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All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika Swabumi (Suara Wawasan Sukabumi) : Ilmu Komputer, Manajemen, dan Sosial Jurnal Khatulistiwa Informatika Techno Nusa Mandiri : Journal of Computing and Information Technology IJISTECH (International Journal Of Information System & Technology) JISICOM (Journal of Information System, Infomatics and Computing) Jurnal Informatika dan Rekayasa Elektronik INFOKUM Akrab Juara : Jurnal Ilmu-ilmu Sosial Jurnal Teknik Informatika (JUTIF) IJISTECH Jurnal AbdiMas Nusa Mandiri INTELEKTIVA International Journal of Educational Research and Social Sciences (IJERSC) Abditeknika - Jurnal Pengabdian Kepada Masyarakat Jurnal Minfo Polgan (JMP) Al-Ijtima: Jurnal Pengabdian Kepada Masyarakat Jurnal Pengabdian Kreatif Cemerlang Indonesia Al-Ijtimā: Jurnal Pengabdian Kepada Masyarakat
WITRIANA ENDAH PANGESTI
Universita Bina Sarana Informatika
Religion Arts Humanities Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Decision Sciences, Operations Research & Management 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 Mathematics Medicine & Pharmacology Physics Public Health Social Sciences Other

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OPTIMALISASI POHON KEPUTUSAN ID3 MENGGUNAKAN PARTICLE SWARM OPTIMIZATION DALAM PREDIKSI ADOPSI LAYANAN DIGITAL PAYMENT Sumarna; Wijaya, Ganda; Suryadithia, Rachmat; Pangesti, Witriana Endah; Yudhistira
Jurnal Informatika dan Rekayasa Elektronik Vol. 8 No. 2 (2025): JIRE November 2025
Publisher : LPPM STMIK Lombok

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36595/jire.v8i2.1711

Abstract

Transformasi digital mendorong peningkatan penggunaan layanan pembayaran digital seperti OVO dan GoPay. Namun, tingkat penggunaan layanan ini belum merata, sehingga diperlukan model prediksi untuk memahami faktor-faktor yang memengaruhi keputusan pengguna dalam mengadopsi layanan tersebut. Penelitian ini mengembangkan model klasifikasi berbasis algoritma ID3 yang dioptimasi menggunakan Particle Swarm Optimization (PSO). Data dikumpulkan melalui kuesioner dari 750 responden, kemudian diproses melalui tahap preprocessing, pelatihan ID3, dan optimasi dengan PSO. Hasil menunjukkan bahwa model ID3+PSO mencapai akurasi 94,53%, lebih tinggi dibandingkan ID3 tanpa optimasi (92,93%). Precision dan recall masing-masing meningkat menjadi 95,41% dan 95,15%, sementara AUC tetap tinggi di angka 98,20%. PSO terbukti efektif menyederhanakan model dan meningkatkan performa klasifikasi. Temuan ini berimplikasi pada peningkatan akurasi sistem rekomendasi dan pengambilan keputusan strategis oleh penyedia layanan digital payment, terutama dalam memahami karakteristik serta potensi adopsi layanan oleh pengguna secara lebih tepat.
Collaborative Filtering Based Recommender Systems For Marketplace Applications Witriana Endah Pangesti; Rachmat Suryadithia; Priyono; Muhammad Faisal; Bilal Abdul Wahid; Arman Syah Putra
International Journal of Educational Research & Social Sciences Vol. 2 No. 5 (2021): October 2021
Publisher : CV. Inara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51601/ijersc.v2i5.184

Abstract

The background of this research is to give the best advice to users who still don't know about other marketplaces that they can still use, to find the items they are looking for and at a cheaper price or with promos they can get. The method used in this research is to use a trial based on data obtained from users who use the media marketplace to purchase an item, with this, the real data can be known so that the best advice for an unknown marketplace can be given. In how many countries, a recommender system has been implemented in a marketplace that will provide advice using advertising media on social media, by using social media, users can find out about the marketplace, and are given continuous advice to install the application so that they can make transactions with purchase of a product in the marketplace. The purpose of this research is to give the best advice so that all people, especially marketplace users, can find out which other marketplaces are in order to know and be able to shop at other marketplaces, by doing price comparisons and being able to get promo prices and knowing based on habits, and ratings from the marketplace.
Co-Authors ADHI DHARMA SURIYANTO Ahmad Rifqy Alfiyan Aji Nurrohman Ananda Sandi Wildani Sabihis Andreyestha Andreyestha Arman Syah Putra Arman Syah Putra Asep Saefulloh Azzahro, Fatimah Dikdik Permana Wigandi Dwiza Riana Dwiza Riana Dwiza Riana Evita Fitri Fanny Fatma Wati Fatimah Azzahro Fitri, Evita Galih Widagdo Ganda Wijaya, Ganda HANAFI EKO DARONO Heru Purwanto Indah Ariyati Ishak, Riswansi Jordy Lasmana Putra Kursehi Falgenti Monikka Nur Winnarto Mugi Raharjo Muhamad Hasan Muhammad Faisal Muhammad Faisal muhammad qomaruddin Nur Azizah, Qudziah Nurul Fiani Salsabila Priyono Qudziah Nur Azizah Rachmat Suryadithia Rachmat Suryadithia Raharjo, Mugi Riyan Latifahul Hasanah Rizky Ade Safitri Safitri Linawati Sartini Sartini Siswahyudianto Siti Marlina Siti Marlina, Siti Sri Hadianti Suharyanto Sumarna Sumarna Sumarna Suryadithia, Rachmat Syarif Hidayatulloh Syarif Hidayatulloh Verry Riyanto W Wibisono Wahid, Bilal Abdul Widagdo, Galih Windu Gata Yudhistira