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All Journal JTT (Jurnal Teknologi Terpadu) AMMA : Jurnal Pengabdian Masyarakat
Adhivia Julian
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Humanities Chemistry Civil Engineering, Building, Construction & Architecture Control & Systems Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mechanical Engineering Nursing

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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

Show Abstract | Download Original | Original Source | Check in Google Scholar

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.
Segmentasi Pelanggan Menggunakan Algoritma K-Means Pada Jaringan Telekomunikasi Untuk Optimalisasi Strategi Pemasaran Adhivia Julian
Jurnal Teknologi Terpadu Vol 13 No 1 (2025): JTT (Jurnal Terpadu Terpadu)
Publisher : Pusat Penelitian dan Pengabdian Kepada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32487/jtt.v13i1.2436

Abstract

Dalam era digital ini, industri telekomunikasi dihadapkan pada tantangan untuk memahami kebutuhan pelanggan yang semakin kompleks. Penelitian ini mengimplementasikan algoritma K-Means untuk segmentasi pelanggan, dengan tujuan utama mengidentifikasi pola perilaku serta merumuskan strategi pemasaran yang lebih efektif. Melalui pendekatan Knowledge Discovery in Databases(KDD), penelitian ini mencakup tahapan seleksi data, pra-pemrosesan, transformasi, penambangan data (data mining), dan evaluasi pola. Data yang dianalisis meliputi informasi mengenai jenis layanan, kecepatan internet, tipe perangkat, dan lokasi pelanggan. Algoritma K-Means diaplikasikan untuk mengelompokkan pelanggan berdasarkan kesamaan perilaku, dengan jumlah klaster optimal ditentukan menggunakan metrik Davies-Bouldin Index (DBI). Hasil analisis menghasilkan tiga klaster, yakni pelanggan dengan kebutuhan layanan dasar, pengguna layanan internet berkecepatan rendah yang sensitif terhadap harga, serta pengguna layanan internet intensif yang jarang me-manfaatkan fitur tambahan. Strategi pemasaran yang diusulkan mencakup penawaran paket hemat, promosi bundling, dan edukasi tentang manfaat fitur tambahan. Evaluasi menggunakan DBI menunjukkan nilai sebesar 0,055, yang mengindikasikan bahwa klaster yang dihasilkan memiliki kualitas yang baik. Penelitian ini menunjukkan efektivitas algoritma K-Means dalam segmentasi pelanggan, sekaligus memberikan dasar bagi perusahaan telekomunikasi untuk meningkatkan loyal-itas dan retensi pelanggan melalui strategi pemasaran yang lebih terarah. Penelitian ini juga mena-warkan peluang untuk eksplorasi lebih lanjut dalam penerapan data mining di sektor telekomunikasi jaringan.
Co-Authors Aditya Fauzi Samsuri Edi Tohidi Edi Wahyudin