-Junjung Biru Waste Bank conducts a selection of the best member biennially. The process is crucial, but it does not have a supporting system, which poses problems emerging from data redundancies and data loss. Among the problem is the difficulty for administrators in summarizing data of members who have transactions. To solve the problem, we devised and implemented a decision support system using the CPI (Composite Performance Index) method. The criteria are the amount of balance and active saving during a six-month interval. The results of this research is a web-based decision support system that produces a ranking order of members, which helps in selecting the best member.

Kiky Rizky Nova Wardani, Kiky -Junjung Biru Waste Bank conducts a selection of the best member biennially. The process is crucial, but it does not have a supporting system, which poses problems emerging from data redundancies and data loss. Among the problem is the difficulty for administrators in summarizing data of members who have transactions. To solve the problem, we devised and implemented a decision support system using the CPI (Composite Performance Index) method. The criteria are the amount of balance and active saving during a six-month interval. The results of this research is a web-based decision support system that produces a ranking order of members, which helps in selecting the best member. PENERAPAN TEXT MINING DALAM MENGANALISIS KEPRIBADIAN PENGGUNA MEDIA SOSIAL.

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Abstract

Facebook”merupakan aplikasi jejaring sosial dimana para pengguna mengungkapkan banyak tentang diri mereka sendiri”melalui laman postingan mereka.Sehingga penulis ingin mengetahui informasi apa”saja”yang dapat diambil tentang kepribadian pengguna. Data mining memainkan peran penting yang bertujuan untuk mengubah data mentah menjadi suatu struktur yang dapat dimengerti untuk dapat digunakan lebih lanjut. Text mining mengacu pada proses mengambil informasi berkualitas tinggi dari teks, salah satu metode klasifikasi yang dapat digunakan”ialah algoritma K-Nearest Neighbor. Berdasarkan teori big five personality hasil penelitian menyimpulkan bahwa tingkat akurasi yang diperoleh yaitu 92.92%, dari 550 data dengan nilai karakter kepribadian openness yang paling tinggi yaitu 239, Conscientiouseness sebanyak 16 data, Extraversion sebanyak 173 data, Agreeableness sebanyak 50 data, Neuroticism sebanyak 33 data dan 39 data yang tidak dapat diklasifikasikan. Kata kunci :Text Mining, Big Five Personality, K Nearest Neighbor, Facebook

Item Type:	Article
Subjects:	K Law > K Law (General)
Divisions:	Faculty of Law, Arts and Social Sciences > School of Law
Depositing User:	Mr Edi Surya Negara
Date Deposited:	16 Jun 2022 01:34
Last Modified:	16 Jun 2022 01:34
URI:	http://eprints.binadarma.ac.id/id/eprint/11217

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