Judul: The Impact Of Credit Use On Rubber Farming Income In South Sumatra
Abstrak: Produktivitas erkebunan karet Indonesia mengalami trend yang fluktiatif. Salah satu penyebabnya adalah sulitnya petani untuk mendapatkan permodalan. Kredit usahatani menjadi salah satu solusi sulitnya permodalan petani. Tujuan penelitian ini adalah menganalisis dampak penggunaan kredit terhadap pendapatan usahatani karet di Sumatera Selatan. Data yang digunakan adalah data sekunder Survei Rumah Tangga Usahatani Perkebunan 2014 oleh Badan Pusat Statistik. Petani responden yang diteliti berjumlah 4.924 petani karet di Sumatera Selatan yang terdiri dari petani 98 yang mengambil kredit dan 4.826 petani yang tidak mengambil kredit. Provinsi Sumatera Selatan dipilih sebagai lokasi penelitian karena merupakan provinsi dengan produksi karet terbesar di Indonesia. Metode yang digunakan adalah metode deskriptif dan propensity score matching (PSM). Hasil penelitian menunjukkan bahwa biaya terbesar yang dikeluarkan petani adalah biaya TKDK dan kredit tidak memberikan dampak yang signifikan terhadap pendapatan usahatani karet. Beberapa variabel yang memengaruhi keputusan petani dalam mengambil kredit diantaranya adalah ingkat pendidikan, keikutsertaan penyuluh, keanggotaan koperasi, kemitraan dengan Perusahaan dan penggunaan benih bersertifikat. Diperlukannya pembimbingan dan penyuluhan kepada petani agar dana yang diberikan dapat digunakan secara optimal untuk usahatani sehingga pendapatan petani dapat meningkat serta diharapkan petani tergabung dalam keanggotaan kelompok tani dan koperasi agar lebih mudah mendapatkan akses dan informasi terkait kredit., The productivity of Indonesian rubber plantations is experiencing a fluctuating trend. One of the reasons is the difficulty for farmers to obtain capital. Farming credit is one solution to farmers' capital difficulties. The aim of this research is to analyze the impact of credit use on rubber farming income in South Sumatra. The data used is secondary data from the 2014 Plantation Farming Household Survey by the Central Statistics Agency. The respondent farmers studied were 4,924 rubber farmers in South Sumatra, consisting of 98 farmers who took credit and 4,826 farmers who did not take credit. South Sumatra Province was chosen as the research location because it is the province with the largest rubber production in Indonesia. The method used is the descriptive method and propensity score matching (PSM). The research results show that the largest costs incurred by farmers are TKDK costs and credit does not have a significant impact on rubber farming income. Several variables that influence farmers' decisions in taking credit include level of education, participation of extension workers, cooperative membership, partnerships with companies and use of certified seeds. Guidance and counseling is needed for farmers so that the funds provided can be used optimally for farming so that farmers' income can increase and it is hoped that farmers will join farmer groups and cooperatives so that it is easier to get access and information related to credit.
Keyword: karet, kredit, pendapatan, propensity score matching

Judul: Determinants of Farmers’ Decision to Take Credit and The Impact on Rubber Farming Performance
Abstrak: Karet adalah salah satu komoditas perkebunan yang banyak diekspor Indonesia. Namun produktivitasnya masih rendah, dimana kesulitan permodalan petani menjadi permasalahan utama dan salah satu cara penguatan permodalan adalah program kredit. Penelitian ini bertujuan untuk menganalisis faktor-faktor yang memengaruhi petani mengambil kredit dan dampaknya terhadap kinerja usahatani karet. Data yang digunakan merupakan data sekunder Survei Rumah Tangga Usaha Perkebunan Tahun 2014 berjumlah 19.229 petani, terdiri dari 355 petani mengambil kredit dan 18.874 petani tidak mengambil kredit. Metode yang digunakan adalah regresi logistik dan propensity score matching. Hasil penelitian menunjukkan bahwa variabel yang signifikan memengaruhi keputusan petani mengambil kredit, antara lain jenis kelamin, tingkat pendidikan, lokasi usahatani, keanggotaan koperasi, keanggotaan kelompok tani, dan kepemilikan lahan. Namun, variabel usia, jumlah tanggungan keluarga, penyuluhan, kemitraan, dan umur tanaman tidak berpengaruh signifikan terhadap keputusan petani mengambil kredit. Selain itu, kredit berdampak positif terhadap produksi, penerimaan, dan biaya usahatani karet, tetapi tidak berpengaruh signifikan terhadap produktivitas dan profit usahatani karet., Rubber is one of the plantation commodities which exported by Indonesia. But the productivity is low, that farmer’s capital difficulty is the main problem and credit is one of the way to solve it. This study aims to analyze the factors that influence farmers in taking credit and its impact on the performance of rubber farming. The data used is secondary data from the 2014 Plantation Business Household Survey with total of 19,229 farmers, consisting of 355 farmers taking credit and 18.874 farmers not taking credit. The method used are logistic regression and propensity score matching. The results showed that significant variables influenced farmers' decisions to take credit are gender, education level, farm location, cooperative membership, farmer group membership, and land ownership. However, age, number of family dependents, agricultural extension services, partnerships, and age of plant are not significant to farmer's decision to take credit. In addition, credit has positive impact on production, income, and expenditure of rubber farming, but it has no significant effect on productivity and profits of rubber farming.
Keyword: credit, farm performance, propensity score matching, rubber

Judul: Construction of Strongly Optimal Binary Linear Code with Minimum Distance 9 and 11
Abstrak: A binary linear code of length n over q F is a subspace of n q F . A code has three parameters that attached to it, namely length, dimension, and minimum distance. A code with length n, dimension k and minimum distance d is often called [n, k, d ]-code. Usually, when two parameters are given, then we want to find a code that has the best value for the last parameter. Based on Gilbert- Varshamov bound, if a [n, k, d ]-code exists and can not be expanded, we call it a strongly optimal code. In this paper, we construct strongly optimal code with minimum distance 9 and 11. In constructing the code, we created a theorem and algorithm based on Gilbert-Varshamov bound before we implement the algorithm to MAPLE programming language. Because of computational limitations, the program can only construct up to k = 10 for d = 9 and k = 12 for d = 11.
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