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"Perkembangan teknologi dan penggunaan keceerdasan buatan yang pesat menekankan pentingnya mempertahankan pelanggan dalam menghadapi persaingan yang ketat, khususnya di sektor telekomunikasi. Salah satu penerapan utama kecerdasan buatan yang sudah banyak diterapkan adalah chatbot untuk layanan pelanggan. Namun, dalam implementasinya masih terdapat kesenjangan antara kualitas layanan chatbot yang dikembangkan dan harapan pelanggan, yang dapat menyebabkan keraguan dalam melanjutkan penggunaan teknologi tersebut. Penelitian ini menggunakan Technology Acceptance Model (TAM) untuk memprediksi faktor-faktor yang mempengaruhi niat keberlanjutan penggunaan chatbot sebagai saluran pelayanan pelanggan pada perusahaan operator seluler. Hasil analisis dengan menggunakan PLS-SEM terhadap 303 responden pelanggan operator seluler di Indonesia menunjukkan bahwa terdapat tiga prediktor utama keberlanjutan penggunaan chatbot, yaitu persepsi kebergunaan, kepercayaan, dan norma subjektif. Berdasarkan hasil analisis hipotesis, disusun 10 rangkaian strategi menggunakan model integrasi IPA-Kano. Strategi-strategi yang diprioritaskan kemudian direkomendasikan untuk diterapkan oleh perusahaan operator seluler di Indonesia dalam mendukung keberlanjutan penggunaan teknologi chatbot dari sisi pelanggan.

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The rapid development of technology and the use of artificial intelligence underscore the importance of retaining customers in the face of fierce competition, particularly in the telecommunications sector. One of the main applications of artificial intelligence that has been widely implemented is chatbots for customer service. However, in its implementation, there remains a gap between the quality of chatbot services developed and customer expectations, which can lead to doubts about continuing to use the technology. This study uses the Technology Acceptance Model (TAM) to predict the factors influencing the continuous intention to use chatbots as a customer service channel in cellular operator companies. The results of the analysis using PLS-SEM on 303 respondents of cellular operator customers in Indonesia show that there are three main predictors of continuous use of chatbots, which are perceived usefulness, trust, and subjective norms. Based on the hypothesis analysis results, 10 series of strategies using the IPA-Kano integration model is developed. The prioritized strategies are then recommended to be implemented by cellular operator companies in Indonesia to support the continuous use of chatbot technology from the customer's perspective."

"Penelitian ini bertujuan untuk mengembangkan dan mengevaluasi aplikasi AI chatbot dalam proses pencarian pengetahuan atau knowledge retrieval pada suatu organisasi. Metodologi pengembangan aplikasi mengikuti metodologi Agile, dengan tahapan yang meliputi preliminary research, perumusan masalah, studi literatur, pengembangan aplikasi, dan evaluasi. Aplikasi dibangun menggunakan teknologi seperti Node.js, Next.js, dan PostgreSQL, serta diimplementasikan melalui platform Vercel dan GitHub. Penelitian ini menggunakan scenario- based task untuk mengevaluasi efektivitas chatbot dengan model GPT-3.5-turbo. Partisipan dibagi menjadi dua kelompok, satu menggunakan metode pencarian tanpa bantuan AI chatbot dan yang lain mendapatkan bantuan AI chatbot. Eksekusi scenario-based task pada penelitian ini dilakukan terhadap organisasi RM. Payakumbuah Cibubur dan BPOM. Selain dua organisasi tersebut, dilakukan juga uji coba untuk memvalidasi model penelitian dengan melakukan scenario-based task terhadap lingkungan Fasilkom UI. Parameter yang diukur termasuk di dalamnya akurasi informasi dan efisiensi waktu. Akurasi diukur dengan membandingkan nilai jawaban partisipan dengan bantuan AI dan tanpa bantuan AI, sementara efisiensi waktu diukur dari durasi yang diperlukan untuk menyelesaikan tugas. Analisis statistik dilakukan menggunakan Wilcoxon signed-rank test untuk efisiensi waktu dan Mann-Whitney U test untuk akurasi jawaban demi menentukan signifikansi perbedaan antara kedua kelompok. Hasil penelitian menunjukkan bahwa penggunaan AI chatbot mampu mempercepat waktu yang dibutuhkan karyawan dalam pencarian informasi organisasi. Selain itu, implementasi AI chatbot mampu menyajikan jawaban dengan akurasi yang konsisten. Kesimpulan dari penelitian ini adalah integrasi AI chatbot dalam knowledge retrieval organisasi memberikan manfaat dalam hal efisiensi dan akurasi.

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This research aims to develop and evaluate AI chatbot applications in the knowledge retrieval process in an organization. The application development methodology follows the Agile methodology, with stages including preliminary research, problem formulation, literature study, application development, and evaluation. The application was built using technologies such as Node.js, Next.js, and PostgreSQL, that implemented through the Vercel and GitHub platforms. This study used scenario-based tasks to evaluate the effectiveness of the chatbot with the GPT- 3.5-turbo model. Participants were divided into two groups, one using the search method without the help of AI chatbot and the other getting the help of AI chatbot. The execution of scenario- based tasks in this study was carried out on the RM. Payakumbuah Cibubur and BPOM. In addition to these two organizations, trials were also conducted to validate the research model by conducting scenario-based tasks on the Fasilkom UI environment. Parameters measured included information accuracy and time efficiency. Accuracy was measured by comparing the value of participants answers with and without AI assistance, while time efficiency was measured by the duration required to complete the task. Statistical analysis was conducted using Wilcoxon signed-rank test for time efficiency and Mann-Whitney U test for answer accuracy to determine the significance of the difference between the two groups. The results showed that the use of AI chatbot was able to speed up the time required for employees to search for organizational information. In addition, the implementation of AI chatbot is able to present answers with consistent accuracy. The conclusion of this research is that the integration of AI chatbot in organizational knowledge retrieval provides benefits in terms of efficiency and accuracy."

"Penelitian ini bertujuan untuk mengembangkan dan mengevaluasi aplikasi AI chatbot dalam proses pencarian pengetahuan atau knowledge retrieval pada suatu organisasi. Metodologi pengembangan aplikasi mengikuti metodologi Agile, dengan tahapan yang meliputi preliminary research, perumusan masalah, studi literatur, pengembangan aplikasi, dan evaluasi. Aplikasi dibangun menggunakan teknologi seperti Node.js, Next.js, dan PostgreSQL, serta diimplementasikan melalui platform Vercel dan GitHub. Penelitian ini menggunakan scenario- based task untuk mengevaluasi efektivitas chatbot dengan model GPT-3.5-turbo. Partisipan dibagi menjadi dua kelompok, satu menggunakan metode pencarian tanpa bantuan AI chatbot dan yang lain mendapatkan bantuan AI chatbot. Eksekusi scenario-based task pada penelitian ini dilakukan terhadap organisasi RM. Payakumbuah Cibubur dan BPOM. Selain dua organisasi tersebut, dilakukan juga uji coba untuk memvalidasi model penelitian dengan melakukan scenario-based task terhadap lingkungan Fasilkom UI. Parameter yang diukur termasuk di dalamnya akurasi informasi dan efisiensi waktu. Akurasi diukur dengan membandingkan nilai jawaban partisipan dengan bantuan AI dan tanpa bantuan AI, sementara efisiensi waktu diukur dari durasi yang diperlukan untuk menyelesaikan tugas. Analisis statistik dilakukan menggunakan Wilcoxon signed-rank test untuk efisiensi waktu dan Mann-Whitney U test untuk akurasi jawaban demi menentukan signifikansi perbedaan antara kedua kelompok. Hasil penelitian menunjukkan bahwa penggunaan AI chatbot mampu mempercepat waktu yang dibutuhkan karyawan dalam pencarian informasi organisasi. Selain itu, implementasi AI chatbot mampu menyajikan jawaban dengan akurasi yang konsisten. Kesimpulan dari penelitian ini adalah integrasi AI chatbot dalam knowledge retrieval organisasi memberikan manfaat dalam hal efisiensi dan akurasi.

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This research aims to develop and evaluate AI chatbot applications in the knowledge retrieval process in an organization. The application development methodology follows the Agile methodology, with stages including preliminary research, problem formulation, literature study, application development, and evaluation. The application was built using technologies such as Node.js, Next.js, and PostgreSQL, that implemented through the Vercel and GitHub platforms. This study used scenario-based tasks to evaluate the effectiveness of the chatbot with the GPT- 3.5-turbo model. Participants were divided into two groups, one using the search method without the help of AI chatbot and the other getting the help of AI chatbot. The execution of scenario- based tasks in this study was carried out on the RM. Payakumbuah Cibubur and BPOM. In addition to these two organizations, trials were also conducted to validate the research model by conducting scenario-based tasks on the Fasilkom UI environment. Parameters measured included information accuracy and time efficiency. Accuracy was measured by comparing the value of participants answers with and without AI assistance, while time efficiency was measured by the duration required to complete the task. Statistical analysis was conducted using Wilcoxon signed-rank test for time efficiency and Mann-Whitney U test for answer accuracy to determine the significance of the difference between the two groups. The results showed that the use of AI chatbot was able to speed up the time required for employees to search for organizational information. In addition, the implementation of AI chatbot is able to present answers with consistent accuracy. The conclusion of this research is that the integration of AI chatbot in organizational knowledge retrieval provides benefits in terms of efficiency and accuracy."

"Pada era perkembangan teknologi, chatbot berbasis AI sebagai media pencarian informasi mulai banyak diadopsi di masyarakat. ChatQurani, merupakan chatbot berbasis AI yang diwacanakan oleh LPMQ (Lajnah Pentashihan Mushaf Al-Qur’an) Kementerian Agama RI untuk menjawab pertanyaan pengguna mengenai kandungan Qur’an serta ‘Ulumul Quran lainnya. Penelitian ini bertujuan memahami kebutuhan fitur calon pengguna akan ChatQurani. Penelitian ini juga menghasilkan desain antarmuka ChatQurani melalui pendekatan user centered design (UCD). Pengumpulan kebutuhan chatbot dilakukan melalui survei serta wawancara pengguna, yang kemudian diimplementasikan menjadi 32 desain fitur. Berikutnya, rancangan desain antarmuka dievaluasi usability testing (UT), wawancara kontekstual, dan system usability scale (SUS). Hasil dari UT menyatakan mayoritas task mendapatkan success rate sebesar 100% dengan nilai terendah sebesar 80%. Selain itu, SUS menghasilkan rerata skor 71,83, menjadikan sistem dinilai memiliki usability “baik” untuk digunakan dan “dapat diterima”.

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In the era of technology, AI-based chatbots as a medium for information retrieval have begun to be widely adopted in society. ChatQurani is an AI-based chatbot envisioned by LPMQ (Lajnah Pentashihan Mushaf Al-Qur’an) of the Indonesian Ministry of Religious Affairs to answer users' questions about the contents of the Qur'an and other 'Ulumul Quran topics. This research aims to understand the needs of potential users for ChatQurani. It also produces the interface design for ChatQurani using user-centered design (UCD) as the approach. The requirements for the chatbot were gathered through a survey and user interviews, which were then implemented into 32 feature designs. The interface design was evaluated using usability testing (UT), contextual interviews, and system usability scale (SUS) questionnaire. The results from UT showed that the majority of tasks achieved a success rate of 100%, with the lowest score being 80%. Additionally, SUS resulted in an average score of 71.83, indicating that the system has a "good" usability rating and is "acceptable" for use."

"Pada era perkembangan teknologi, chatbot berbasis AI sebagai media pencarian informasi mulai banyak diadopsi di masyarakat. ChatQurani, merupakan chatbot berbasis AI yang diwacanakan oleh LPMQ (Lajnah Pentashihan Mushaf Al-Qur’an) Kementerian Agama RI untuk menjawab pertanyaan pengguna mengenai kandungan Qur’an serta ‘Ulumul Quran lainnya. Penelitian ini bertujuan memahami kebutuhan fitur calon pengguna akan ChatQurani. Penelitian ini juga menghasilkan desain antarmuka ChatQurani melalui pendekatan user centered design (UCD). Pengumpulan kebutuhan chatbot dilakukan melalui survei serta wawancara pengguna, yang kemudian diimplementasikan menjadi 32 desain fitur. Berikutnya, rancangan desain antarmuka dievaluasi usability testing (UT), wawancara kontekstual, dan system usability scale (SUS). Hasil dari UT menyatakan mayoritas task mendapatkan success rate sebesar 100% dengan nilai terendah sebesar 80%. Selain itu, SUS menghasilkan rerata skor 71,83, menjadikan sistem dinilai memiliki usability “baik” untuk digunakan dan “dapat diterima”.

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In the era of technology, AI-based chatbots as a medium for information retrieval have begun to be widely adopted in society. ChatQurani is an AI-based chatbot envisioned by LPMQ (Lajnah Pentashihan Mushaf Al-Qur’an) of the Indonesian Ministry of Religious Affairs to answer users' questions about the contents of the Qur'an and other 'Ulumul Quran topics. This research aims to understand the needs of potential users for ChatQurani. It also produces the interface design for ChatQurani using user-centered design (UCD) as the approach. The requirements for the chatbot were gathered through a survey and user interviews, which were then implemented into 32 feature designs. The interface design was evaluated using usability testing (UT), contextual interviews, and system usability scale (SUS) questionnaire. The results from UT showed that the majority of tasks achieved a success rate of 100%, with the lowest score being 80%. Additionally, SUS resulted in an average score of 71.83, indicating that the system has a "good" usability rating and is "acceptable" for use."

"Pada era perkembangan teknologi, chatbot berbasis AI sebagai media pencarian informasi mulai banyak diadopsi di masyarakat. ChatQurani, merupakan chatbot berbasis AI yang diwacanakan oleh LPMQ (Lajnah Pentashihan Mushaf Al-Qur’an) Kementerian Agama RI untuk menjawab pertanyaan pengguna mengenai kandungan Qur’an serta ‘Ulumul Quran lainnya. Penelitian ini bertujuan memahami kebutuhan fitur calon pengguna akan ChatQurani. Penelitian ini juga menghasilkan desain antarmuka ChatQurani melalui pendekatan user centered design (UCD). Pengumpulan kebutuhan chatbot dilakukan melalui survei serta wawancara pengguna, yang kemudian diimplementasikan menjadi 32 desain fitur. Berikutnya, rancangan desain antarmuka dievaluasi usability testing (UT), wawancara kontekstual, dan system usability scale (SUS). Hasil dari UT menyatakan mayoritas task mendapatkan success rate sebesar 100% dengan nilai terendah sebesar 80%. Selain itu, SUS menghasilkan rerata skor 71,83, menjadikan sistem dinilai memiliki usability “baik” untuk digunakan dan “dapat diterima”.

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In the era of technology, AI-based chatbots as a medium for information retrieval have begun to be widely adopted in society. ChatQurani is an AI-based chatbot envisioned by LPMQ (Lajnah Pentashihan Mushaf Al-Qur’an) of the Indonesian Ministry of Religious Affairs to answer users' questions about the contents of the Qur'an and other 'Ulumul Quran topics. This research aims to understand the needs of potential users for ChatQurani. It also produces the interface design for ChatQurani using user-centered design (UCD) as the approach. The requirements for the chatbot were gathered through a survey and user interviews, which were then implemented into 32 feature designs. The interface design was evaluated using usability testing (UT), contextual interviews, and system usability scale (SUS) questionnaire. The results from UT showed that the majority of tasks achieved a success rate of 100%, with the lowest score being 80%. Additionally, SUS resulted in an average score of 71.83, indicating that the system has a "good" usability rating and is "acceptable" for use."