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All Journal Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Jurnas Nasional Teknologi dan Sistem Informasi Agrokreatif Jurnal Ilmiah Pengabdian kepada Masyarakat Journal of Information Systems Engineering and Business Intelligence Proceeding of the Electrical Engineering Computer Science and Informatics Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Jurnal Informatika Universitas Pamulang PEDULI: Jurnal Imiah Pengabdian Pada Masyarakat Indonesian Journal of Electrical Engineering and Computer Science Jurnal Layanan Masyarakat (Journal of Public Service)
Purbandini Soeparman, Purbandini
Fakultas Sains Dan Teknologi Universitas Airlangga
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Environmental Science Social Sciences Other

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Alzheimer’s prediction via CNN-SVM on chatbot platform with MRI Kadafi, Muhammad Syaekar; Yaqubi, Ahmad Khalil; Purbandini, Purbandini; Astuti, Suryani Dyah
Indonesian Journal of Electrical Engineering and Computer Science Vol 36, No 1: October 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v36.i1.pp64-73

Abstract

Artificial intelligence (AI), consisting of models and algorithms capable of concluding data to produce future predictions, has revolutionary potential in various aspects of human life. One application is an Alzheimer’s disease (AD) prediction chat robot (chatbot). Only now has a method provided very accurate findings and recommendations regarding the early detection of AD using magnetic resonance imaging (MRI). Therefore, this research aims to measure AD prediction performance in four stage classes, namely very mild demented, mild demented, moderate demented, and non-demented, using brain MRI images trained in the convolutional neural network (CNN)- support vector machine (SVM) model. The research involved nine combination schemes of dataset proportions and preprocessing in the CNNSVM model. Evaluation shows that scheme 1 produces the highest accuracy, precision, recall, and F1-score, namely 98%, 99%, 98%, and 98%. The chatbot, trained using CNN, achieved 99.34% accuracy in question responses, and was then combined with AD prediction models for improved accuracy. The test results show that the chatbot functionality runs well for each transition, with a functionality score reaching 99.64 points out of 100.00. This success shows excellent potential for early detection of AD. This research brings new hope in preventing AD through AI, with potential positive impacts on human health and quality of life.
Fuzzy Type-2 Trapezoid Methods for Decision Making Salt Farmer Mapping Kustiyahningsih, Yeni; Rahmanita, Eza; Purbandini, Purbandini; Purnama, Jaka
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 7, No. 3, August 2022
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v7i3.1454

Abstract

The need for domestic salt every year has increased, both for consumption and industrial salt. Some of the fisheries service programs include providing assistance to people's businesses, providing geomembrane, and online marketing training. A large number of salt farmers and official work programs have caused the implementation of the program to be less than optimal, resulting in low salt production. This study uses a type-2 fuzzy method by integrating two methods, namely type-2 Fuzzy Analytical Hierarchy Process AHP (FAHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Fuzzy type-2 has higher accuracy than fuzzy type-1 and is more efficient and more flexible in determining the linguistic scale for criteria. The Fuzzy Analytical Hierarchy Process AHP (FAHP) interval is used to determine the weight of the salt farmer mapping criteria. Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS), used to determine. The findings of this study are that the indicators that most influence the mapping of salt farmers are land area, marketing, and market. The results of the mapping of salt farmers are the classification of salt farmer class groups and recommendations for improvement for each salt farmer. Hybrid type-2 Fuzzy Analytical Hierarchy Process AHP (FAHP) method and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), can be used for mapping salt farmers based on the consistency ratio value below 10 percent, 37 percent enter high class, 28 percent enter the middle class and 35 percent enter low class
OPTIMIZING THE USE OF ARTIFICIAL INTELLIGENCE FOR THE CREATION OF PROMOTIONAL CONTENT AND LEARNING IN THE BOARDING SCHOOL Taufik, Taufik; Effendy, Faried; Purbandini, Purbandini; Purwanti, Endah; Werdiningsih, Indah; Nuzulita, Nania; Baihaqi, Joevans Mikail; Adhipratama, Javier Ihsan; Alfath, Muhammad Fauzan; Pratama, Muhammad Fadhil Putra; Muid, Faruq Abdul; Kastur, Annita; Agustin, Dewien Nabila
Jurnal Layanan Masyarakat (Journal of Public Services) Vol. 9 No. 3 (2025): JURNAL LAYANAN MASYARAKAT
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/.v9i3.2025.372-382

Abstract

Darul Ittihad Islamic Boarding School (Pondok Pesantren Darul Ittihad), as a traditional educational institution, faces challenges in optimizing the use of information technology, particularly Artificial Intelligence (AI), for the development of promotional and instructional content. This community service program (PKM) aims to enhance the pesantren's capacity to utilize AI and digital design applications such as Canva. The activity was conducted in three phases: preparation, implementation, and evaluation. During the preparation phase, the team conducted a needs assessment survey and developed relevant training materials. The implementation phase consisted of two training sessions, focusing on the creation of AI-based promotional and educational content. Evaluation was carried out by collecting participant feedback through a questionnaire distributed via Google Forms. The evaluation results indicated a high level of participant satisfaction, with an average score of 3.24 out of 4. Additionally, 88% of participants successfully completed the independent assignments provided after the training, demonstrating a significant improvement in skills. This program concludes that the integration of AI into teaching and promotional processes at Darul Ittihad has the potential to enhance communication effectiveness, increase content relevance, and better prepare students to face the challenges of the digital era.
Implementasi Solar Shelter untuk Menunjang Sistem Energi Terbarukan yang Berkelanjutan di Pulau Gili Iyang, Kabupaten Sumenep Mubarok, Muhammad Syahril; Apsari, Retna; Uta Nugraha, Yoga; Amelia Effendi, Yutika; Jamilatul Awalin, Lilik; Purbandini, Purbandini; Sofiah, Amila; Rantini, Dwi; Fahmiyah, Indah
PEDULI: Jurnal Ilmiah Pengabdian Pada Masyarakat Vol 9 No 2 (2025): In Progres
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37303/peduli.v9i2.770

Abstract

Limitations in electricity access and reliability remains a critical challenge for small islands and remote areas in Indonesia, constraining socio-economic development and sustainable tourism growth. This community engagement program aimed to design and implement a solar shelter system to support renewable energy utilization in Gili Iyang Island, Sumenep, widely recognized as an “oxygen island” and emerging health tourism destination. The program adopted a participatory approach involving local youth organizations (Karang Taruna) and the Kelompok Sadar Wisata (Pokdarwis) through needs assessment, system design, installation, testing, and technical training. The implemented off-grid photovoltaic system consists of a 100 Wp solar panel, a 24 V 20 A solar charge controller, a 12 V 50 Ah VRLA battery, and a 1000 W pure sine wave inverter supplying 220 V AC loads. Field testing demonstrated that the system reliably powered an automatic coconut irrigation pump and multiple electronic charging devices under typical operating conditions. Beyond technical performance, the program enhanced local capacity in basic solar energy operation and maintenance while strengthening the island’s image as a sustainable ecotourism destination. The initiative directly contributes to SDG 7 (Affordable and Clean Energy) and supports long-term renewable energy adoption in small island contexts.
Co-Authors Adhipratama, Javier Ihsan Agustin, Dewien Nabila Alfath, Muhammad Fauzan Anindya Ananda Hapsari Audrey Maximillian Herli Audrey Maximillian Herli, Audrey Maximillian Awalin, Lilik Jamilatul Baihaqi, Joevans Mikail D. Kartono Dyah Erawati, Dyah Effendi, Yutika Amelia Endah Purwanti Eto Wuryanto Eva Hariyanti Eza Rahmanita Faried Effendy Halimatuz Zuhriyah Ibnu Ibadillah Indah Fahmiyah Indah Werdiningsih Indra Kharisma Raharjana Ira Puspitasari Irfan Nur Aulia Kadafi, Muhammad Syaekar Kastur, Annita Mubarok, Muhammad Syahril Muid, Faruq Abdul Nania Nuzulita Nur Ardista Pratama, Muhammad Fadhil Putra Rantini, Dwi Retna Apsari RR. Ella Evrita Hestiandari Sembiring, Rinawati Sofiah, Amila Suryani Dyah Astuti Taufik Taufik Taufik Taufik Uta Nugraha, Yoga Yaqubi, Ahmad Khalil Yeni Kustiyahningsih