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"Practitioners in apparel manufacturing and retailing enterprises in the fashion industry, ranging from senior to front line management, constantly face complex and critical decisions. There has been growing interest in the use of artificial intelligence (AI) techniques to enhance this process, and a number of AI techniques have already been successfully applied to apparel production and retailing. Optimizing decision making in the apparel supply chain using artificial intelligence (AI): From production to retail provides detailed coverage of these techniques, outlining how they are used to assist decision makers in tackling key supply chain problems. Key decision points in the apparel supply chain and the fundamentals of artificial intelligence techniques are the focus of the opening chapters, before the book proceeds to discuss the use of neural networks, genetic algorithms, fuzzy set theory and extreme learning machines for intelligent sales forecasting and intelligent product cross-selling systems."

"Generative Artificial Intelligence (GAI) telah memegang penting dalam berbagai bidang, termasuk sebagai alat bantu pemrograman di Indonesia. Namun, penelitian mengenai adopsi GAI sebagai alat bantu pemrograman masih terbatas. Penelitian ini bertujuan menganalisis faktor yang memengaruhi niat karyawan di Indonesia untuk mengadopsi GAI dalam pemrograman, dengan fokus pada kualitas output kode dan kualitas sistem yang memengaruhi persepsi kegunaan serta kemudahan penggunaan GAI. Penelitian menggunakan metode PLS-SEM dalam analisis kuantitatif dengan 497 data valid, serta analisis kualitatif melalui wawancara 10 narasumber. Hasilnya menunjukkan bahwa persepsi kegunaan dipengaruhi oleh faktor presentation, structure, interactivity, responsiveness, understandability, assurance, dan reliability, sementara persepsi kemudahan penggunaan dipengaruhi oleh presentation, structure, responsiveness, assurance, dan reliability. Kedua persepsi ini memengaruhi niat adopsi GAI untuk pemrograman. Penelitian juga meneliti hubungan ini berdasarkan gender dan usia melalui analisis multigrup. Hasilnya memberikan saran bagi pengembang GAI untuk meningkatkan kualitas kode output dan sistem, yang terbukti memengaruhi persepsi pengguna tentang kegunaan dan kemudahan penggunaan GAI

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Generative Artificial Intelligence (GAI) has become significant in various fields, including as a programming aid in Indonesia. However, research on the adoption of GAI as a programming tool remains limited. This study aims to analyze the factors influencing employees in Indonesia to adopt GAI for programming, focusing on output code quality and system quality, which affect the perceived usefulness and ease of use of GAI. The study employs the PLS-SEM method for quantitative analysis with 497 valid data points and qualitative analysis through interviews with 10 informants. The results indicate that perceived usefulness is influenced by factors such as presentation, structure, interactivity, responsiveness, understandability, assurance, and reliability, while perceived ease of use is influenced by presentation, structure, responsiveness, assurance, and reliability. Both perceptions affect the intention to adopt GAI for programming. The study also examines these relationships based on gender and age using multigroup analysis. The findings provide practical suggestions for GAI developers to enhance the quality of output code and system, which significantly influence users' perceptions of the usefulness and ease of use of GAI."

"Generative Artificial Intelligence (GAI) telah memegang penting dalam berbagai bidang, termasuk sebagai alat bantu pemrograman di Indonesia. Namun, penelitian mengenai adopsi GAI sebagai alat bantu pemrograman masih terbatas. Penelitian ini bertujuan menganalisis faktor yang memengaruhi niat karyawan di Indonesia untuk mengadopsi GAI dalam pemrograman, dengan fokus pada kualitas output kode dan kualitas sistem yang memengaruhi persepsi kegunaan serta kemudahan penggunaan GAI. Penelitian menggunakan metode PLS-SEM dalam analisis kuantitatif dengan 497 data valid, serta analisis kualitatif melalui wawancara 10 narasumber. Hasilnya menunjukkan bahwa persepsi kegunaan dipengaruhi oleh faktor presentation, structure, interactivity, responsiveness, understandability, assurance, dan reliability, sementara persepsi kemudahan penggunaan dipengaruhi oleh presentation, structure, responsiveness, assurance, dan reliability. Kedua persepsi ini memengaruhi niat adopsi GAI untuk pemrograman. Penelitian juga meneliti hubungan ini berdasarkan gender dan usia melalui analisis multigrup. Hasilnya memberikan saran bagi pengembang GAI untuk meningkatkan kualitas kode output dan sistem, yang terbukti memengaruhi persepsi pengguna tentang kegunaan dan kemudahan penggunaan GAI

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Generative Artificial Intelligence (GAI) has become significant in various fields, including as a programming aid in Indonesia. However, research on the adoption of GAI as a programming tool remains limited. This study aims to analyze the factors influencing employees in Indonesia to adopt GAI for programming, focusing on output code quality and system quality, which affect the perceived usefulness and ease of use of GAI. The study employs the PLS-SEM method for quantitative analysis with 497 valid data points and qualitative analysis through interviews with 10 informants. The results indicate that perceived usefulness is influenced by factors such as presentation, structure, interactivity, responsiveness, understandability, assurance, and reliability, while perceived ease of use is influenced by presentation, structure, responsiveness, assurance, and reliability. Both perceptions affect the intention to adopt GAI for programming. The study also examines these relationships based on gender and age using multigroup analysis. The findings provide practical suggestions for GAI developers to enhance the quality of output code and system, which significantly influence users' perceptions of the usefulness and ease of use of GAI."

"Dunia saat ini berkembang pesat dengan kemampuan kecerdasan buatan (AI) untuk membuka cara-cara baru dan menarik untuk melibatkan pelanggan. Dengan memberikan penawaran inovatif dan pengalaman yang dipersonalisasi, AI memperkuat ikatan antara merek dan konsumen mereka, sehingga membedakan mereka dari para pesaing. Berdasarkan model Stimulus-Organism-Response (SOR), penelitian ini bertujuan untuk menganalisis bagaimana faktor stimulus dalam upaya pemasaran Artificial Intelligence (AI) berdampak pada perilaku loyalitas konsumen pada aplikasi layanan pesan antar makanan. Penelitian ini menggunakan pendekatan kuantitatif, deskriptif, dan survei cross-sectional. Structural Equation Model (SEM) digunakan untuk menganalisis 412 tanggapan dari survei kuesioner terhadap subjek Generasi Y dan Z yang menggunakan aplikasi pesan-antar makanan dari 2 platform terkemuka di industri ini, yaitu Gojek (GoFood) dan Grab (GrabFood). Hasil penelitian menunjukkan bahwa semua faktor stimulus dalam upaya pemasaran AI memengaruhi pengalaman merek, sementara hanya informasi dan interaksi yang memengaruhi ekuitas merek. Pengalaman dan ekuitas merek secara signifikan mempengaruhi tanggapan (preferensi merek dan niat penggunaan ulang). Implikasi dari penelitian ini dapat memungkinkan akademisi dan praktisi bisnis untuk memahami pengaruh AI terhadap pengalaman pengguna dan memberikan panduan untuk pengembangan strategi pemasaran dan branding untuk mengupayakan kepuasan pelanggan dengan menawarkan layanan online.

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Today's world thrives on artificial intelligence’s (AI) ability to unlock new and exciting ways to engage customers. By powering innovative offerings and personalized experiences, AI strengthens the bond between brands and their consumers, setting them apart from the competition. According to the Stimulus–Organism–Response (SOR) model, this study aims to analyze how stimulus factors in Artificial Intelligence (AI) marketing efforts impact consumer loyalty behavior in food delivery service applications. This research uses a quantitative, descriptive, and cross-sectional survey approach. Structural Equation Model (SEM) was used to analyze 412 responses from a questionnaire survey of Generation Y and Z subjects who used food delivery service applications from 2 leading platforms in the industry, such as Gojek (GoFood) and Grab (GrabFood). The results showed that all stimulus factors in AI marketing efforts affect brand experience, while only information and interaction affect brand equity. Both brand experience and equity significantly influence responses (brand preference and reuse intention).  Implications of this study can activate academia and business practitioners to understand the influence of AI on user experiences and provide a guide for the development of marketing and branding strategies to strive for customer satisfaction by offering online service."

"This book is to presents and evaluates a way of modelling and optimizing nonlinear RFID Network Planning (RNP) problems using artificial intelligence techniques. It uses Artificial Neural Network models (ANN) to bind together the computational artificial intelligence algorithm with knowledge representation an efficient artificial intelligence paradigm to model and optimize RFID networks.This effort leads to proposing a novel artificial intelligence algorithm which has been named hybrid artificial intelligence optimization technique to perform optimization of RNP as a hard learning problem. This hybrid optimization technique consists of two different optimization phases. First phase is optimizing RNP by Redundant Antenna Elimination (RAE) algorithm and the second phase which completes RNP optimization process is Ring Probabilistic Logic Neural Networks (RPLNN).The hybrid paradigm is explored using a flexible manufacturing system (FMS) and the results are compared with well-known evolutionary optimization technique namely Genetic Algorithm (GA) to demonstrate the feasibility of the proposed architecture successfully."

"The two LNAI volumes 7208 and 7209 constitute the proceedings of the 7th International Conference on Hybrid Artificial Intelligent Systems, HAIS 2012, held in Salamanca, Spain, in March 2012. The 118 papers published in these proceedings were carefully reviewed and selected from 293 submissions. They are organized in topical sessions on agents and multi agents systems, HAIS applications, cluster analysis, data mining and knowledge discovery, evolutionary computation, learning algorithms, systems, man, and cybernetics by HAIS workshop, methods of classifier fusion, HAIS for computer security (HAISFCS), data mining: data preparation and analysis, hybrid artificial intelligence systems in management of production systems, hybrid artificial intelligent systems for ordinal regression, hybrid metaheuristics for combinatorial optimization and modelling complex systems, hybrid computational intelligence and lattice computing for image and signal processing and nonstationary models of pattern recognition and classifier combinations."

"The two LNAI volumes 7208 and 7209 constitute the proceedings of the 7th International Conference on Hybrid Artificial Intelligent Systems, HAIS 2012, held in Salamanca, Spain, in March 2012. The 118 papers published in these proceedings were carefully reviewed and selected from 293 submissions. They are organized in topical sessions on agents and multi agents systems, HAIS applications, cluster analysis, data mining and knowledge discovery, evolutionary computation, learning algorithms, systems, man, and cybernetics by HAIS workshop, methods of classifier fusion, HAIS for computer security (HAISFCS), data mining, data preparation and analysis, hybrid artificial intelligence systems in management of production systems, hybrid artificial intelligent systems for ordinal regression, hybrid metaheuristics for combinatorial optimization and modelling complex systems, hybrid computational intelligence and lattice computing for image and signal processing and nonstationary models of pattern recognition and classifier combinations."

"This volume constitutes the thoroughly refereed conference proceedings of the 25th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2012, held in Dalian, China, in June 2012. The total of 82 papers selected for the proceedings were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on machine learning methods, cyber-physical system for intelligent transportation applications, AI applications, evolutionary algorithms, combinatorial optimization, modeling and support of cognitive and affective human processes, natural language processing and its applications, social network and its applications, mission-critical applications and case studies of intelligent systems, AI methods, sentiment analysis for asian languages, aspects on cognitive computing and intelligent interaction, spatio-temporal datamining, structured learning and their applications; decision making and knowledge based systems, pattern recognition, agent based systems, decision making techniques and innovative knowledge management, and machine learning applications."

"Budaya komunikasi yang diciptakan oleh suatu organisasi memainkan peran penting dalam keberhasilan adopsi AI. Penelitian ini bertujuan untuk menganalisis tahapan proses penerimaan Artificial Intelligence dalam bidang komunikasi pemasaran di industri B2B Indonesia. Menggabungkan teori Difusi Inovasi dan Technology-Organizational-Environmental Framework, penelitian ini menggunakan metode kualitatif dengan wawancara semi-terstruktur terhadap tiga informan yang bekerja di tiga industri B2B dengan sector berbeda. Hasil penelitian menunjukkan bahwa masing-masing individu melewati proses lima langkah: knowledge stage, persuasion stage, decision stage, implementation stage, serta confirmation stage. Terdapat dua jenis struktur organisasi yang ditemukan yang terbentuk dalam keputusan adopsi, yaitu struktur organisasi organik dimana lebih cocok untuk fase adopsi, serta struktur organisasi mekanistik yang lebih cocok untuk fase implementasi. Ketiga informan telah berhasil melakukan adopsi AI dikarenakan perilaku kepemimpinan manajemen perusahaan yang cenderung mengkomunikasikan serta mendukung pentingnya inovasi. Budaya komunikasi yang inovatif tidak dapat terlepas dari peran agen penghubung internal yang bersifat informal. Terdapat berbagai macam tools AI di divisi pemasaran industri B2B yang dapat diklasifikasikan berdasarkan fungsinya masing-masing, yaitu fungsi produksi konten, placement, analisis, dan Customer Service. Manfaat penggunaan AI yang dirasakan yaitu efisiensi waktu dan tenaga kerja, budget, manfaat terhadap kualitas konten dan growth marketing, dan peningkatan kreativitas karyawan. Biaya yang dikeluarkan oleh perusahaan dalam menginvestasikan AI tidak sebanding dengan outcome berupa keuntungan serta ketertarikan calon pelanggan kepada perusahaan menjadi lebih besar. Ketiga informan menyatakan bahwa penerapan AI saat ini sudah tepat guna serta akan dilanjutkan untuk membantu kegiatan perusahaan kedepannya.

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The communication culture created by an organization plays a vital role in the success of AI adoption. This research aims to analyze the stages of the process of accepting Artificial Intelligence in the field of marketing communications in the Indonesian B2B industry. Combining the Diffusion of Innovation theory and the Technology-Organizational Environmental Framework, this research uses qualitative methods with semi-structured interviews with three informants who work in three B2B industries with different sectors. The research results show that each individual goes through a five-step process: knowledge stage, persuasion stage, decision stage, implementation stage, and confirmation stage. There are two types of organizational structures found that are formed in adoption decisions, namely organic organizational structures which are more suitable for the adoption phase, and mechanistic organizational structures which are more suitable for the implementation phase. The three informants have succeeded in adopting AI due to the behavior of company management leadership which tends to communicate and support the importance of innovation. An innovative communication culture cannot be separated from the role of informal internal liaison agents. There are various kinds of AI tools in the B2B industrial marketing division which can be classified based on their respective functions, namely content production, placement, analysis and customer service functions. The perceived benefits of using AI are time and labor efficiency, budget, benefits to content quality and marketing growth, and increased employee creativity. The costs incurred by companies in investing in AI are not commensurate with the outcomes in the form of profits and the interest of potential customers in the company becomes greater. The three informants stated that the current application of AI is appropriate and will continue to help the company’s activities in the future."

"Privasi data menjadi perhatian krusial dalam lanskap bisnis saat ini, terutama dengan Big Data dan Analytics (BD&A) serta kecerdasan buatan (AI). Diulas melalui empat artikel, lanskap analitika bisnis yang terus berkembang membahas aspek sejarah, tantangan implementasi, dan perannya yang transformatif. Sambil menyoroti manfaat BD&A dan AI, esai menekankan kebutuhan mendesak akan kesadaran dan langkah-langkah proaktif untuk mengatasi isu privasi data. Esai ini menekankan dampak negatif dari pengumpulan data yang luas dan menganjurkan perlindungan informasi pribadi melalui regulasi yang ketat. Diskusinya menekankan kesiapan organisasi dan pengembangan kepemimpinan untuk mengatasi tantangan dalam adopsi BD&A sambil memastikan perlindungan data yang sensitif. Esai ini menyimpulkan dengan mengajak untuk lebih mendalami privasi data melalui studi kasus di masa depan untuk mengurangi risiko dalam penanganan informasi rahasia di lingkungan digital yang dinamis.

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Data privacy is a critical concern in today's business landscape, particularly with Big Data and Analytics (BD&A) and artificial intelligence (AI). Explored through four articles, the evolving business analytics landscape addresses historical aspects, implementation challenges, and its transformative role. While highlighting the benefits of BD&A and AI, the essay emphasizes the urgent need for awareness and proactive measures to address data privacy issues. It underscores the drawbacks of extensive data collection and advocates for safeguarding personal information through stringent regulations. The discussion stresses organizational readiness and leadership development to navigate challenges in BD&A adoption while ensuring sensitive data protection. The essay concludes by calling for deeper exploration of data privacy in future case studies to mitigate risks in handling confidential information in the dynamic digital environment."