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All Journal SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Budimas : Jurnal Pengabdian Masyarakat International Journal of Computer and Information System (IJCIS) Transformasi Jurnal Ilmiah IT CIDA : Diseminasi Teknologi Informasi Jurnal Rekayasa Sistem Informasi dan Teknologi
Kapti Kapti, Kapti
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Augmented Reality Kampanye Bahaya Merokok Berbasis Android Kapti, Kapti; Priyoatmoko, Wahyu
Jurnal Ilmiah IT CIDA Vol 6 No 1: Juni 2020
Publisher : STMIK Amikom Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (840.446 KB) | DOI: 10.55635/jic.v6i1.115

Abstract

Merokok merupakan rutinitas sebagian masyarakat, baik di rumah maupun di tempat umum. Sedangkan di STMIK Bina Patria Magelang aktivitas merokok masih bisa ditemui di kalangan mahasiswa. Hal ini  perlu untuk dicarikan penyelesaiannya. Penelitian ini memiliki tujuan Dapat merancang dan membangun Augmented Reality Kampanye Bahaya Merokok yang diaplikasikan di smartphone dengan OS Android”. Penelitian ini menggunakan metode perancangan dan pengembangan perangkat lunak MDLC. Enam tahapan yang dimikili MDLC antara lain : concept, design, material collecting, assembly, testing, distribution. Augmented Reality Kampanye Bahaya Merokok yang telah dibuat dapat menampilkan gambar 3d dampak rokok bagi tubuh manusia, menampilkan kandungan rokok dan menampilkan informasi bahaya rokok bagi tubuh manusia. Hasil Pengujian kuesioner  aplikasi ini menunjukkan 70% responden menyatakan bahwa aplikasi ini  layak. Hal ini membuat mereka sadar akan bahaya rokok. Kata Kunci: Android, Augmented Reality, Bahaya rokok, Media , Unity.
SEGMENTASI PELANGGAN MENGGUNAKAN METODE DBSCAN UNTUK MENDETEKSI POLA BELANJA Handayani, Riska Dwi; Astuti, Dwi; Priyoatmoko, Wahyu; Kapti, Kapti
TRANSFORMASI Vol 21, No 1 (2025): TRANSFORMASI
Publisher : STMIK BINA PATRIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56357/jt.v21i1.439

Abstract

Customer segmentation is one approach used to identify customer characteristics. Accurate segmentation allows companies to personalize offers, increase customer retention and optimize marketing costs. The purpose of this study is to group customer characteristics of a retail company using the DBSCAN (Density-Based Spatial Clustering of Applications with Noise) method. The DBSCAN method does not require initial determination of the number of clusters, is able to recognize clusters with irregular shapes and can identify outliers or customers with extreme patterns. The dataset used is an external dataset obtained from Kaggle. The dataset contains customer personalization analysis with a total of 2,240 rows and 29 columns. The results of the study show that the DBSCAN method can produce an eps value of 1.2 and produce the highest Silhouette Score of 0.080 with 4 clusters formed. Visualization of segmentation results with PCA dimension reduction techniques into two dimensions to facilitate interpretation. The PCA visualization produces 5 clusters, each of which represents its respective customer group. Thus, this approach offers an adaptive segmentation alternative that is more sensitive to complex behavioral patterns.Keywords : Customer segmentation, DBSCAN, shopping patterns, silhouette scorem, PCA
Co-Authors Anwar, Muchtadil Dwi Astuti Ericka Darmawan Fatkhurrochman, Fatkhurrochman handayani, riska dwi Ina Sholihah Widiati, Ina Sholihah Jok, Felix Joko Purwanto Joko Purwanto Khasanah, Ilfi Laili Muhammad Abdul Muin Muqorobin, Muqorobin Nahdliy, Faiz Jabar Saputri, Panca Dewi Sri Waluyo Sugeng Wahyudiono, Sugeng Sukris Sutiyatno Tri Yusnanto Ulinuha, Zakya Faaza Wahyu Priyoatmoko Yeza Febriani