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"Perkembangan teknologi kecerdasan buatan (AI) telah memberikan dampak signifikan pada industri desain, salah satunya melalui penggunaan plugin AI di Figma yang meningkatkan efisiensi kerja dan hasil inovatif dalam alur kerja yang kompleks. Penelitian ini bertujuan untuk menganalisis pengaruh karakteristik tugas dan teknologi dari teori TTF serta faktor-faktor dalam teori UTAUT terhadap niat pengguna dalam menggunakan plugin AI di Figma. Dengan pendekatan mixed-method, data dikumpulkan melalui wawancara secara daring dengan 12 responden dan menyebarkan kuesioner kepada 466 responden. Melalui analisis kualitatif ditemukan tiga dimensi task characteristic (task variability, task time sensitivity, dan task creativity) serta empat dimensi technology characteristic (perceived intelligence, adaptability, responsiveness, dan perceived novelty). Pengolahan data kuantitatif dilakukan dengan metode Structural Equation Model Partial Least Square (PLS-SEM). Hasil penelitian ini menunjukkan bahwa task-technology fit, performance expectancy, effort expectancy, social influence, dan perceived risk memengaruhi niat penggunaan plugin AI di Figma, terkecuali untuk facilitating conditions yang tidak berpengaruh secara signifikan. Pendekatan ini diharapkan memberikan wawasan tentang faktor-faktor yang memengaruhi niat awal pengguna dan menjadi panduan bagi pengembang AI untuk mendorong adopsi teknologi AI dalam desain.

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The development of artificial intelligence (AI) technology has had a significant impact on the design industry, particularly through the use of AI plugin in Figma that enhance work efficiency and foster innovative outcomes in complex workflows. This research aims to analyze the influence of task and technology characteristics from the Task-Technology Fit (TTF) theory, as well as factors from the Unified Theory of Acceptance and Use of Technology (UTAUT), on users' intention to use AI plugin in Figma. Using a mixed-method approach, data was collected through online interviews with 12 respondents and a questionnaire distributed to 466 respondents. Qualitative analysis identified three dimensions of task characteristics (task variability, task time sensitivity, and task creativity) and four dimensions of technology characteristics (perceived intelligence, adaptability, responsiveness, and perceived novelty). Quantitative data analysis was conducted using the Structural Equation Model Partial Least Square (PLS-SEM) method. The results of this study reveal that task-technology fit, performance expectancy, effort expectancy, social influence, and perceived risk influence the intention to use AI plugin in Figma, except for facilitating conditions, which did not have a significant effect. This approach is expected to provide insights into the factors influencing initial user intention and serve as a guide for AI developers to promote the adoption of AI technology in design."

"Perkembangan teknologi kecerdasan buatan (AI) telah memberikan dampak signifikan pada industri desain, salah satunya melalui penggunaan plugin AI di Figma yang meningkatkan efisiensi kerja dan hasil inovatif dalam alur kerja yang kompleks. Penelitian ini bertujuan untuk menganalisis pengaruh karakteristik tugas dan teknologi dari teori TTF serta faktor-faktor dalam teori UTAUT terhadap niat pengguna dalam menggunakan plugin AI di Figma. Dengan pendekatan mixed-method, data dikumpulkan melalui wawancara secara daring dengan 12 responden dan menyebarkan kuesioner kepada 466 responden. Melalui analisis kualitatif ditemukan tiga dimensi task characteristic (task variability, task time sensitivity, dan task creativity) serta empat dimensi technology characteristic (perceived intelligence, adaptability, responsiveness, dan perceived novelty). Pengolahan data kuantitatif dilakukan dengan metode Structural Equation Model Partial Least Square (PLS-SEM). Hasil penelitian ini menunjukkan bahwa task-technology fit, performance expectancy, effort expectancy, social influence, dan perceived risk memengaruhi niat penggunaan plugin AI di Figma, terkecuali untuk facilitating conditions yang tidak berpengaruh secara signifikan. Pendekatan ini diharapkan memberikan wawasan tentang faktor-faktor yang memengaruhi niat awal pengguna dan menjadi panduan bagi pengembang AI untuk mendorong adopsi teknologi AI dalam desain.

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The development of artificial intelligence (AI) technology has had a significant impact on the design industry, particularly through the use of AI plugin in Figma that enhance work efficiency and foster innovative outcomes in complex workflows. This research aims to analyze the influence of task and technology characteristics from the Task-Technology Fit (TTF) theory, as well as factors from the Unified Theory of Acceptance and Use of Technology (UTAUT), on users' intention to use AI plugin in Figma. Using a mixed-method approach, data was collected through online interviews with 12 respondents and a questionnaire distributed to 466 respondents. Qualitative analysis identified three dimensions of task characteristics (task variability, task time sensitivity, and task creativity) and four dimensions of technology characteristics (perceived intelligence, adaptability, responsiveness, and perceived novelty). Quantitative data analysis was conducted using the Structural Equation Model Partial Least Square (PLS-SEM) method. The results of this study reveal that task-technology fit, performance expectancy, effort expectancy, social influence, and perceived risk influence the intention to use AI plugin in Figma, except for facilitating conditions, which did not have a significant effect. This approach is expected to provide insights into the factors influencing initial user intention and serve as a guide for AI developers to promote the adoption of AI technology in design."

"Perkembangan teknologi kecerdasan buatan (AI) telah memberikan dampak signifikan pada industri desain, salah satunya melalui penggunaan plugin AI di Figma yang meningkatkan efisiensi kerja dan hasil inovatif dalam alur kerja yang kompleks. Penelitian ini bertujuan untuk menganalisis pengaruh karakteristik tugas dan teknologi dari teori TTF serta faktor-faktor dalam teori UTAUT terhadap niat pengguna dalam menggunakan plugin AI di Figma. Dengan pendekatan mixed-method, data dikumpulkan melalui wawancara secara daring dengan 12 responden dan menyebarkan kuesioner kepada 466 responden. Melalui analisis kualitatif ditemukan tiga dimensi task characteristic (task variability, task time sensitivity, dan task creativity) serta empat dimensi technology characteristic (perceived intelligence, adaptability, responsiveness, dan perceived novelty). Pengolahan data kuantitatif dilakukan dengan metode Structural Equation Model Partial Least Square (PLS-SEM). Hasil penelitian ini menunjukkan bahwa task-technology fit, performance expectancy, effort expectancy, social influence, dan perceived risk memengaruhi niat penggunaan plugin AI di Figma, terkecuali untuk facilitating conditions yang tidak berpengaruh secara signifikan. Pendekatan ini diharapkan memberikan wawasan tentang faktor-faktor yang memengaruhi niat awal pengguna dan menjadi panduan bagi pengembang AI untuk mendorong adopsi teknologi AI dalam desain.

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The development of artificial intelligence (AI) technology has had a significant impact on the design industry, particularly through the use of AI plugin in Figma that enhance work efficiency and foster innovative outcomes in complex workflows. This research aims to analyze the influence of task and technology characteristics from the Task-Technology Fit (TTF) theory, as well as factors from the Unified Theory of Acceptance and Use of Technology (UTAUT), on users' intention to use AI plugin in Figma. Using a mixed-method approach, data was collected through online interviews with 12 respondents and a questionnaire distributed to 466 respondents. Qualitative analysis identified three dimensions of task characteristics (task variability, task time sensitivity, and task creativity) and four dimensions of technology characteristics (perceived intelligence, adaptability, responsiveness, and perceived novelty). Quantitative data analysis was conducted using the Structural Equation Model Partial Least Square (PLS-SEM) method. The results of this study reveal that task-technology fit, performance expectancy, effort expectancy, social influence, and perceived risk influence the intention to use AI plugin in Figma, except for facilitating conditions, which did not have a significant effect. This approach is expected to provide insights into the factors influencing initial user intention and serve as a guide for AI developers to promote the adoption of AI technology in design."

"This proceedings volume chronicles the papers presented at the 35th CIB W78 2018 Conference: IT in Design, Construction, and Management, held in Chicago, IL, USA, in October 2018. The theme of the conference focused on fostering, encouraging, and promoting research and development in the application of integrated information technology (IT) throughout the life-cycle of the design, construction, and occupancy of buildings and related facilities. The CIB – International Council for Research and Innovation in Building Construction – was established in 1953 as an association whose objectives were to stimulate and facilitate international cooperation and information exchange between governmental research institutes in the building and construction sector, with an emphasis on those institutes engaged in technical fields of research. The conference brought together more than 200 scholars from 40 countries, who presented the innovative concepts and methods featured in this collection of papers."

"ABSTRAKBatasan berupa aturan (rule) merupakan suatu alat yang digunakan untuk membatasi jumlah dan pembentukan produk varian dari kombinasi nilai komponen pembentuknya. Aturan tersebut digunakan sebagai dasar penenman kombinasi yang valid dari semua nilai karakteristik komponen pembentuk yang tersusun dalam configurable material yang sesuai dengan aspek-aspek yang berhubungan dengan pembentukan suatu produk.Pada skripsi ini, akan dibahas tentang pembentukan aturan unluk proses konfigurasi varian sebagai produk jadi yang dihasilkan oleh PT X berupa alat angkat jenis forklift. Penyusunan aturan ini dilakukan dengan menerapkan SAP R/3 System yang menyediakan sarana tersebut dengan menggnmakan istilah Object Dependency.Pembentukan Object Dependency pada SAP R/3 merupakan basic data dari sistem perencanaan produksi. Hasil dari pembentukan Object Dependency bertujuan untuk mempermudah proses konigurasi vauian yang digunakan dalam pembentukan customer order yang juga didukung oleh SAP R/3. Dengan penggunaan Object Dependency ini diharapkan PT X dapat memproduksi beberapa jenis produk vaxian untuk jenis forklift yang memenuhi selera konsumen (customer - oriented).

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"Perkembangan teknologi telah memberikan kemudahan bagi sejumlah pihak, salah satunya dalam membangun hubungan pelanggan. Hubungan pelanggan dapat dibangun serta dipelihara melalui sistem yang terintegrasi antara CRM dan AI. Keduanya memberikan solusi bagi perusahaan maupun institusi lainnya untuk memperoleh data serta memenuhi kebutuhan pelanggan. Oleh sebab itu, tulisan ini ingin melihat efektivitas penggunaan CRM dan AI dalam mengelola pelanggan yang bertujuan untuk mengetahui kebutuhan maupun perilaku para pelanggannya. CRM yang telah terintegrasi oleh AI, memberikan manfaat yang besar dibandingkan CRM tradisional. Atas manfaat yang diperoleh, CRM yang terintegrasi dengan AI sangat membantu perusahaan dalam efisiensi waktu maupun biaya serta efektivitas dalam pemenuhan kebutuhan pelanggan serta penyelesaian permasalahan yang sedang dihadapi. Dengan demikian, penggunaan CRM dan AI secara bersamaan dinilai lebih efektif dibandingkan dengan CRM tradisional.

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Technological developments have made things easier for several parties, one of which is building customer relationships. Customer relationships can be built and maintained through an integrated system between CRM and AI. Both provide solutions for companies and other institutions to obtain data and meet customer needs. Therefore, this paper wants to see the effectiveness of using CRM and AI in managing customers to know the needs and behaviors of customers. CRM that has been integrated with AI provides great benefits compared to traditional CRM. Due to the benefits obtained, CRM integrated with AI helps companies in terms of time and cost efficiency as well as effectiveness in meeting customer needs and resolving the problems they are facing. Thus, using CRM and AI together is considered more effective than traditional CRM."

"Perkembangan teknologi Artificial Intelligence (AI), terkhusus AI text generators (AITGs), telah membawa perubahan signifikan dalam kehidupan manusia di Indonesia. Kehadiran AITGs berhasil mengubah perilaku seseorang mencapai berbagai tujuan, misalnya sebagai sumber belajar dan berpotensi menggantikan popularitas Google SE sebagai penyedia informasi paling populer saat ini. Penelitian ini bertujuan untuk memahami lebih jauh fenomena perpindahan dari Google SE ke AITGs dan memahami faktor-faktor yang memengaruhi terjadinya perilaku ini. Penelitian ini menggunakan kerangka PPM sebagai acuan pembentukan model. Penelitian ini melakukan analisis kualitatif terhadap 11 responden dan analisis kuantitatif terhadap 491 responden. Analisis data dilakukan dengan menggunakan grounded theory dan PLS-SEM modelling menggunakan bantuan aplikasi SmartPLS 4. Hasil penelitian ini mengungkapkan bahwa faktor low searching performance, explainability, inertia, perceived usefulness, social interaction, dan adaptability berpengaruh terhadap intensi berpindah dari Google SE ke AITGs. Sebaliknya, faktor privacy concern, intrusiveness of advertisement, perceived risk, dan perceived ease of use tidak berpengaruh secara signifikan terhadap intensi berpindah dari Google SE ke AITGs. Hasil tersebut diharapkan dapat membuka peluang bagi pengembangan ilmu pengetahuan secara umum dan terkhusus dalam konteks AITGs sebagai sumber belajar. Penelitian ini diharapkan dapat menjadi sumber informasi bagi masyarakat terkait AITGs sebagai sumber belajar, acuan bagi akademisi dan pengajar dalam penyusunan kurikulum dan aturan, serta bermanfaat bagi pelaku bisnis dan pengembang untuk meningkatkan fungsionalitas yang sesuai dengan kebutuhan masyarakat.

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The development of Artificial Intelligence (AI) technology, especially AI text generators (AITGs), has brought significant changes to human life in Indonesia. The presence of AITGs has succeeded in changing a person's behavior to achieve various goals, for example as a learning resource, and has the potential to replace the popularity of Google SE as the most popular information provider today. This research aims to understand further the phenomenon of moving from Google SE to AITGs and understand the factors that influence this behavior. This research uses the PPM framework as a reference for model formation. This research conducted a qualitative analysis of 11 respondents and a quantitative analysis of 491 respondents. Data analysis was carried out using grounded theory and PLS-SEM modeling using the SmartPLS 4 application. The results of this study revealed that the factors of low searching performance, explainability, inertia, perceived usefulness, social interaction, and adaptability influenced the intention to switch from Google SE to AITGs. On the other hand, the factors of privacy concern, intrusiveness of advertisement, perceived risk, and perceived ease of use do not significantly influence the intention to switch from Google SE to AITGs. It is hoped that these results will open up opportunities for the development of knowledge in general and specifically in the context of AITGs as a learning resource. It is hoped that this research can be a source of information for the community regarding AITGs as a learning resource, a reference for academics and teachers in preparing curricula and regulations, as well as being useful for business people and developers to improve functionality by community needs."