational commitment. For organisations managing young digital talent, the findings support meaningful job design, transparent communication during technological change, and sustained learning and reskilling opportunities. Together, the results clarify how positive and threatening work experiences are concurrently associated with commitment among Generation Z employees in a rapidly changing digital employment context

Dear Authors, We are excited to share that we have launched a new article collection, AI-Driven Proactive Health Care Education and Disease Prevention. We invite you to submit your contribution. The Collection is hosted by the Taylor & Francis journal, Critical Public Health, a gold open access journal with an Impact Factor of 2.6 (2025) and a CiteScore of 3.8 (2025). This Article Collection is an opportunity to highlight recent research advances. This article collection offers a chance to showcase recent developments in using artificial intelligence for proactive health education, early disease detection, and disease prevention across a range of demographics. By combining interdisciplinary research and cutting-edge methodologies, we aim to accelerate the adoption of AI-driven health solutions that empower patients, healthcare professionals, and broader communities. By creating this Collection, we hope to raise awareness of this topic and support its growth by providing a permanent, freely available body of work for our research community. The deadline to submit a manuscript is August 13th, 2027 We look forward to hearing from you. If you have any questions, please do not hesitate to ask. Best wishes, Article Collection Guest Editorial Team for AI-Driven Proactive Health Care Education and Disease Prevention Adjunct Research Professor Dr. Supaprawat Siripipatthanakul Associate Professor Astri D. Andriani, Ph.D. Assoc. Prof. Dr. Syamsul Hadi

Perovskite solar cells (PSCs) are an intriguing field of study due to their unique characteristics. This study aims to utilize the SCAPS-1D simulator to study the behaviour of absorbers in perovskite photocells that incorporate silver cadmium fluoride (AgCdF3). In this study, AgCdF3-based absorber material combined with 4 distinct ETLs namely PC60BM, SnS2, ZnSe and CdZnS and C6TBTAPH2 HTL in the structural proposed configuration of FTO/ETL/AgCdF3/C6TBTAPH2/Au. The materials have been chosen based on the proper band alignments. The influence of thickness, acceptor density, defect density for both HTL and absorber layer in addition to the donor density, defect density, and thickness of the ETLs are observed carefully. Several parameters including the thickness of absorber and ETL and acceptor density of absorber layer is optimized to find best performances. After all the optimization, the FTO/PC60BM/AgCdF3/C6TBTAPH2/Au structure has provided the highest power conversion efficiency (PCE) of 31.32 %, along with 0.86 V of open circuit voltage (VOC), 41.90 mA/cm2 of short circuit current (JSC) and 86.65 % of fill factor (FF). This simulation research allows scientists to develop cost-effective and efficient PSCs, advancing solar technology.