The wettability of material can change from hydrophobic to hydrophilic when treated using plasma nitrogen. The present work investigated the influence of the plasma treatment duration on the modification of polystyrene’s surface coating on a glass surface. The polystyrene layer was produced by means of spin coating method with the rotational speed of 3000 RPM for 1 minute. The plasma was established by a 2 MHz RF generator at the power of 40 watts, pressure of 0.3 Torr, flow rate 40 mL/min. The samples were treated at various exposure time which were 2 min, 5 min, 10 min, and 15 min. The wettability of the polystyrene was measured using a contact angle measurement before and after the nitrogen plasma treatment. Polar functional groups related to the wettability were observed by a Fourier Transform Infrared (FTIR). The longer the treatment duration, the smaller the contact angle was observed. A very low contact angle of 6.42° was achieved at a power of 40 watt at 0.3 torr for the exposure time of 15 min. This means that the surface of the polystyrene changed to super hydrophilic or super wetting. The FTIR results show the spectra of NH2 and C-H functional group at the wavenumber of 3485 cm1 and 2962 cm1, respectively. These functional groups indicate the existence of the polar groups, which contribute to the change of surface hydrophobicity into hydrophilicity.

Pelanggan internet banking tumbuh sangat cepat. Segmentasi nasabah dapat diterapkan berdasarkan data internet banking. Clustering adalah teknik data mining tanpa pengawasan yang dapat digunakan untuk segmentasi pelanggan. Penelitian ini membangun model clustering pada data profil nasabah bank berdasarkan data kredit sehinagga didapatkan segemntasi nasabah yang nantinya digunakan sebagai landasan keputusan untuk melakukan startegi pemasaran. Metode clustering menggunakan metode K-Means dengan validasi cluster menggunakan metode Silhouette coefficient. Berdasarkan Silhouette coefficient didapatkan nilai terbaik untuk 3 cluster yaitu cluster 0, 1, dan 2. Hasil cluster dengan k-means terbagi menjadi 3 cluster yaitu cluster 0 – rata-rata jumlah kredit lebih rendah, durasi pendek, dan pelanggan usia tua, cluster 1 – rata-rata jumlah kredit tinggi, durasi panjang, dan pelanggan paruh baya atau usai pertengahan, dan cluster 2 - rata-rata jumlah kredit lebih rendah, durasi pendek, dan pelanggan usia muda. Hasil segementasi tersebut dapat dijadikan acuan untuk melakukan startegi pemasaran kedepan.

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