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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) snimed Edutech: Jurnal Teknologi Pendidikan Jurnal Edik Informatika : Penelitian Bidang Komputer Sains dan Pendidikan Informatika Format : Jurnal Imiah Teknik Informatika JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal Pengabdian Masyarakat AbdiMas Jurnal Inovasi Hasil Pengabdian Masyarakat (JIPEMAS) Petir Aptisi Transactions on Management CSRID (Computer Science Research and Its Development Journal) CCIT (Creative Communication and Innovative Technology) Journal JOURNAL INFORMATICS, SCIENCE & TECHNOLOGY JISICOM (Journal of Information System, Infomatics and Computing) Journal of Information System, Applied, Management, Accounting and Research E-JURNAL JUSITI : Jurnal Sistem Informasi dan Teknologi Informasi Abdimas Universal Informatika TERANG : Jurnal Pengabdian Pada Masyarakat Menerangi Negeri ICIT (Innovative Creative and Information Technology) Journal Journal Cerita: Creative Education of Research in Information Technology and Artificial Informatics Jurnal Sistem Komputer & Kecerdasan Buatan JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Community Development Journal: Jurnal Pengabdian Masyarakat JUKI : Jurnal Komputer dan Informatika Jurnal Abdidas Jurnal Teknik Informatika (JUTIF) International Journal Of Science, Technology & Management (IJSTM) Entrepreneurship Bisnis Manajemen Akuntansi (E-BISMA) International Journal of Engineering, Science and Information Technology Jurnal Abdimas Bina Bangsa Tridharmadimas: Jurnal Pengabdian Kepada Masyarakat Jayakarta Jurnal Minfo Polgan (JMP) Formosa Journal of Science and Technology (FJST) Malcom: Indonesian Journal of Machine Learning and Computer Science Universal Raharja Community (URNITY Journal) STORAGE: Jurnal Ilmiah Teknik dan Ilmu Komputer Kohesi: Jurnal Sains dan Teknologi Journal of Informatics and Information Security International Journal of Educational Research
Diah Aryani, Diah
Prodi Teknik Informatika, Fakultas Ilmu Komputer Universitas Esa Unggul
Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Public Health Social Sciences Transportation Other

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Penguatan Kompetensi Digital Guru PKBM Maleo melalui Pelatihan Pemanfaatan Aplikasi Artificial Intelligence untuk Persiapan Pembelajaran Aryani, Diah; Asri, Jefry Sunupurwa; Asianto, Andriyanti; Akbar, Habibullah; Sutejo, Bayu Sulistiyanto Ipung; Suharti, Dwi Sloria
Abdimas Universal Vol. 8 No. 1 (2026): April
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Balikpapan (LPPM UNIBA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36277/abdimasuniversal.v8i1.2832

Abstract

The development of Artificial Intelligence (AI) technology has opened up new opportunities to improve the efficiency of the learning process, particularly in terms of how teachers can prepare teaching materials more innovatively and efficiently. However, the use of AI technology in education still faces several challenges, primarily due to teachers' limited digital literacy. The purpose of this Community Service (PKM) activity is to help PKBM Maleo teachers improve their digital competency by teaching them how to use AI applications, specifically ChatGPT, when preparing lessons. In this activity, Participatory Action Research (PAR) is the approach method used in this activity. PAR supports active partner participation in every step of the process, such as problem identification, program planning, training implementation, evaluation, and reflection. The training activity was held in January 2026 with 14 teachers participating, with the results of the activity evaluation carried out using pre-test and post-test methods to measure the level of participants' understanding of the material provided. The pre-test results showed a significant increase in participant understanding, with an average score of 97.14, while the post-test results showed an increase to 85.7% to 100%. The results of this PKM activity demonstrate that AI training with ChatGPT can help teachers improve their digital literacy skills and better prepare learning materials. It is hoped that this activity will encourage the wise and productive use of artificial intelligence technology in learning in non-formal schools.
Pelatihan dan Implementasi Sistem Verifikasi Ijazah Digital Berbasis n8n dan Filament di SMKN 1 Kabupaten Tangerang Asri, Jefry Sunupurwa; Aryani, Diah; Fannya, Puteri; Arfian, Muhamad Hadi; Widyawan, Tri Ismardiko; Ramadhan, Iksan
Abdimas Universal Vol. 8 No. 1 (2026): April
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Balikpapan (LPPM UNIBA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36277/abdimasuniversal.v8i1.2838

Abstract

This community service activity was conducted to address the problem of diploma verification at SMKN 1 Kabupaten Tangerang, which is still carried out manually, requiring considerable time and posing risks of recording errors and document loss. This activity aims to develop and implement a digital-based diploma verification system to improve efficiency, accuracy, and the quality of administrative services. The system utilizes Laravel Filament as the administrative interface, n8n for workflow automation, MySQL as the database, and Optical Character Recognition (OCR) technology to automatically extract information from diploma documents. The implementation results show a significant performance improvement, where verification time decreased by more than 90%, from 10–15 minutes to less than one minute per document. In addition, data accuracy increased from approximately 85% to 98%, and document retrieval speed improved by more than 80%. Based on user satisfaction questionnaire results, 100% of respondents stated that the system is easy to use and helps accelerate administrative tasks. Therefore, the developed system is proven to be effective in supporting the digital transformation of academic document management in the school environment.
Penerapan Random Forest dan Content-Based Filtering pada Alokasi Tenaga Kesehatan Hipertensi Jefry Sunupurwa Asri; Diah Aryani; Puteri Fannya; Ratna Dewi
Journal of Information System Research (JOSH) Vol 7 No 2 (2026): January 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v7i2.9251

Abstract

Hypertension is a major health issue in DKI Jakarta requiring efficient resource distribution to overcome inter-regional access inequalities. This research aims to design and implement a web-based decision support system (DSS) integrating Geographic Information System (GIS) to optimize health worker allocation and determine hypertension priority areas precisely. The novelty lies in integrating a Random Forest machine learning model to predict service coverage until 2030 with Content-Based Filtering (CBF). The CBF method utilizes intrinsic regional features, including service percentages, geographical locations, and prediction trends, to generate objective health worker quota recommendations. The Random Forest model was validated using 5-Fold Cross Validation with excellent performance, showing an average R² value of 0.86 and an accurate Mean Absolute Error (MAE) of 6.7%. The system is implemented using Streamlit and Folium frameworks for geographical visualization. Research results provide contributions through priority area maps, adaptive health worker quota recommendations, and Mobile Health Clinic route simulations supporting data-driven decision-making. Through this system, policymakers can perform strategic planning to improve hypertension intervention effectiveness in Jakarta. With an integrated predictive and recommendation approach, this study is expected to become a reference in the digital transformation of public health resource allocation more equitably and accurately.
Perbandingan Performa Xception dan InceptionV1 untuk Pengenalan Ekspresi Wajah Ferdinand Defin Delio; Diah Aryani; Habibullah Akbar; Mohamad Yusuf; Yaya Sudarya Triana
FORMAT Vol 15 No 1 (2026)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/format.2026.v15.i1.003

Abstract

Penelitian ini bertujuan untuk menganalisis dan membandingkan performa dua arsitektur Convolutional Neural Network (CNN) populer, yaitu Xception dan InceptionV1, dalam tugas pengenalan ekspresi wajah (Facial Expression Recognition/FER). Penelitian ini dilakukan dengan pendekatan transfer learning dan fine-tuning menggunakan dataset FER-2013 yang berisi 35.887 citra wajah grayscale berukuran 48×48 piksel yang diklasifikasikan ke dalam tujuh emosi dasar. Setiap citra diubah ukurannya menjadi 224×224 piksel, dinormalisasi, dan diproses dengan teknik augmentasi untuk meningkatkan generalisasi model terhadap variasi ekspresi wajah, pencahayaan, dan pose. Proses pelatihan dilakukan selama 30 epoch menggunakan optimizer Adam dengan learning rate 0.0001 dan batch size 64. Strategi fine-tuning dilakukan dengan membuka 30% lapisan atas model untuk mengoptimalkan bobot fitur yang telah dipelajari sebelumnya dari dataset ImageNet. Evaluasi kinerja dilakukan berdasarkan metrik akurasi, presisi, recall, F1-score, serta efisiensi komputasi yang diukur dari waktu pelatihan dan inferensi. Hasil eksperimen menunjukkan bahwa Xception mencapai akurasi validasi 70,69% dengan waktu inferensi rata-rata 20–25 ms, sedangkan InceptionV1 mencapai 65,80% dengan waktu inferensi 43–126 ms. Arsitektur Xception terbukti lebih efisien secara komputasi karena memanfaatkan depthwise separable convolution yang mengurangi jumlah parameter tanpa menurunkan akurasi. Temuan ini menunjukkan bahwa Xception lebih sesuai untuk aplikasi FER real-time dan perangkat dengan sumber daya terbatas, serta memberikan dasar yang kuat bagi penelitian lanjutan dalam pengembangan sistem pengenalan ekspresi wajah berbasis video dan lingkungan dunia nyata.
Co-Authors Adaafi'ah, Yasinta Addaafi’ah, Yasinta Ade Setiadi Adnandi, M Arba Adrian Adrian Ahmad Fathurrozi Aji Setiawan Akbar, Habibullah Andreansyah, Tedy Andriyanti Asianto Ari Asmawati Ari Pambudi Arnas, Dio Hartawan Ary Budi Warsito, Ary Budi Bashir, Pandu Bayu Sulistiyanto Ipung Sutejo Budi Tjahjono Damayanti, Prisila Delio, Ferdinand Defin Endi Rekarti, Endi Fannya, Puteri Fatonah, Nenden Siti Ferdinand Defin Delio Fifit Alfiah Fredy Susanto Gaol, Lasando Lumban H. Haris H. Haris Hani Dewi Ariessanti Harahap, Eka Purnama Haris Haris ., Haris Harlinda Syofyan Hendrian Hendrian Hendrian, Hendrian Herwanto, Agus Ichwani, Arief Ichyan Holilan Ilamsyah Ilamsyah Indri Handayani, Indri Ira Tyas Ningrum Izza Ilma Insyifani Jefry Sunupurwa Asri Jefry Sunupurwa Asri Kusmawan, Dicky Luri Sesy Apriyani Malabay Malabay Manurung, Jhordy Noverdian Mariyana Widiastuti Martino Wibowo Martono, Aris Mohamad Yusuf Mohamad Yusuf Mohammed Al-shammari, Marwan Kadhim Muhamad Yusup Muhammad Hadi Arfian Noviandi Noviandi Po Abas Sunarya Purnomo, Yunianto Putra, Syahrizal Dwi Putri, Dian Mustika Qurotul Aini Rafael Praseli Rafi Zhafar Kurnia Ramadhan, Kresna Ratna Dewi Ronald Nur Sunarto RR. Ella Evrita Hestiandari Ruli Supriati, Ruli Sabar Sukarno Sakina Nusarifa Tantri Saputra, Mochamad Adi Selvana Arma Putra Setiadi, Ade Shine Pintor Siolemba Patiro Sigit Santoso Siti Maesaroh STMIK, Author Super Sudaryono Sudaryono Sugeng Santoso Suhandi Junaedi Suharti, Dwi Sloria Supriyono, Ignatius Agus Suryana, Endang Susanto, Ratnawati Sutanto, Imam Syaadiah Arifin Syafnidawati, Syafnidawati Tiara Fanny Eldiana Ulum, M. Bahrul Ulum, Muhamad Bahrul Untung Rahardja Verdi Yasin Wahyu, Sawali Widiarso, Rafif Tri Widyawan, Tri Ismardiko Willi Kornellius Yaya Sudarya Triana Yaya Sudarya Triana Yose Amelia, Sabrina Yulhendri Yulhendri