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All Journal JOINT (Journal of Information Technology Prosiding Seminar Nasional Unimus
Dita Rizki Amalia
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Humanities Computer Science & IT Engineering Health Professions Nursing Public Health

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INTEGRATED LIBRARY SYSTEM UNTUK MENINGKATKAN EFEKTIVITAS LAYANAN PERPUSTAKAAN DENGAN MENGGUNAKAN METODE ALGORITMA APRIORI (Studi Kasus: PERPUSTAKAAN KABUPATEN CIREBON): METODE ALGORITMA APRIORI Alfi Nurfajiah; Tuti Hartati Mindara; Dita Rizki Amalia
Journal of Information Technology Vol 3 No 1 (2021): JOINT (Journal of Information Technology)
Publisher : LPPM STMIK AMIK BANDUNG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47292/joint.v3i1.55

Abstract

Cirebon Regency Library is one of the libraries that stands on Jl. Sunan Drajat No.9 Source. Where the library has improved its services through the provision of facilities and rooms that are very adequate. With the increase in book collections in the library, it would be great if you use a data mining system that functions to determine the data set as a process that can help in finding the books desired by library customers. The association rule technique using a priori algorithm can be used as a reference in finding out simultaneous borrowing in one transaction that occurs on one item. After determining that one item, testing is carried out whether it can meet the support standard which can be used as a minimum requirement then a rule is made in accordance with the confidance drinking standard, since 2020 the Library System in Cirebon Regency has used localhost which is an integrated library system in providing services to customers. One of the services provided is information that is needed centrally so that it can support decision makers what books are available for borrowing, what are the conditions for becoming a member, who is already a member. By using this system, we can see a pattern of borrowed books based on recommendations from librarians and can make arrangements in book storage in accordance with the patterns of information in book storage.
Perbandingan Hasil Klasifikasi Rasa Minuman Thai Tea yang Paling Digemari Menggunakan K-means dan K-medoids Dita Rizki Amalia; Riri Narasati; Ahmad Faqih
Prosiding Seminar Nasional Unimus Vol 2 (2019): Tantangan Implementasi Hasil Riset Perguruan Tinggi untuk Industrialisasi
Publisher : Universitas Muhammadiyah Semarang

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Abstract

Data Mining saat ini semakin marak digunakan obaik oleh instansi, perusahaan, maupun organisasi. Dalam hal ini Peneliti tertarik meneliti tentang minuman yang sedang menjadi tren dalam masyarakat karena melihat minat yang besar di kalangan masyaraka., Ranah dalam penelitian ini adalah menggunakan data mining dengan kmedoids dan k-means, dimana dalam pengelompokkan kedua algorima ini memperoleh hal yang sama namun cara yang berbeda k-menas dengan mengambil nilai rata-rata sedangkan k-medoids dengan mengambil nilaitengah. Langkah dalam data mining adalah data seleksi, data cleaning, data authentication,data integration, dan data transformation. Hasil penelitian menunjukkan kedua metode menghasilkan cluster yang sama yaitu rekomendasi rasa thai tea original dengan susu dan greentea dengan susu dengan nilai centroid 0,286 sesuai dengan target penelitian.Kata kunci: Data Mining, K-Means, K-Medoids B, Clustering.
Co-Authors Ahmad Faqih Alfi Nurfajiah Riri Narasati Tuti Hartati