Implementasi Algoritma K-Means Clustering untuk pemetaan Perkebunan Kabupaten Sukabumi dengan memanfaatkan Citra Google Maps

Fuzilesamana, Adie Pratama (2018) Implementasi Algoritma K-Means Clustering untuk pemetaan Perkebunan Kabupaten Sukabumi dengan memanfaatkan Citra Google Maps. Diploma thesis, UIN Sunan Gunung Djati Bandung.

[img]
Preview
Text (COVER)
1_cover.pdf

Download (116kB) | Preview
[img]
Preview
Text (ABSTRAK)
2_abstrak.pdf

Download (271kB) | Preview
[img]
Preview
Text (DAFTAR ISI)
3_daftarisi.pdf

Download (127kB) | Preview
[img]
Preview
Text (BAB I)
4_bab1.pdf

Download (236kB) | Preview
[img] Text (BAB II)
5_bab2.pdf
Restricted to Registered users only

Download (531kB) | Request a copy
[img] Text (BAB III)
6_bab3.pdf
Restricted to Registered users only

Download (764kB) | Request a copy
[img] Text (BAB IV)
7_bab4.pdf
Restricted to Registered users only

Download (1MB) | Request a copy
[img] Text (BAB V)
8_bab5.pdf
Restricted to Registered users only

Download (103kB) | Request a copy
[img] Text (DAFTAR PUSTAKA)
9_daftarpustaka.pdf
Restricted to Registered users only

Download (107kB) | Request a copy

Abstract

Daerah di Kabupaten Sukabumi merupakan penghasil yang cukup tinggi pada bidang perkebunan karena banyak nya jenis tumbuhan yang dapat di maksimalkan di daerah tersebut. Maka tentunya pemanfaatan perkebunan akan baiknya ada fungsi sistem pemeliharaan tanaman yaitu salah satunya dengan sistem pemetaan perkebunan. Pemetaan yang tersedia sekarang ini masih belum dilakukan secara digital dan proses pengisian data yang terlalu banyak dimasukan yang mengakibatkan proses pemetaan yang lama. Maka dari itu proses pemetaan akan dilakukan secara digital dan akan dilakukan proses cluster dengan memanfaatkan algoritma K-Means Clustering. Dengan menggunakan algoritma K-Means Clustering ini maka akan menentukan potensi komoditas mana saja yang memiliki tingkat tinggi, sedang dan rendah. Setelah dilakukannya proses clustering dan diketahui nya potensi perkebunan akan dilakukan pemetaan dengan memanfaatkan Google Maps yang nantinya akan memberikan informasi perkebunan di setiap kecamatan yang ada di kabupaten Sukabumi. Regions in kabupaten sukabumi received an average of produces who moderately high on smallholder tree crops because a lot of her sorts of crops at that stage they could maximize which women in this area .Then surely the utilization of in the plantation sector and be the best and will there is the function of the system the cost of maintenance plant promised to supply one of them is by a mapping system for the plantation sector. Mapping available now has still not been done in digitally and the process of filling in the data too much inserted that resulted in the process of mapping a long. Therefore the process mapping will be done in digital and will be done the process clusters by using k-means algorithm clustering. By the use of an algorithm k-means clustering to it and the tent will determine the potential of these commodities only require anywhere i like he complaining possessing to a high degree , is now being constructed and low .After great suffering he has brought the process of and was detected as clustering his tree crops as well as the safe situation at home will be conducted by the the mapping of by making use of the google maps that is going to want to tell him plantation companies in the the each area kabupaten sukabumi received an average.

Item Type: Thesis (Diploma)
Uncontrolled Keywords: Komoditas; Cluster; K-Means Clustering; Google Maps
Subjects: Divinatory Graphology
Earth Sciences > Data Processing and Analysis of Geology
Field and Plantation Crops
Area Planning > Plans for Specific Kinds of Areas
Divisions: Fakultas Sains dan Teknologi > Program Studi Teknik Informatika
Depositing User: Adie Pratama Fuzilesmana
Date Deposited: 24 Jul 2018 03:39
Last Modified: 24 Jul 2018 03:39
URI: http://digilib.uinsgd.ac.id/id/eprint/11363

Actions (login required)

View Item View Item