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Nurvelly Rosanti, Nurvelly
Universitas Muhammadiyah Jakarta
Agriculture, Biological Sciences & Forestry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Engineering Environmental Science Languange, Linguistic, Communication & Media Library & Information Science Mathematics Social Sciences Other

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Utilization of Machine Learning for Property Price Segmentation and Prediction Andriansyah, Akbar; Dzulkarnain, Mulki Djenfik; Afkarinah, Afni Izzah; Amili, Fadel; Ramadhika, Gilang; rosanti, Nurvelly; Ambo, Siti Nurbaya; Andharani, Yana; Sutrisno, Mirza
Society : Jurnal Pengabdian Masyarakat Vol. 4 No. 2 (2025): Maret
Publisher : Edumedia Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55824/jpm.v4i2.537

Abstract

Advances in digital technology have encouraged the utilization of artificial intelligence, especially machine learning, in various sectors, including property price analysis. However, there are still many people who do not understand the basic concepts of this technology, so structured and applicable education is needed. To answer this challenge, an activity entitled “Utilization of Machine Learning for Property Price Segmentation and Prediction” was held which aimed to introduce and train participants in the application of machine learning to predict property prices. This activity consists of two main parts, namely webinars and workshops. The webinar focused on introducing the concepts of artificial intelligence, machine learning, and AI Project Cycle as the main method in analyzing house prices. Meanwhile, the workshop provided hands-on training to participants in building prediction models using Google Colab. This activity was carried out through a series of stages, starting from socialization, preparation of materials, pre-test to measure initial understanding, educational and practical sessions, to evaluation through post-test and filling in participant feedback. A total of 39 participants from various backgrounds participated in this activity. The evaluation showed that 38.7% of participants were satisfied, while 51.6% were very satisfied with the program. In addition, the post-test results showed a significant increase in understanding compared to the pre-test results. Based on these results, this activity proved to be successful in providing new insights into the application of machine learning in property price prediction and equipping participants with practical skills that can be applied in the real world.
Educating on the Application of Tensorflow in Artificial Intelligence, Machine Learning and Deep Learning Santoso, Ilham Budi; Aji, Irfan Pandu; Franskusuma, Sutio; Putri, Khansa Aqila; Ardharani, Yana; Mujiastuti, Rully; Nurbaya Ambo, Sitti; Meilina, Popy; Rosanti, Nurvelly; Amri, Nurul
Society : Jurnal Pengabdian Masyarakat Vol. 4 No. 2 (2025): Maret
Publisher : Edumedia Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55824/jpm.v4i2.547

Abstract

In addition to bringing positive impacts, technological developments also provide new challenges in improving people's technological literacy, especially related to Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL). One of the main challenges is the low public understanding of these technologies, which are increasingly relevant in the era of digital transformation. On the other hand, Google developed a library with the name TensorFlow which is widely used for data processing in Artificial Intelligence, Machine Learning, and Deep Learning. Based on this, educational activities were carried out in the form of introducing and training the use of TensorFlow to the general public in the form of webinars and workshops with the theme ‘Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning’. The activity was carried out in two stages, namely webinars for delivering basic material and workshops for hands-on practice. Based on evaluation through a Likert scale questionnaire, the majority of participants stated that they were very satisfied with the quality of the material, presenters, and implementation of activities. The post-test results also showed an increase in participants' understanding of the material, as evidenced by correct answers on topics such as TensorFlow functions, supervised learning, and neural networks. The participation of 52 participants from various institutions shows the success of this activity in achieving its goals.  
Chatbots Made Easy: A Practical Workshop on Generative AI Aullia, Mochammad Rizqi; Fadillah, Muhammad Daffa; Umam, Khoirul; Septiana, Dimas; Rahmawati Gunawan, Alfiana; Nurbaya Ambo, Sitti; Rosanti, Nurvelly; Ardhani, Yana; Jumail, Jumail
Society : Jurnal Pengabdian Masyarakat Vol. 4 No. 3 (2025): Mei
Publisher : Edumedia Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55824/jpm.v4i3.548

Abstract

Chatbots powered by Generative AI have become a rapidly evolving technological innovation, enabling users to interact with AI-based systems in a more natural way. However, the implementation of these chatbots still faces many challenges, especially for beginners who lack a deep technical background. This study aims to develop a more accessible and understandable approach for those new to Generative AI. Through webinars and workshops, participants were introduced to the fundamentals of language models, the use of tools such as Google Colab, as well as various challenges and opportunities in AI chatbot development. Some of the main obstacles encountered included complex materials, limited access to data and computational resources, and varying levels of understanding among participants. Nevertheless, these activities provided beginners with the opportunity to grasp the basics of Generative AI and even develop their own chatbots. With a more practical and inclusive approach, this study contributes to introducing Generative AI-based chatbot technology to a broader audience. Evaluation results showed positive feedback from 77 participants from diverse backgrounds, with 51.9% stating they were very satisfied, 37.7% satisfied, and 10.4% neutral. Additionally, Pre-Test and Post-Test results indicated an improvement in participants' understanding of building simple chatbots. This initiative successfully provided a strong foundation for beginners to enter the field of Artificial Intelligence, particularly Generative AI
Python and Data Science: Building a Foundation with Practical Projects Abduzzhohir, Yasir; Saleh, Muhammad Raihan; Sunatun, Sunatun; Saputra, Agita Irvanda; Wahyudi, Ramzy Al Firza; Hendra, Hendra; Mujiastuti, Rully; Sutrisno, Mirza; Jumail, Jumail; Rosanti, Nurvelly
Society : Jurnal Pengabdian Masyarakat Vol. 4 No. 3 (2025): Mei
Publisher : Edumedia Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55824/jpm.v4i3.551

Abstract

In today's digital era, data has a crucial role in decision making. To increase public understanding, especially students, about Data Science, a webinar and online workshop titled “Python and Data Science: Building a Foundation with Practical Projects” through the Zoom Meeting Conference platform. This activity aims to provide a basic understanding of the concepts, benefits, and applications of Data Science in various industrial fields. Participants are invited to learn the use of Python in data analysis, and are given case study projects related to sales data analysis to apply the knowledge they have gained. This webinar and workshop activity was held on January 23, 2025, at 09.00 WIB which was attended by 40 participants from various institutions. The evaluation results show that participants expressed their satisfaction as indicated by the percentage of positive values in the feedback of 40% satisfied and 37% very satisfied with this activity.  In addition, there was an increase in participants' understanding of Data Science, with the Pre-Test average score increasing from 7.87% to 8.21% on the Post-Test.
Co-Authors Abduzzhohir, Yasir Abean, Mohammad Arief Abyan Shidqi, Muhammad Adharani, Yana Afkarinah, Afni Izzah Aji, Irfan Pandu Alfarizi, Muhammad Azis Alifsyah Ramadhan, Rafi Novranza Alriyanto, Abri Okta Ambiyah, Muhammad Chairil Ambo, Siti Nurbaya Amili, Fadel Amri, Nurul Andharani, Yana Andriansyah, Akbar Anjani, Meisya Putri Ardhani, Yana Ardharani, Yana Arista Putri, Syahda Asti Ayuningtyas, Asti Asyahri, Aldo Dwi Aullia, Mochammad Rizqi Azizah, Faza Shafa Bintang, Reihan Aditya Permata Budiarto, Khamdan Cholis Arethusa, Muhammad Daulay, Azhari Dewi Risanty, Rita Dzulkarnain, Mulki Djenfik Erwin Setiawan, Erwin Fadhlurokhman, Rafi Fadillah, Muhammad Daffa Fajri, Muhammad Akbar Al Fajri, Muhammad Ihsan Fakhul Jannah, Elsa Ananda Hanifah Faridzi, Salman Al Faza Shafa Azizah Filayati, Muhammad Albi Akbar Fizar, Bintang Al FJ, Elsa Ananda Hanjfah Franskusuma, Sutio Ghifari, Sandhi Alfianda Guritno, Deden Habibi, Yusuf Haryanda, Muhammad Haykal Andana, Muhammad Hendra Hendra Hidayat, Ragil Irawan, Doni Jumail, Jumail Khoirrosyid, Haida Khoirul Umam Lestari, Fina Dwi Mahmuda, Faiz Marhani Maududi, Izzuddin Al Qossam Maulana Saputra, Reza Ade Maulana, Mirza MUHAMMAD HASBI Muhammad, Hilbram Mukti, Hari Mustafa, Faizal Nindya Putri, Azzahra Novranza, Rafi Nurbaya Ambo, Sitti Popy Meilina Prayogo, Ikhsan Adi Putri, Khansa Aqila Putri, Syahda Arista Rabbani, Syamil Ghufron Rahmawati Gunawan, Alfiana Ramadhika, Gilang Retnani Latifah, Retnani Risanty, Rita Dewi Rizky Aditya, Fauzan Rizky Maulana, Rizky Rully Mujiastuti S, Muhamad Thirafi Qaedi Sabhan, Rifqi Baihaqi Saleh, Muhammad Raihan Saleh, Oldi Alfani Sunan Santoso, Ilham Budi Saputra, Agita Irvanda Saputra, Ambar Dwi Septiana, Dimas Sherli Fadilah, Ridha Shidqi, Muhammad Abyan Sirojul Munir Sitti Nurbaya Sunatun, Sunatun Sutrisno, Mirza Taufik Hidayat Vivria, Muhammad Efendi Wahyudi, Ramzy Al Firza Winnugroho Wiratman, Manfaluthy Hakim, Tiara Aninditha, Aru W. Sudoyo, Joedo Prihartono Zahro, Rahmita