PENGEMBANGAN APLIKASI ANDROID UNTUK PENINGKATAN EFISIENSI OPERASI PENDATAAN PENGAMATAN BUNGA TUMBUHAN
The use of technology in applications is very supportive of company activities. The company's success is influenced the compatibility of expectations between system analysts, application users, sponsors and customers. The current situation of the company is still using a manual data collection...
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2022-07-19.
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| 100 | 1 | 0 | |a Amien Aziz, . |e author |
| 245 | 0 | 0 | |a PENGEMBANGAN APLIKASI ANDROID UNTUK PENINGKATAN EFISIENSI OPERASI PENDATAAN PENGAMATAN BUNGA TUMBUHAN |
| 260 | |c 2022-07-19. | ||
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| 500 | |a http://repository.upnvj.ac.id/19761/43/LAMPIRAN.pdf | ||
| 500 | |a http://repository.upnvj.ac.id/19761/33/HASIL%20PLAGIARISME.pdf | ||
| 500 | |a http://repository.upnvj.ac.id/19761/48/ARTIKEL%20KI.pdf | ||
| 520 | |a The use of technology in applications is very supportive of company activities. The company's success is influenced the compatibility of expectations between system analysts, application users, sponsors and customers. The current situation of the company is still using a manual data collection system using paper based form, resulting in slow data procurement and even stopping completely on holidays. It is important for every agricultural company to know the condition of their flowering plants, one way to find out is by doing data mining. The data used in this study is secondary data from the company, that are not labeled, so it is necessary to use an unsupervised algorithm, which in this study uses the K-Means algorithm. Starting from this problem, a digital system is needed that can provide data in a reliable, precise, fast, and efficient manner. A data mining model was also created which ultimately resulted in 2 groups, which were obtained using the elbow method, with 328 members of cluster 1 and cluster 2 with 763 members. | ||
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