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All Journal KAREBA : Jurnal Ilmu Komunikasi Mimbar Agribisnis: Jurnal Pemikiran Masyarakat Ilmiah Berwawasan Agribisnis Jurnal Komunikasi Ikatan Sarjana Komunikasi Indonesia Syntax Literate: Jurnal Ilmiah Indonesia urnal Interaksi: Jurnal Ilmu Komunikasi Journal of Communication Sciences (JCoS) Jurnal Ilmiah Mandala Education (JIME) JISIP: Jurnal Ilmu Sosial dan Pendidikan BUANA SAINS Borneo Engineering: Jurnal Teknik Sipil Proceedings of International Conference on Da'wa and Communication Economics and Digital Business Review Journal of Economics and Business UBS Journal of Applied Civil Engineering and Infrastructure Technology (JACEIT) Calathu: Jurnal Ilmu Komunikasi Jurnal Locus Penelitian dan Pengabdian JOMPA ABDI: Jurnal Pengabdian Masyarakat Journal of Comprehensive Science Civil Engineering Scientific Journal Jurnal Pengabdian Masyarakat Bangsa Blantika : Multidisciplinary Journal FAWAID: Sharia Economic Law Review Jurnal Global Ilmiah JAMIN Jurnal Inovasi Global West Science Islamic Studies Jurnal Multidisiplin Indonesia Jurnal Archipelago Cateris Paribus Journal CHANNEL: Jurnal Komunikasi
Hasrullah Hasrullah, Hasrullah
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Journal : Journal of Comprehensive Science

 1 
Analisis Efektivitas Sistem Rekomendasi pada Toko Online Purnomo, Cahyo; Hasrullah, Hasrullah
Journal of Comprehensive Science Vol. 4 No. 1 (2025): Journal of Comprehensive Science (JCS)
Publisher : Green Publisher Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59188/jcs.v4i1.2959

Abstract

Dalam era digital, toko online menghadapi tantangan utama dalam membantu pelanggan menemukan produk yang relevan dan sesuai dengan preferensi mereka di tengah banyaknya pilihan yang tersedia. Sistem rekomendasi sering kali menghadapi kendala dalam memberikan saran yang efektif dan personal, sehingga dampaknya terhadap kepuasan pelanggan dan kinerja bisnis dapat bervariasi tergantung pada implementasinya. Penelitian ini menganalisis efektivitas berbagai sistem rekomendasi yang diterapkan pada toko online untuk meningkatkan pengalaman pengguna dan penjualan. Sistem rekomendasi merupakan alat penting dalam membantu pelanggan menemukan produk yang relevan dengan preferensi mereka, terutama di tengah jumlah pilihan produk yang terus meningkat. Analisis ini mengkaji metode-metode rekomendasi, seperti algoritma Apriori, Collaborative Filtering, dan K-Means Clustering, yang digunakan dalam toko online untuk memberikan rekomendasi yang personal. Hasil analisis menunjukkan bahwa Collaborative Filtering, terutama yang berbasis pengguna, paling efektif dalam memberikan rekomendasi personal.Penelitian ini diharapkan dapat memberikan wawasan yang bermanfaat bagi pengembang sistem rekomendasi di platform e-commerce, terutama dalam mengoptimalkan kinerja sistem dan meminimalkan tantangan yang ada.
Sistem Rekomendasi Pemilihan Produk Skincare Wildana Al Kautsar, Arifa; Hasrullah, Hasrullah
Journal of Comprehensive Science Vol. 4 No. 2 (2025): Journal of Comprehensive Science (JCS)
Publisher : Green Publisher Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59188/jcs.v4i2.3026

Abstract

The skin is the largest organ of the body that requires proper care to maintain a healthy body. Along with the increasing trend of skincare or skincare in Indonesia, many consumers face difficulties in choosing products that suit their skin type and problems. In this case, the Content-Based Filtering-based recommendation system can provide a solution for users to choose skincare products that suit their preferences based on existing product reviews. This study aims to develop a skincare product selection recommendation system using the Content-Based Filtering approach, which is based on product description analysis and user reviews. The novelty of this study lies in the use of TF-IDF weighting and Cosine Similarity calculation to analyze similarities between products based on user descriptions and reviews. The research method used is qualitative with a descriptive approach, which involves data collection through scrapping from the Female Daily platform and data analysis using pre-processing and TF-IDF weighting techniques. The results of the study show that this recommendation system can provide the most relevant skincare products based on the similarity of reviews and product descriptions, thus helping users choose products that suit their skin needs. This study concludes that Content-Based Filtering is effective in helping users find the right skincare products, minimizing product selection errors, and improving user experience.
Co-Authors Adi Hermawansyah Aftah, Chairul Ahmad Husain Mappaseling, Ahmad Husain Ahmad Syarif, Iif Akbar, Aditya Andani, Indriani Andi Alimuddin Unde, Andi Alimuddin Andi Muhammad Abdi Anggerwati, A. Indah Anggriani, Ririn Ansar Suherman, Ansar Aprianto, M. Tomi Aris, Ardiyanti Arland Yusran, Arland Arnus, Sri Hadijah Burhanuddin, A Putri Permatasari Arafah Chatarina Umbul Wahyuni Estu Pratiwi, Yupitari Fathurrijal, Fathurrijal Firdaus Wahyudi Fudjaja, Letty Hafied Cangara, Hafied Hamida Hasan Harwadi, Fuad Hasandi, Ilman Hasrullah, Excelsia Ramadhany Hendra Maniza, Lalu Hernadi, Ahmad Hidayati, Nurmalika I Gusti Ngurah Antaryama Ishanan, Ishanan Jeanny Maria Fatimah Judijanto, Loso Karnay, Sudirman Karunia Akbar, Ilham Kusuma, Afandi La Jaali, La Laras, Dwi lestari, winda Lisa Musfirah, Lisa Merdikna Raturain, Putri Mochtar Touwe, Mochtar Mokodenseho, Sabil Muhammad Iqbal Sultan, Muhammad Iqbal Muhammad Nur Muhammad Syafri, Muhammad Muhammad Yahya Musran Munizu Mustakim Mustakim Nor, Syariyan Nosakros Arya, Nosakros Nurdin, Muhammad Firdan Nuri Sanjaya, Irfan Nurwijayanti Pratama, Rafael Verdyansyah Purnomo, Cahyo Raden Firdaus Wahyudi, Raden Firdaus Rahmadani, Noviyanti Putri Rahmadiansyah, Afique Rosniar Rosniar, Rosniar Sagena, Uni W sahrani Putri, Risma Saleh, Sitti Fithriani Seltika Canta, Dila Selva, Selva Setyaningsih, Erlin Siwansyah, Siwansyah Sonni, Alem Febri Syahrir Soleman, Syahrir T, Ruslang Taqwa, Amrullah Verdyansyah Pratama, Rafly Virginiawati, Aulia Wahyu Santoso Wahyuni, Nuorma Wildana Al Kautsar, Arifa Wirawan Jaya, Wirawan Wisesa, Harna Rizki Yudistia, Tasya Takhayaza Yuhdi Fahrimal Zahron, Evi Ziraldo, Bryan