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All Journal ComEngApp : Computer Engineering and Applications Journal CAUCHY: Jurnal Matematika Murni dan Aplikasi Journal of Educational, Health and Community Psychology Jurnal Psikologi Terapan dan Pendidikan Science and Technology Indonesia Format : Jurnal Imiah Teknik Informatika Jurnal Penelitian Sains AKSIOLOGIYA : Jurnal Pengabdian Kepada Masyarakat BAREKENG: Jurnal Ilmu Matematika dan Terapan PROCESSOR Jurnal Ilmiah Sistem Informasi, Teknologi Informasi dan Sistem Komputer KACANEGARA Jurnal Pengabdian pada Masyarakat JURNAL PENDIDIKAN TAMBUSAI Journal of Electronics, Electromedical Engineering, and Medical Informatics Jurnal AbdiMas Nusa Mandiri JAGROS : Jurnal Agroteknologi dan Sains (Journal of Agrotechnology Science) Kontribusi: Jurnal Penelitian dan Pengabdian Kepada Masyarakat Electrician : Jurnal Rekayasa dan Teknologi Elektro COREAI: Jurnal Kecerdasan Buatan, Komputasi dan Teknologi Informasi Jurnal INFOTEL Vokasi UNESA Bulletin of Engineering, Technology and Applied Science
Bambang Suprihatin
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Pembelajaran Ensemble Voting Tertimbang dari Arsitektur CNN untuk Klasifikasi Retinopati Diabetik Desiani, Anita; Primartha, Rifkie; Hanum, Herlina; Dewi, Siti Rusdiana Puspa; Suprihatin, Bambang; Al-Filambany, Muhammad Gibran; Suedarmin, Muhammad
JURNAL INFOTEL Vol 16 No 1 (2024): February 2024
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v16i1.999

Abstract

Diabetic Retinopathy (DR) is a diabetes disease that attacks the retina of the eye and can be recognized through retinal images. The process of assisting retinal images can be done by applying deep learning-based methods, one of which is the Convolutional Neural Network (CNN). CNN has many architectures that can perform image classification processes, namely ResNet-50, MobileNet, and EfficientNet. Weaknesses of each architecture can be overcome through ensemble learning methods that can add up the performance results of each classification method. The study applies the ensemble learning method to improve the performance of the ResNet-50, MobileNet, and EfficientNet architectures in paying for DR disease on the retina by weighted voting. The data used are the APTOS and EyePACS datasets. The method in this research is data collection, training, testing, and evaluation of each architecture and ensemble learning. The results of the superior ensemble learning performance in the value of accuracy, F1-Score, and Cohens Kappa were obtained respectively 93.3%, 93.42%, and 0.866. The best specificity value was obtained by Resnet-50 at 99.78% and the highest sensitivity value was obtained by EfficientNet at 96.2%. Based on the classification results of each architectural and ensemble learning, it can be interpreted that the proposed ensemble learning method is excellent to perform image classification for Diabetic Retinopathy.
Pemanfaatan Limbah Kain Songket Desa Limbang sebagai Produk Bernilai Ekonomi Suprihatin, Bambang; Maiyanti, Sri Indra; Primartha, Rifkie; Amran, Ali; Desiani, Anita; Sari, Puspa
Aksiologiya: Jurnal Pengabdian Kepada Masyarakat Vol 9 No 4 (2025): November
Publisher : Universitas Muhammadiyah Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30651/aks.v9i4.26346

Abstract

Desa Limbang Jaya merupakan desa pengerajin kain songket di Sumatera Selatan. Mayoritas perempuan di desa ini bekerja sebagai pengerajin songket. Seorang pengerajin di Desa Limbang Jaya dapat menenun 3 hingga 4 helai kain berukuran 50-80 cm setiap bulannya. Setiap kain melalui proses pemotongan yang menyisakan berupa potongan kecil kain. Limbah songket biasanya dibuang atau dibakar, padahal limbah ini dapat diolah menjadi produk kerajinan yang memiliki nilai jual dengan menggunakan teknik menjahit seperti patchwork dan quilting. Kegiatan yang dilakukan berupa pelatihan dalam pengolahan limbah kain songket dengan menerapkan teknik patchwork dan quilting untuk menghasilkan produk dengan nilai jual. Kegiatan ini ditujukan pada penduduk perempuan khususnya pengrajin songket untuk meningkatkan keterampilan dalam mengolah limbah kain songket. Kegiatan pengolahan limbah sampah di desa Limbang Jaya belum pernah dilakukan. Tahapan kegiatan ini terdiri dari observasi, persiapan kegiatan, penyampaian materi, pelatihan, pendampingan, dan evaluasi. Kegiatan ini berhasil meningkatkan secara signifikan pemahaman dan keterampilan praktis peserta, yang diindikasikan oleh kenaikan nilai rata-rata post-test sebesar 38% dan dihasilkannya produk prototipe yang memiliki nilai jual. Hal ini mengindikasikan peningkatan pemahaman dan keterampilan peserta dalam pengolahan limbah kain songket dengan menerapkan teknik patchwork dan quilting yang menandakan keberhasilan dari kegiatan ini. Kegiatan ini dapat mendorong pembentukan usaha kreatif berbasis limbang songet yang dapat meningkatkan perekonomian masyarakat di Desa Limbang Jaya dalam jangka panjang.
Perbandingan Algoritma CART Dan AdaBoost Pada Klasifikasi Demensia All Fajri, Muhammad Arya; Saputra, M Aldi; Desiani, Anita; Suprihatin, Bambang; Hanum, Herlina
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.i1.002

Abstract

Demensia merupakan gangguan kesehatan ditandai dengan penurunan daya ingat, kemampuan kognitif, dan perilaku yang mengganggu aktivitas pada kehidupan sehari-hari. Masyarakat kurang mendapatkan informasi mengenai deteksi dini demensia yang disebabkan terbatasnya fasilitas kesehatan. Klasifikasi menggunakan data mining dapat membantu deteksi dini demensia. Penelitian ini bertujuan membandingkan algoritma CART dan AdaBoost untuk melihat metode yang paling efektif digunakan pada klasifikasi demensia. Pembagian data dilakukan menggunakan metode percentage split dan k-fold cross-validation. Percentage split membagi data menjadi dua bagian dengan 70% data pelatihan dan 30% data pengujian. K-fold cross-validation mengelompokkan data dengan 1 kelompok data menjadi data pengujian dan 9 kelompok data lainnya menjadi data pengujian yang dilakukan berulang pada setiap kelompok data sebanyak 10 kali. ADASYN digunakan untuk menyeimbangkan data pada setiap kelas. Hasil evaluasi kinerja pada kedua algoritma menunjukkan AdaBoost menggunakan ADASYN dan k-fold cross-validation memiliki nilai tertinggi untuk akurasi, presisi, recall, f1-score, dan ROC-AUC masing-masing sebesar 92.52%, 92.11%, 92.52%, 91.46%, dan 96.85%. Hasil ini menunjukkan bahwa algoritma AdaBoost sangat baik dalam memprediksi seluruh demensia dengan benar, mempertahankan keseimbangan antara presisi dan recall, dan membedakan tiga kelas demensia. Hasil penelitian menunjukkan keunggulan pendekatan ensemble learning dalam menangani variasi data dan meningkatkan stabilitas model klasifikasi demensia. Penelitian ini menunjukkan bahwa AdaBoost memiliki performa yang sangat baik dibandingkan CART pada klasifikasi demensia.
PENINGKATAN SKILL SISWA TUNARUNGU MELALUI PELATIHAN PATCHWORK DAN QUILTING BERBASIS APLIKASI SIGN TALK DI SLB-B YPAC PALEMBANG Desiani, Anita; Suprihatin, Bambang; Amran, Ali; Oktariansyah, Yadi; Dewi, Siti Rusdiana Puspa; Jonatan, Jonatan; Prayogo, Slamet; Sinabutar, Lonamonika
Jurnal AbdiMas Nusa Mandiri Vol. 8 No. 2 (2026): Periode April 2026
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/abdimas.v8i2.7965

Abstract

Skill development for deaf students at SLB-B YPAC Palembang still faces significant challenges, particularly due to communication barriers between teachers and students that hinder knowledge transfer. This community service program aims to enhance hard skills (technical sewing skills in patchwork and quilting) as well as soft skills (communication, teamwork, and independence) through the integration of an Artificial Intelligence (AI)-based application called Sign Talk. The implementation method was carried out through a workshop and intensive mentoring scheme over 4 months, which included 3 main training sessions, each lasting 120 minutes, for 15 deaf students. Evaluation was conducted using pre-test and post-test instruments analyzed descriptively. The results of the activity showed an increase in students’ soft skills of 40.5%. For hard skills, specifically sewing competencies, there was a 23.31% increase. Although 90% of participants rated the Sign Talk application as very helpful in understanding instructions during the activity, further development of the Sign Talk vocabulary is needed. Additionally, this activity can be expanded to include other hard skill trainings with Sign Talk serving as the communication medium.
Application of Greedy Algorithm and Simulated Annealing Algorithm on the Asymmetric Capacitated Vehicle Routing Problem Model in Designing Optimal Garbage Transportation Routes Arisha, Bella; Puspita, Fitri Maya; Suprihatin, Bambang; Indrawati
Vokasi UNESA Bulletin of Engineering, Technology and Applied Science Vol. 3 No. 2 (2026): (In Progress)
Publisher : Universitas Negeri Surabaya or The State University of Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/vubeta.v3i2.45644

Abstract

Waste management remains a recurring issue, particularly in large urban areas. An optimal waste collection route is essential to prevent the problem from becoming more severe and persistent. This study aims to determine the minimum distance and route for waste collection in the Seberang Ulu 1 District, Palembang, using the Greedy and Simulated Annealing algorithms. The calculations were carried out by dividing the district into four work zones. The results show that, using the Greedy algorithm, the minimum distances and routes for work zones 1 through 4 were 24.655 km, 29.7 km, 22.7 km, and 24.705 km, respectively. Meanwhile, using the Simulated Annealing algorithm, the minimum distances and routes for each work zone were 24.325 km, 32.45 km, 22.5 km, and 22.385 km. On average, SA reduces the total distance traveled by 2.1% compared to Greedy, but it requires a longer computation time due to its iterative process of finding the global optimum. These indicate that both algorithms are equally effective in solving the ACVRP problem, with different advantages. SA's advantage in optimizing more complex routes and Greedy's advantage in computation speed for practical implementation. These findings indicate that the Simulated Annealing Algorithm and the Greedy Algorithm almost the same results in solving the Asymmetric Capacitated Vehicle Routing Problem in Seberang Ulu 1 District, Palembang.
Co-Authors Agatha, Lucy Chania Agus Supriyanto Al-Filambany, Muhammad Gibran Ali Amran All Fajri, Muhammad Arya Anita Desiani Armalia, Divasanda Ayuputri, Niken Bella Arisha, Bella Cahyani, Kariah Ayu Dwifa, Dima Efriliyanti, Filda Eka Susanti Ekawati, Jihan Intan Endro Setyo Cahyono, Endro Setyo Ermatita - Evi Yuliza, Evi Fadilah, Nadiyah Fitri Maya Puspita Geovani, Dite Herlina Hanum, Herlina Indra Maiyanti, Sri Indrawati Indrawati Indrawati Irmeilyana Jonatan, Jonatan Kurniawan, Rifki Marselina, Nyanyu Chika Mulawarman Mulawarman Mutiara, Siti Rahma Ngudiantoro . Ning Eliyati Novi Rustiana Dewi NUNI GOFAR Nurlita Hendiani Permata, Anggun Pranata, Teddi Prayogo, Slamet Puspa Sari, Puspa Putra Bahtera Jaya Bangun, Putra Bahtera Jaya Putra BJ Bangun, Putra BJ Putri Pratiwi Ramayanti, Indri Rayani, Ira Rifkie Primartha Rio Halim, Muhammat Rufi'i Salamah, Fitri Salsabila, Aulia Saputra, M Aldi Sarjani, Ita Sigit Priyanta Sinabutar, Lonamonika Sisca Octarina Siti Rusdiana Puspa Dewi Sri Indra Maiyanti Suedarmin, Muhammad Suratama, Bintang Yadi Oktariansyah Yanita, Nurul Fadhila