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ITS » Master Theses » Matematika Industri - S2
Posted by anis at 02/01/2007 12:06:22 • 9690 Views
FAKTOR-FAKTOR YANG MEMPENGARUHI KEMAMPUAN PETANI MEMBAYAR KREDIT USAHA TANI
The Factors That Influence Farmers Capabilities Of Returning Farm Credit
Created by :
MOKODOMPIT, SUTOMO ( )
| Subject: | Kredit pertanian | | Keyword: | Kredit usahatani
dana bantuan pemerintah
Analisis |
[ Description ]
Kredit usahatani merupakan dana bantuan pemerintah untuk meningkatkan
taraf hidup petani di Indonesia, manun sekarang ini sebagian besar petani tidak dapat
mengembalikan kredit sehingga terjadi kredit macet.
Penelitian ini akan melihat faktor-faktor yang mempengaruhi kemampuan
petani untuk mengembalikan kredit. Alat analisis yang digunakan adalah Analisis
Regresi Komponen Utama. Dari hasil analisis diperoleh :
Faktor Pertama, terdiri dari luas lahan (XI), Urea (X5), TSP (X6), KCL (X7) dan
pestisida (X8) dimana faktor ini mampu menjelaskan 39,7 % keragaman total.
Faktor Kedua, terdiri dari Umur petani (X2), Pengalaman bertani (X3), dan jumlah
tanggungan keluarga (X4) mampu menjelaskan 20,9 % keragaman total.
Faktor Ketiga, terdiri dari Status pemilikan lahan (X9) mampu menjelaskan 11,1 %
dari keragaman total.
Faktor Keempat, terdiri Tingkat Pendidikan (X10) mampu menjelaskan 17,2 % dari
keragaman total.
Persamaan regresi dari keempat faktor tersebut adalah:
Y = 2612053-732747Wi+363591W2+210564W3+189300W4
Dalam hal kemampuan petani untuk mengembalikan kredit usahatani, minimal petani
pemilik harus mengelolah lahan seluas 1,1 ha, dan petani penyewa 1,72 ha untuk
dapat meminjam kredit sebesar Rp. 1.000.000,-
Alt. Description
The farm credit is assistence fund to increase standard of living the Indonesian
farmers. But morer of the farmers are not be able to pay the credit.
This research is intend to find factors influence farmer capabilities of
returning farm credit. The analysis method is Principal Component Regression
analysis. The result of analysis are :
The First Factor, are Wide of area (XI), Urea (X5), TSP (X6), KCL (XT) and
Pesticide (X8) determine to 39,7 % total variabilities.
The Second Factor, are Age farmer (X2), Farmer experience (X3) and number of
burden (X4) determine to 20,9 % total variabilities.
The Third Factor, is ownship status (X9) determine to 11,1 % total variabilities.
The Fourth Factor, is Education level (XI0) determine to 17,2 % total variabilities.
The Regression Model from fourth factor is :
Y = 2612053-732747Wi+363591W2+210564W3+189300W4
The capabilities farmers to pay of farm credit is depend on minimal
arearequarement 1,1 hectare if owner area, but if he rent farmers must be 1,72 hectare
for pay in installmemnt for one million credit
| Contributor | : |
- Dra. Farida Agustini W, MS.
Drs. Soehardjoepri, M.Si.
| | Date Create | : | 02/01/2007 | | Type | : | Text | | Format | : | pdf ; 43 pages | | Language | : | Indonesian | | Identifier | : | ITS-Master-31000020154444 | | Collection ID | : | 31000020154444 | | Call Number | : | 519.536 Mok f |
Source :
Theses Industry Mathematic RT 519.536 Mok f, 2001
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