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All Journal Information System for Educators and Professionals : Journal of Information System KOPERTIP: Jurnal Ilmiah Manajemen Informatika dan Komputer Jurnal Informatika dan Rekayasa Perangkat Lunak Jurnal Dinamika Informatika (JDI) J-AKSI : JURNAL AKUNTANSI DAN SISTEM INFORMASI Journal of Artificial Intelligence and Engineering Applications (JAIEA) AMMA : Jurnal Pengabdian Masyarakat INTERNAL (Information System Journal)
Edi Wahyudin
STMIK IKMI Cirebon
Humanities Automotive Engineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Nursing Social Sciences Other

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Peningkatan Literasi Keuangan Keluarga melalui Pelatihan Digital Pasca Pandemi Edi Tohidi; Edi Wahyudin; Adhivia Julian; Aditya Fauzi Samsuri
AMMA : Jurnal Pengabdian Masyarakat Vol. 1 No. 03 (2022): AMMA : Jurnal Pengabdian Masyarakat
Publisher : CV. Multi Kreasi Media

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Abstract

The COVID-19 pandemic has had a significant impact on household economic stability in Indonesia. Many families have experienced a decrease in income, changes in consumption patterns, and limited access to formal financial services. In the post-pandemic period, the economic challenges faced by households have become increasingly complex, thus requiring enhanced literacy and skills in financial management, particularly those based on digital tools. This Community Service Program (PKM) aims to provide training in digital-based household financial management to communities in the partner area, in order to improve their ability to manage income, expenses, savings, and the wise use of digital financial applications. The implementation method includes an initial survey to assess participants' financial literacy levels, preparation of training modules, face to-face and online training sessions, as well as evaluation of participants’ improvement in knowledge and skills. The training materials cover topics such as household financial planning, debt and savings management, the use of digital wallets, financial recording applications, and basic understanding of micro-investments. The results of the program indicate that the training successfully increased participants’ understanding of basic financial concepts and improved their ability to use digital financial tracking applications. Participants also became more skilled in preparing family budgets, monitoring daily expenses, and identifying priority needs. Other positive outcomes include heightened awareness of the importance of saving and managing financial risk. This activity provides tangible contributions to fostering economic self-reliance among families in the digital era. Going forward, similar training programs are expected to be developed as sustainable initiatives, particularly for lower-middle income communities that are more vulnerable to economic shocks.
Pemanfaatan Aplikasi Akuntansi Sederhana dalam Meningkatkan Transparansi Keuangan Koperasi Desa Edi Wahyudin; Fathurrohman; Agnes Rosmeri Manurung; Akdan Amrullah
AMMA : Jurnal Pengabdian Masyarakat Vol. 1 No. 03 (2022): AMMA : Jurnal Pengabdian Masyarakat
Publisher : CV. Multi Kreasi Media

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Abstract

This Community Partnership Program aims to improve financial transparency and accountability in village cooperatives through the utilization of a simple accounting application. Activities include training on application usage, assistance in recording financial transactions, and evaluation of system implementation. It is expected that with this application, the financial management of cooperatives will become more structured, easily understandable, and accessible to members, thereby increasing trust and participation in cooperative activities.
OPTIMASI KLASTERISASI PENERIMAAN PAJAK BUMI DAN BANGUNAN MENGGUNAKAN ALGORITMA K-MEDOIDS Febri Abdi Annur Dhuha; Ade Irma Purnamasari; Denni Pratama; Edi Tohidi; Edi Wahyudin
JURNAL AKUNTANSI DAN SISTEM INFORMASI Vol 7 No 1 (2026): Edisi Februari 2026
Publisher : Program Studi Akuntansi Fakultas Ekonomika dan Bisnis Universitas Majalengka

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31949/j-aksi.v7i1.16659

Abstract

Pajak Bumi dan Bangunan (PBB) merupakan komponen strategis dalam Pendapatan Asli Daerah (PAD) yang berperan penting dalam mendukung penyelenggaraan pembangunan dan pelayanan publik. Namun, heterogenitas data dan variasi karakteristik objek pajak menyebabkan pemerintah daerah mengalami kesulitan dalam memetakan potensi fiskal dan tingkat kepatuhan wajib pajak secara akurat. Penelitian ini bertujuan menganalisis efektivitas algoritma K-Medoids dalam mengelompokkan wajib pajak di Kecamatan Tanjung berdasarkan atribut numerik, yaitu luas tanah, luas bangunan, NJOP tanah, NJOP bangunan, dan nilai PBB tahun berjalan. Metode penelitian meliputi tahapan pengumpulan data, pra-pemrosesan, transformasi logaritmik, normalisasi, implementasi algoritma K-Medoids, serta evaluasi hasil klaster menggunakan metrik Silhouette Coefficient dan Davies–Bouldin Index. Proses komputasi dilakukan menggunakan Python dengan pustaka pyClustering dan scikit-learn. Hasil penelitian menunjukkan terbentuknya empat klaster wajib pajak dengan karakteristik berbeda: klaster aset besar berkontribusi rendah, klaster premium berkontribusi tinggi, klaster ekonomi rendah dengan pola pembayaran tidak stabil, dan klaster ekonomi menengah dengan kepatuhan cukup baik. Evaluasi kualitas model menghasilkan Silhouette Coefficient sebesar 0,4204 dan Davies–Bouldin Index sebesar 0,7893, yang menunjukkan struktur klaster cukup baik dan stabil. Temuan ini memberikan kontribusi empiris dalam mendukung optimalisasi pengelolaan PBB berbasis analitik, serta dapat digunakan sebagai dasar penyusunan strategi penagihan berbasis prioritas dan formulasi kebijakan fiskal yang lebih tepat sasaran.
PENINGKATAN KLASIFIKASI PENJUALAN PRODUK FASHION DI SABHIRA OFFICIAL DENGAN RANDOM FOREST Nazwa Arraudhah; Ade Irma Purnama Sari; Agus Bahtiar; Edi Wahyudin
Jurnal Dinamika Informatika Vol. 14 No. 1 (2025): Jurnal Dinamika Informatika Volume 14 Nomor 1
Publisher : Program Studi Informatika Universitas PGRI Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31316/jdi.v14i1.512

Abstract

Penelitian ini berfokus pada peningkatan akurasi model klasifikasi penjualan produk fashion di Toko Sabhira Official dengan menerapkan algoritma Random Forest. Pendekatan yang digunakan mengikuti tahapan Knowledge Discovery in Database (KDD), yang mencakup pemilihan data, prapemrosesan, transformasi, data mining, dan evaluasi. Data penelitian terdiri dari 1.559 transaksi dalam periode Agustus hingga Oktober 2023, dengan atribut seperti kategori produk, jumlah barang terjual, harga, serta kategori penjualan (rendah, sedang, tinggi). Model dikembangkan menggunakan perangkat lunak RapidMiner, dengan pembagian data sebesar 70% untuk pelatihan dan 30% untuk pengujian. Hasil analisis menunjukkan bahwa algoritma Random Forest mampu mencapai tingkat akurasi sebesar 99,81%, dengan precision untuk kategori “Tinggi” mencapai 100%, sementara kategori lainnya memiliki nilai di atas 99%. Evaluasi menggunakan confusion matrix menunjukkan tingkat kesalahan prediksi yang sangat rendah, sehingga model ini dapat mengklasifikasikan tingkat penjualan secara lebih akurat. Hasil penelitian ini memberikan wawasan yang berguna bagi Toko Sabhira Official dalam pengelolaan stok serta strategi promosi berbasis data.
Optimization of Convolutional Neural Networks Using Resizing Techniques for Banana Leaf Disease Classification Aldiyansyah Kurniawan; Ade Irma Purnamasari; Denni Pratama; Edi Tohidi; Edi Wahyudin
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 5 No. 2 (2026): February 2026
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v5i2.1876

Abstract

Early and accurate identification of banana leaf diseases is essential for supporting digital agriculture, as visual symptoms often require rapid and reliable analysis. This study investigates the impact of three image resizing techniques squashing, letterboxing, and random resized crop on the performance of the MobileNetV2 architecture in classifying four categories of banana leaf images using the Banana Leaf Disease Dataset v4 consisting of 4,675 samples. The experiments were conducted using a transfer learning approach with an 80:10:10 data split, standardized normalization, and data augmentation. The results show that all resizing techniques achieved test accuracies above 92%. Squashing produced the highest accuracy and fastest training time, letterboxing demonstrated the most stable performance with the lowest validation loss, and random resized crop improved generalization to variations in object position. These findings confirm that resizing strategies significantly influence the stability and effectiveness of CNN models. Overall, MobileNetV2 proves capable of delivering accurate and efficient classification of banana leaf diseases when supported by an appropriate preprocessing pipeline. This study provides empirical evidence for developing image-based plant disease diagnosis systems within smart agriculture.
Penguatan Digital Marketing Berbasis Artificial Intelligence Bagi Produk Lokal UMKM Fatihanursari Dikananda; Edi Wahyudin; Odi Nurdiawan; Rudi Kurniawan
AMMA : Jurnal Pengabdian Masyarakat Vol. 4 No. 5 : Juni (2025): AMMA : Jurnal Pengabdian Masyarakat
Publisher : CV. Multi Kreasi Media

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Abstract

Micro, Small, and Medium Enterprises (MSMEs) play a significant role in regional economic development but continue to face challenges in implementing digital marketing strategies. This community service program aimed to improve MSMEs' capabilities through mentoring on Artificial Intelligence (AI)-based digital marketing for five MSMEs in Cirebon City. The implementation included needs assessment, digital marketing training, AI utilization workshops, implementation assistance, and monitoring and evaluation. The results demonstrated improvements in social media management, content planning, AI-assisted copywriting, and digital promotional activities. The program enhanced participants' digital competencies and supported sustainable improvements in the competitiveness of local products.
Co-Authors Ade Irma Purnama Sari Ade Irma Purnamasari Adhivia Julian Aditya Fauzi Samsuri Agnes Rosmeri Manurung Akdan Amrullah Akhmad Roziq Aldiyansyah Kurniawan Arif Rinaldi Dikananda Auldi Dwi Cahyani Kusumawardani Azizah Nuraini Hardadi Denni Pratama Edi Tohidi Fathurrohman Fatihanursari Dikananda Febri Abdi Annur Dhuha Garzitta Aditya Fahreza Haidar Fakhri Hegarmanah Muhabatin Iin Irfan Ali Kaslani Muhamad Agastya Muhamad Yoni Ardiansah Muhammad Aji Pratama Muhammad Zamil Farhan Mulyawan Nazwa Arraudhah Nazwa Putri Nindya Nining Rahaningsih Nurilah Odi Nurdiawan Rachmat Trikar Sohadi Raja Al-Fath Hidayat Rudi Kurniawan Shalsa Fadillah Rahmadenta Shifa Dwi Oktaviani Siskawati Siti Aisyah Tiar Imam Muarif Tio Prasetya Tuti Hartati Umi Hayati Yudhistira Arie Wijaya Yuniar Kartika