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All Journal Djtechno: Jurnal Teknologi Informasi Jurnal Pengabdian Masyarakat Nusantara Jurnal Suara Pengabdian 45 Journal of Artificial Intelligence and Digital Business
Ryan Arya Pramudya, Ryan Arya
Universitas Negeri Semarang
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Social Sciences

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Program Pelatihan Kewirausahaan Digital di Desa Blerong Kabupaten Demak Yuniarti, Nur Atika; Pramudya, Ryan Arya
Jurnal Pengabdian Masyarakat Nusantara (JPMN) Vol. 4 No. 1 (2024): Februari-Juli 2024
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jpmn.v4i1.2702

Abstract

The community service program is a digital entrepreneurship training program held in Blerong Village. The aim is to increase the ability of MSME players to entrepreneurs using technology, both in collaborating and marketing products. This activity includes knowledge transfer and entrepreneurship training, which takes place at the Computer Laboratory of the Faculty of Economics and Business, University of 17 August 1945 Semarang. This program will be implemented on April 28, 2024, followed by continuous coaching. This training involves resource persons from business practitioners and economic academics. The method used is an educational and participatory approach, which has proven effective in improving the digital skills of MSME owners. The ultimate goal is to help MSMEs achieve business success and increase income through increasing digital entrepreneurial agility.
Program Pelatihan Kewirausahaan Digital di Desa Blerong Kabupaten Demak Yuniarti, Nur Atika; Pramudya, Ryan Arya
Jurnal Pengabdian Masyarakat Nusantara (JPMN) Vol. 4 No. 1 (2024): Februari-Juli 2024
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jpmn.v4i1.2702

Abstract

The community service program is a digital entrepreneurship training program held in Blerong Village. The aim is to increase the ability of MSME players to entrepreneurs using technology, both in collaborating and marketing products. This activity includes knowledge transfer and entrepreneurship training, which takes place at the Computer Laboratory of the Faculty of Economics and Business, University of 17 August 1945 Semarang. This program will be implemented on April 28, 2024, followed by continuous coaching. This training involves resource persons from business practitioners and economic academics. The method used is an educational and participatory approach, which has proven effective in improving the digital skills of MSME owners. The ultimate goal is to help MSMEs achieve business success and increase income through increasing digital entrepreneurial agility.
Transformasi Budidaya Jamur Menjadi Usaha Mandiri: Pemberdayaan Masyarakat Desa melalui Penguatan Manajemen Bisnis Yuniarti, Nur Atika; Pramudya, Ryan Arya; Mutiarachim, Atika
Jurnal Suara Pengabdian 45 Vol. 4 No. 2 (2025): Juni: Jurnal Suara Pengabdian 45
Publisher : LPPM Universitas 17 Agustus 1945 Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56444/0yqyq425

Abstract

Program pengabdian masyarakat melalui penguatan manajemen bisnis telah dilaksanakan di Desa Manggarmas, Kecamatan Godong, Kabupaten Grobogan pada 25 Mei 2025. Program ini bertujuan meningkatkan kapasitas manajerial petani jamur melalui pelatihan manajemen usaha dan strategi pemasaran digital. Permasalahan utama yang dihadapi meliputi pencatatan keuangan yang belum optimal, ketiadaan standar pengemasan produk, dan minimnya pemanfaatan media digital untuk pemasaran. Kegiatan pelatihan menggunakan pendekatan edukatif dan partisipatif, mencakup distribusi hasil panen, teknik pengemasan, dan pemasaran digital. Hasil evaluasi menunjukkan peningkatan signifikan: manajemen usaha sederhana naik 75%, penguasaan teknik pengemasan meningkat 80%, dan penggunaan media digital untuk pemasaran bertambah 70%. Dampak positif terlihat dari munculnya pembeli dari luar desa setelah petani mengunggah produk ke media sosial, mendorong terwujudnya wirausahawan mandiri yang mampu mengembangkan usaha dan meningkatkan pendapatan.
HYBRID DEEP LEARNING RANDOM FOREST OPTIMASI PEMILIHAN FITUR UNTUK PREDIKSI CHURN INDUSTRI TELEKOMUNIKASI Mutiarachim, Atika; Marutho, Dhendra; Yuniarti, Nur Atika; Pramudya, Ryan Arya; Tyoso, Jaluanto Sunu Punjul
Djtechno: Jurnal Teknologi Informasi Vol 6, No 2 (2025): Agustus
Publisher : Universitas Dharmawangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46576/djtechno.v6i2.7052

Abstract

Customer churn merupakan tantangan kritis dalam industri telekomunikasi yang berdampak signifikan terhadap profitabilitas perusahaan. Penelitian ini mengusulkan pendekatan hybrid machine learning untuk memprediksi customer churn dengan mengintegrasikan deep learning dan random forest serta mengoptimalkan performa melalui seleksi fitur chi-square dan information gain. Dataset IBM Telco Customer Churn yang terdiri dari 7.043 sampel dengan 31 atribut digunakan dalam penelitian ini. Metodologi penelitian meliputi preprocessing data, implementasi 10-fold cross validation, aplikasi metode seleksi fitur, dan evaluasi performa menggunakan confusion matrix serta metrik klasifikasi biner. Hasil penelitian menunjukkan bahwa implementasi seleksi fitur secara signifikan meningkatkan akurasi prediksi, di mana akurasi tanpa seleksi fitur mencapai 97.00% (Deep Learning) dan 98.68% (Random Forest), sedangkan dengan seleksi fitur chi-square meningkat menjadi 97.97% (Deep Learning) dan 98.72% (Random Forest). Performa terbaik dicapai oleh kombinasi Random Forest dengan seleksi fitur information gain yang menghasilkan akurasi 98.75%, precision 98.37%, recall 99.96%, dan F-measure 99.16%. Temuan ini membuktikan efektivitas kombinasi algoritma ensemble dengan teknik seleksi fitur dalam mengoptimalkan prediksi customer churn untuk mendukung strategi retensi pelanggan yang lebih tepat sasaran
K-Means Clustering Analysis For Identifying Product Purchase Patterns Based On Country On E-Commerce Platforms Pramudya, Ryan Arya; Adiguna, Vinsent Brilian
RIGGS: Journal of Artificial Intelligence and Digital Business Vol. 4 No. 4 (2026): November - January
Publisher : Prodi Bisnis Digital Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/riggs.v4i4.3296

Abstract

E-commerce sites get a lot of transaction data from people in different countries who like different kinds of products. It is very important to know how people buy things based on their country and the type of product they buy in order to come up with better and more efficient marketing plans. This study seeks to discern product purchasing patterns by country through the application of the K-Means clustering algorithm on international e-commerce transaction data. This study utilized a dataset comprising 6,000 e-commerce transaction records, characterized by two primary variables: country and product category. Several methods were used in the preprocessing stage. For example, missing values were replaced to deal with missing data, nominal data was changed to numerical data to change categorical data into numerical data, and Z-transformation was used to normalize the data so that it was all on the same scale. We used the K-Means algorithm to group data into clusters with different k values, such as k=2, 5, 10, 15, 20, and 25. We then used the average within centroid distance metric and the elbow method to find the best number of clusters. The elbow method analysis showed that the best number of clusters was k=10, which showed a big drop in the average within centroid distance value. The ten clusters with algorithms K-Means that were made show very specific market segmentation, with each cluster having its own set of countries and product categories that are most popular.
Co-Authors Adiguna, Vinsent Brilian Dhendra Marutho Jaluanto Sunu Punjul Tyoso Mutiarachim, Atika Yuniarti, Nur Atika