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All Journal Jurnal Kesehatan BALANGA: Jurnal Pendidikan Teknologi dan Kejuruan JIPMukjt:Jurnal Ilmu Pendidikan Muhammadiyah Kramat Djati Jurnal DIALEKTIKA : Jurnal Ilmu Sosial Jurnal Budgeting Jurnal Ilmiah MEA (Manajemen, Ekonomi, dan Akuntansi) Jurnal Ilmu Pendidikan dan Kearifan Lokal (JIPKL) PANDU: Jurnal Pendidikan Anak dan Pendidikan Umum AL-THIFL : Jurnal Ilmiah Pendidikan Guru Madrasah Ibtidaiyah Jurnal Pendidikan Guru Madrasah Ibtidaiyah Al-Amin Jurnal Pengabdian Masyarakat dan Riset Pendidikan Setawar Abdimas Journal of Informatics and Information Security
Annisa Wulandari
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Religion Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Physics Public Health Social Sciences Other

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Journal : Journal of Informatics and Information Security

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Penerapan Algoritma K-Means Untuk Pengelompokkan Minat Konsumen Gas LPG Pada Pangkalan Sudiawati Annisa Wulandari; Tri Dharma Putra; Srisulistiowati, Dwi Budi
Journal of Informatic and Information Security Vol. 3 No. 1 (2022): Juni 2022
Publisher : Program Studi Informatika, Fakultas Ilmu Komputer Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/vfx5ae35

Abstract

Pangkalan Sudiawati is one of the shops engaged in the sale of LPG Gas products domiciled in Harapan Indah, North Bekasi. The goods sold at the Sudiawati base are 3 Kg and 12 Kg LPG Gas. These problems can be solved by using one of the techniques in data mining, namely the K-Means Clustering algorithm. This research is intended to assist Pangkalan Sudiawati in selling 3 Kg and 12 Kg LPG gas to consumers, to group sales data in order to maximize stock management. The data is processed by manual calculations using the K-Means algorithm and using Microsoft Excel 2019 Software. These results can be used to improve stock managementand sales strategies at Pangkalan Sudiawati.
Co-Authors Ahmad Nurul Ihsan B Annisa Nur Azizah Annisya Rossita Palupi Dinda Maura Prameswari Dwi Budi Srisulistiowati Efriani Eka Rahmadhayanti Fitri Zahrotul Jannah Ikmawati Ikmawati Indriani Prasmitha Mardhatillah Hafidzah Harahap Maryam Alhansa Zuhro Mi'roju Abdul Rozaq Al Ghifari Muhammad Marzuki Mukhlison Effendi Nasrah, Nasrah Nur Masyiah Masyir Nur Wahyu Malpiana P Nurhayati Puja Afrianti Orbit Thomas Pandu Wilantara Rahmalia Afriyani Ratri Dian Aprilia RINI INDAHWATI Safira Nur Sabillah Salma Azizah Azzahra Syarif Nur Titis Dyah Dewi Narendradhuhita Tri Dharma Putra Untu, Zainuddin Untu Wella Ananda Wildan Adib Furqon Winda Ramadianti Yofy Syarkani Yuwanita Nurmasari