Koehuan, Jonathan E. and Prof. Dr. Ir. Bambang Suharto,, MS and Dr. Ir. Gunomo Djoyowasito,, MS and Prof. Dr. Ir. Wignyanto,, MS (2020) Studi Analisis Pertumbuhan Produktivitas Air Untuk Tanaman Pangan di Wilayah Timor Barat. Doktor thesis, Universitas Brawijaya.
Abstract
Wilayah Timor Barat merupakan bagian dari Provinsi Nusa Tenggara Timur (NTT), berklim semi-arid, sebagaian besar penduduk bekerja pada sub sektor pertanian tanaman pangan. Tanaman pangan utama di Timor Barat adalah jagung dan padi dengan sistim budidaya tradisional untuk konsumsi. Meskipun mengalami peningkatan produksi tetapi masih belum dapat memenuhi kebutuhan saat ini dan kebutuhan akan datang. Peningkatan produksi pangan sangat direkomendasikan melalui peningkatan produktivitas air untuk tanaman. Belum tersedianya hasil penelitian produktivitas air untuk tanaman pangan di Wilayah Timor Barat dan belum ada penelitian terkait pertumbuhan total faktor produktivitas air untuk tanaman memotivasi peneliti untuk melakukan penelitian ini. Penelitian ini bertujuan untuk mengetahui nilai fisik produktivitas air untuk tanaman pangan. Mendesain model frontier dan menjelaskan pertumbuhan dan dekomposisi total faktor produktivitas air untuk tanaman pangan. Membangun model frontier parametrik efisiensi efek dan menjelaskan pengaruh faktor eksternal non stokasitk terhadap efisiensi pemanfaatan air tanaman serta merumuskan rekomendasi melalui perbandingan pertumbuhan total faktor produktivitas air untuk tanaman pangan. Penelitian ini menggunakan data sekunder iklim dan non iklim tahun 2000-2015. Penelitian ini dilaksanakan dalam empat tahap yaitu tahap I dilakukan pengumpulan panel data sekunder, pengelolaan data awal, estimasi volume penggunaan air tanaman (CWU) dan estimasi produktivitas air untuk tanaman (PAT) padi, jagung dan pangan.Penelitian tahap II merupakan analisis pertumbuhan total faktor produktivitas air untuk tanaman (TFPAT) menggunakan model frontier non parametrik Data envelopment analysis- Malmquist index (DEA-MI-PAT) faktor tunggal dan banyak faktor. Penelitian tahap III merupakan analisis TFPAT menggunakan model frontier parametrik Stochastic frontier analysis – Malmquist index (SFA-MI-PAT) faktor tunggal dan multi faktor. Pada penelitian tahap IV dilakukan analisis pengaruh faktor eksternal terhadap efisiensi menggunakan model frontier parametrik efisiensi efek (SFA-MI-PAT-TE). Kegiatan selanjutnya adalah merumuskan rekomendasi melalui perbandingan pertumbuhan indeks TFPAT non parametrik, parametrik, faktor tunggal dan banyak faktor, Produktivitas air untuk tanaman padi (PATPadi) secara fisik rata-rata sebesar 0.459 kg beras/m3 untuk data non parametrik dan 0.441 kg beras/m3 untuk data parametrik. Produktivitas air untuk tanaman jagung (PATJagung) secara fisik rata-rata 0.792 kg pipilan/m3 untuk data non parametrik dan 0.787 kg pipilan/m3 untuk data parametrik. Produktivitas air untuk tanaman pangan (PATPangan) merupakan gabungan PATPadi dan PATJagung rata-rata sebesar 0.458 kg beras/m3 untuk data non parametrik dan 0.452 kg beras/m3 untuk data parametrik. Rata-rata nilai produktivitas air untuk tanaman secara fisik tertinggi bukan berasal dari produsen tertinggi. Tidak terdapat perbedaan signifikan antara nilai PAT non parametrik dan parametrik. Model frontier non parametrik pengukuran total faktor produktivitas air untuk tanaman pangan Data envelopment analysis – Malmquist index faktor tunggal untuk tanaman padi (model DEA-MI-PAT-FT-PD) dan tanaman jagung (model DEA-MI-PAT-FT- JG) merupakan versi model satu masukan-satu keluaran (SISO). Model untuk tanaman pangan terdiri dari tiga versi yaitu versi Single input-single output (model DEA-MI-PAT-FT- PGN-SIS), versi Multiple inputs-single output (model DEA-MI-PAT-FT-PGN- MIS) dan versi Multiple inputs-multiple outputs (model DEA-MI-PAT-FT-PGN-MIM). Model frontier non parametrik pengukuran total faktor produktivitas air untuk tanaman pangan Data envelopment analysis – Malmquist index banyak faktor untuk tanaman padi (Model DEA- MI-PAT-BFR-PD) dan untuk tanaman jagung (model DEA-MI-PAT-BFR-JG) merupakan versi multiple inputs-single output (MISO). Model untuk tanaman pangan dibangun tiga versi yaitu versi MISO (model DEA-MI-PAT-BFR-PGN-MIS), versi Multiple inputs- multiple outputs (model DEA-MI-PAT-BFR-PGN-MIM) dan versi Multiple inputs-multiple outputs pengembangan (model DEA-MI-PAT-BFR-PGN-MIM-1). Berdasarkan model frontier non parametrik faktor tunggal (Model DEA-MI-PAT-FT), rata-rata indeks total faktor produktivitas air untuk tanaman padi (TFPATPadi) dan indeks TFPATJagung sebesar 1,017, indeks TFPATPangan sebesar 1.014. Selama periode 2000- 2015, terjadi penurunan indeks TFPATPadi sebesar 37,38%, akibat peningkatan EFCPadi sebesar 0,69% dan penurunan TECPadi sebesar 37,81%. Terjadi peningkatan indeks TFPATJagung sebesar 5,01% akibat penurunan indeks EFCJagung sebesar 14,89% dan peningkatan indeks TECJagung sebesar 23,38%. Terjadi penurunan indeks TFPATPangan sebesar 16,43% akibat penurunan indeks EFCPangan sebesar 3,17% dan penurunan indeks TECPangan sebesar 13,40%. Berdasarkan model frontier non parametrik banyak faktor (Model DEA-MI-PAT- BFR), rata-rata indeks total faktor produktivitas air untuk tanaman padi (TFPATPadi) sebesar 0,963; indeks TFPATJagung sebesar 0,960 dan indeks TFPATPangan sebesar 0,966. Selama periode 2000-2015, terjadi penurunan indeks TFPATPadi sebesar 35,47%, akibat penurunan EFCPadi sebesar 2,58% dan penurunan TECPadi sebesar 33,77%. Terjadi peningkatan indeks TFPATJagung sebesar 8,11% akibat peningkatan indeks EFCJagung sebesar 16,65% dan penurunan indeks TECJagung sebesar 7,51%. Terjadi penurunan indeks TFPATPangan sebesar 15,36% akibat peningkatan indeks EFCPangan sebesar 2,54% dan penurunan indeks TECPangan sebesar 15,95%. Model frontier parametrik pengukuran total faktor produktivitas air untuk tanaman Stochastic frontier analysis – Malmquist index faktor tunggal dan banyak faktor (model SFA-MI-PAT-FT dan model SFA-MI-PAT-BFR) dikonstruksi berbasis fungsi produksi Cobb-Douglas (CD) dan fungsi produksi Translog (TRS). Pada model untuk tanaman pangan dilakukan pengembangan variabel masukan untuk membentuk model pangan pengembangan (pangan-1). Pada model banyak faktor (BFR) dikembangkan tiga varian model berdasarkan spesifikasi variabel masukan yaitu varian biasa (BS), varian rasio (RT) dan varian pembobotan rasio (WT). Model-model tersebut didesain dengan mempertimbangkan ketersediaan data variabel masukan dan variabel keluaran spesifik wilayah semi-arid tropis seperti wilayah Timor Barat. Model-model frontier parametrik dibangun dan diseleksi untuk mendapatkan model terbaik untuk tiap jenis tanaman. Model SFA-MI-PAT-FT terbaik untuk tanaman padi adalah model SFA-MI-PAT-FT- PD berbasis fungsi produksi Translog dengan asumsi efisiensi berdistribusi half normal dan time invariant. Model SFA-MI-PAT-FT terbaik untuk tanaman jagung adalah model SFA-MI-PAT-FT-JG berdasarkan fungsi produksi Translog dengan asumsi distribusi efisiensi truncated normal dan time invariant. Model SFA-MI-PAT-FT terbaik untuk tanaman pangan adalah model SFA-MI-PAT-FT-PGN-1 berdasarkan fungsi produksi Translog dengan asumsi distribusi efisiensi truncated normal dan time invariant. Model SFA-MI-PAT-BFR terbaik untuk tanaman padi adalah model SFA-MI-PAT- BFR-PD-WT berbasis fungsi produksi Translog dengan asumsi efisiensi truncated normal dan time varying. Model SFA-MI-PAT-BFR terbaik untuk tanaman jagung adalah model SFA-MI-PAT-BFR-JG-WT berbasis fungsi produksi Cobb-Douglas (CD) varian pembobotan ratio dengan asumsi efisiensi truncated normal dan time invariant. Model SFA-MI-PAT-BFR terbaik untuk tanaman pangan adalah model SFA-MI-PAT-BFR-PGN- 1-WT berbasis fungsi produksi Translog dengan asumsi efisiensi half normal dan time invariant. Berdasarkan model SFA-MI-PAT-FT-PD, indeks TFPATPadi rata-rata sebesar 1,002 yang dipengaruhi oleh indeks efisiensi (EFCPadi) sebesar 1,000 dan indeks teknologi produksi (TECPadi) sebesar 1,002. Berdasarkan model SFA-MI-PAT-BFR-JG-WT, pertumbuhan indeks TFPATJagung rata-rata sebesar 0,987 dengan rata-rata indeks EFCJagung dan indeks TECJagung masing-masing sebesar 0,991 dan 0,996. Berdasarkan model SFA-MI-PAT-BFR-PGN-1-WT, rata-rata indeks TFPATPangan sebesar 1,013 dengan komponen rata-rata indeks EFCPangan sebesar 1,000 dan indeks TECPangan sebesar 1,013.Berdasarkan model SFA-MI-PAT-BFR-PD-WT, rata-rata indeks TFPATPadi sebesar 1,002 yang dipengaruhi oleh rata-rata indeks EFCPadi sebesar 1,000 dan rata-rata indeks TECPadi sebesar 1,002. Pada model frontier parametrik berasumsi time varying ini, dapat diidentifikasi peningkatan indeks TFPATPadi sebesar 5,56% yang disebabkan oleh penurunan indeks EFCPadi sebesar 0,01% dan peningkatan indeks TECPadi sebesar 5,56%. Berdasarkan model SFA-MI-PAT-BFR-JG-WT, rata-rata indeks TFPATJagung sebesar 1,010 dengan komponen rata-rata indeks EFCJagung sebesar 1,000 dan indeks TECJagung sebesar 1,010. Berdasarkan model SFA-MI-PAT-BFR-PGN-1-WT, rata-rata indeks TFPATPangan sebesar 0,920. Rata-rata indeks EFCPangan sebesar 1,000 dan indeks TECPangan sebesar 0,921. Model frontier parametrik efisiensi efek Stochastic frontier analysis – Malmquist index dibangun untuk analisis pengaruh faktor lingkungan, faktor sosial dan faktor ekonomi terhadap efisiensi penggunaan air tanaman padi, jagung dan pangan. Model dibangun berbasis fungsi produksi CD dan fungsi produksi TRS dengan asumsi distribusi efisiensi half normal dan truncated normal. Model dibangun berdasarkan faktor tunggal dan banyak faktor (model SFA-MI-PAT-FT-TE dan model SFA-MI-PAT-BFR-TE). Model SFA-MI-PAT-FT-TE-PD terbaik adalah model SFA-MI-PAT-FT-TE-PD berbasis fungsi produksi TRS dengan asumsi distribusi efisiensi half normal. Model SFA- MI-PAT-FT-TE-JG terbaik adalah model berbasis fungsi produksi TRS dengan asumsi distribusi efisiensi truncated normal. Model SFA-MI-PAT-FT-TE-PGN terbaik adalah model SFA-MI-PAT-FT-TE-PGN-1 berbasis fungsi produksi TRS dengan asumsi distribusi efisiensi half normal. Model SFA-MI-PAT-BFR-TE-PD-WT berbasis fungsi produksi CD dengan asumsi distribusi efisiensi half normal. Model SFA-MI-PAT-BFR-TE-JG-RT berbasis fungsi produksi CD dengan asumsi distribusi efisiensi truncated normal. Model SFA-MI-PAT-BFR-TE-PGN-WT berbasis fungsi produksi TRS dengan asumsi distribusi efisiensi half normal. Berdasarkan model SFA-MI-PAT-FT-TE-PD terbaik; faktor sosial dan faktor ekonomi berpengaruh nyata terhadap efisiensi penggunaan air tanaman padi. Berdasarkan model SFA-MI-PAT-FT-TE-JG terbaik; faktor lingkungan, faktor sosial dan faktor ekonomi berpengaruh nyata terhadap efisiensi penggunaan air tanaman jagung. Berdasarkan model SFA-MI-PAT-FT-TE-PGN-1 terbaik, faktor sosial dan faktor ekonomi berpengaruh nyata terhadap efisiensi penggunaan air tanaman pangan faktor tunggal parametrik. Berdasarkan model SFA-MI-PAT-BFR-TE-PD-WT terbaik; faktor lingkungan, faktor sosial dan faktor ekonomi berpengaruh nyata terhadap efisiensi penggunaan air tanaman padi. Berdasarkan model SFA-MI-PAT-BFR-TE-JG-RT terbaik; faktor lingkungan, faktor sosial dan faktor ekonomi berpengaruh nyata terhadap efisiensi penggunaan air tanaman jagung. Berdasarkan model SFA-MI-PAT-BFR-TE-PGN-WT terbaik, faktor ekonomi berpengaruh nyata terhadap efisiensi penggunaan air tanaman pangan. Pertumbuhan indeks TFPAT berbeda berdasarkan model pengukuran dan dekomposisi. Pertumbuhan indeks TFPATPadi non parametrik dan parametrik faktor tunggal lebih tinggi dibanding indeks TFPATPadi non parametrik dan parametrik banyak faktor. Pertumbuhan indeks TFPATPadi dan TECPadi non parametrik faktor tunggal memiliki indeks tertinggi (1,017 dan 1,027), sedangkan indeks TFPATPadi dan TECPadi non parametrik banyak faktor memiliki indeks terendah (0,963 dan 0,972). Pertumbuhan indeks EFCPadi relatif sama dan tinggi berkisar antara 0,990 sampai 1,000. Pertumbuhan indeks TFPATPadi lebih dipengaruhi oleh pertumbuhan indeks TECPadi. Pertumbuhan indeks TFPATJagung dan TECJagung parametrik faktor tunggal memiliki pertumbuhan indeks tertinggi (1,017 dan 1,027), sedangkan TFPATJagung dan TECJagung non parametrik banyak faktor memiliki pertumbuhan indeks terendah (0,960 dan 0,953). Pertumbuhan indeks EFCJagung relatif sama dan tinggi berkisar antara 0,990 sampai 1,007. Pertumbuhan indeks TECJagung lebih mempengaruhi pertumbuhan indeks TFPATJagung. Kabupaten Belu memiliki indeks TFPATJagung tertinggi sebesar 0,997 dengan indeks EFC sebesar 1,003 dan indeks TEC sebesar 0,994. Pertumbuhan indeks TECJagung lebih mempengaruhi pertumbuhan indeks TFPATJagung.Pada pertumbuhan indeks TFPATPangan; tiga indeks TFPATPangan non parametrik faktor tunggal memiliki indeks pertumbuhan tertinggi (1,014), sedangkan indeks TFPATPangan parametrik banyak faktor memiliki indeks terendah (0,920). Pertumbuhan indeks EFCPangan relatif seragam dan tinggi. Pertumbuhan indeks EFCPangan terendah (0,986) merupakan indeks non parametrik faktor tunggal SISO. Pertumbuhan indeks TECPangan non parametrik faktor tunggal SISO memiliki indeks tertinggi (1,028) sedangkan indeks TECPangan parametrik banyak faktor memiliki indeks terendah (0,921). Pertumbuhan indeks TECPangan lebih mempengaruhi pertumbuhan indeks TFPATPangan. Kabupaten Belu memiliki indeks TFPATPadi tertinggi sebesar 1,026 dengan indeks EFC sebesar 1,006 dan indeks TEC sebesar 1,020. Kabupaten Belu memiliki indeks TFPATJagung tertinggi sebesar 0,997 dengan indeks EFC sebesar 1,003 dan indeks TEC sebesar 0,994. Tingginya indeks TFPATPadi dan TFPATJagung disebabkan oleh faktor lingkungan, faktor budaya dan kearifan lokal petani di Kabupaten Belu. Kota Kupang memiliki indeks TFPATPangan tertinggi sebesar 1,016 dengan indeks EFC sebesar 1,000 dan indeks TEC sebesar 1,016. Petani Kota Kupang memiliki kualitas sumberdaya manusia, akses terhadap faktor produksi, infrastruktur, kemampuan ekonomi dan akses pasar yang relative lebih baik dibandingkan kabupaten lainnya. Direkomendasikan, berdasarkan indeks EFCPadi dan indeks EFCJagung terendah, PATPadi dan PATJagung dapat ditingkatkan 1% tanpa penambahan CWUPadi dan CWUJagung . Berdasarkan indeks EFCPangan terendah, PATPangan dapat ditingkatkan 1,40% tanpa perlu panambahan CWUPangan. Peningkatan produktivitas air untuk tanaman (PAT) dilakukan dengan meningkatkan TFPAT, komponen indeks teknologi produksi (TEC) perlu mendapatkan prioritas. Indeks efisiensi (EFC) dipertahankan dan ditingkatkan dengan memperhatikan faktor lingkungan, faktor sosial dan faktor ekonomi. Selanjutnya, peningkatan teknologi produksi (TEC) perlu memperhatikan aspek keberlanjutan berbasis kearifan lokal dan pemanfaatan input organik. Perlu dilakukan analisis pertumbuhan TFPAT pada wilayah lain di Indonesia sehingga didapatkan informasi ilmiah yang lebih lengkap. Sebaiknya menggunakan panel data harga berdasarkan harga konstan untuk meminimasi pengaruh inflasi. Perlu menggunakan variabel bebas dan variabel eksternal yang lebih banyak pada model banyak faktor. Perlu dilakukan analisis pertumbuhan produktivitas air untuk tanaman pertanian lainnya
English Abstract
The West Timor region is part of the province of East Nusa Tenggara (NTT), with a semi-arid climate, most of the population works in the food crop agriculture sub-sector. The main food crops in West Timor are corn and paddy with a traditional cultivation system for consumption. Even though the production has increased, it is still unable to meet current and future needs. Increasing food production is highly recommended through increasing crop water productivity. The unavailability of research results on crop water productivity in West Timor and no research related to the growth of total water productivity factors are the motivated of this research. This study aims to determine the physical value of food crops water productivity. Designing frontier models and explaining the growth and decomposition of crops water total factors productivity. Build parametric frontier models of efficiency effect and explain the effect of non-stochastic external factors on the efficiency of crop water utilization and formulate recommendations through the comparison of the total growth of water productivity factors. This study applied secondary data of climate and non-climatic during the year of 2000-2015. This research was carried out in four stages, namely stage I, including collecting secondary panel data, initial data processing, estimating crops water use (CWU) subsequently estimating crop water productivity (PAT) of paddy, corn and food. Phase II research was an analysis of crops water total factor productivity (TFPAT) using non- parametric frontier model of Data envelopment analysis-Malmquist index (DEA-MI-PAT) single-factor and multi-factor. The third stage of the research was a TFPAT analysis using the frontier parametric model of Stochastic frontier analysis - Malmquist index (SFA-MI- PAT) single factor and multi factors. In stage IV research, an analysis of the influence of stochastic external factors on efficiency was carried out using the efficiency effect parametric frontier model (SFA-MI-PAT-TE). The next activity was to formulate recommendations through the comparison of the TFPAT index growth of non-parametric, parametric, single factor and multiple factors, The average physical value of paddy water productivity (PATPaddy) was 0.459 kg of rice / m3 for non-parametric data and 0.441 kg of rice / m3 for parametric data. The physical value of corn water productivity (PATCorn) was 0.792 kg shelled / m3 for non-parametric data and 0.787 kg shelled / m3 for parametric data. In terms of food water productivity (PATFood) that was a combination of PATPaddy and PATCorn in average of 0.458 kg of rice / m3 for non- parametric data and 0.452 kg of rice / m3 for parametric data. The highest average value of crop water productivity was not from the highest producer. There was no significant difference between the non-parametric and parametric PAT values. The non-parametric frontier model of crops water total factor productivity measurement and decomposition Data envelopment analysis - Malmquist index Single factor for paddy (DEA-MI-PAT-FT-PD model) and corn (DEA-MI-PAT-FT-JG model) was the single input-single output (SISO) version of the model. The model for food crops consists of three versions, namely the Single input-single output version (DEA-MI-PAT-FT- PGN-SIS model), the Multiple inputs-single output version (DEA-MI-PAT-FT-PGN-MIS model) and the Multiple inputs-multiple outputs version (DEA-MI-PAT-FT-PGN-MIM model). The non-parametric frontier model for measuring and decomposition of crops water total factor productivity Data envelopment analysis - Malmquist index Multi-factor for paddy (DEA-MI-PAT-BFR-PD Model) and for corn (DEA-MI-PAT-BFR-JG model) was a version of multiple inputs-single output (MISO). The model for food crops was built in three versions, namely the MISO version (DEA-MI-PAT-BFR-PGN-MIS model), the multiple inputs-multiple DISSERTATION. Jonathan E. Koehuan, The Study Analysis of Staple Food Water Productivity Growth in the West Timor Region. Promotor : Prof. Dr. Ir. Bambang Suharto, MS., Co-Promotor: Dr. Ir. Gunomo Djoyowasito, MS.,Co- Promotor : Prof. Dr. Ir. Wignyanto, MS outputs version (DEA-MI-PAT-BFR-PGN-MIM model) and the multiple inputs-multiple outputs extended version (DEA-MI-PAT-BFR-PGN-MIM-1 model). Based on the single factor non-parametric frontier model (DEA-MI-PAT-FT Model), the average crop water total factor productivity index for paddy (TFPATPaddy) and TFPATCorn index was 1.017, the TFPATFood index was 1.014. During the 2000-2015 periods, there was a decrease in the TFPATPaddy index by 37.38%, due to an increase in EFCPaddy by 0.69% and a decrease in TECPaddy by 37.81%. There was an increase in the TFPATCorn index by 5.01% due to a decrease in the EFCCorn index by 14.89% and an increase in the TECCorn index by 23.38%. There was a decrease in the TFPATFood index by 16.43% due to a decrease in the EFCFood index by 3.17% and a decrease in the TECFood index by 13.40%. Based on the multi-factor non-parametric frontier model (DEA-MI-PAT-BFR Model), the average crop water total factor productivity index for paddy (TFPATPaddy) was 0.963; the TFPATCorn index was 0.960 and the TFPATFood index was 0.966. During the 2000- 2015 periods, there was a decrease in the TFPATPaddy index by 35.47%, due to a decrease in EFCPaddy by 2.58% and a decrease in TECPaddy by 33.77%. There was an increase in the TFPATCorn index by 8.11% due to an increase in the EFCCorn index by 16.65% and a decrease in the TECCorn index by 7.51%. There was a decrease in the TFPATFood index by 15.36% due to an increase in the EFCFood index by 2.54% and a decrease in the TECFood index by 15.95%. Parametric frontier models for measuring and decomposition of crop water total factor productivity Stochastic frontier analysis - Malmquist indexes single and multi-factor (SFA-MI-PAT-FT and SFA-MI-PAT-BFR models) were constructed based on the Cobb- Douglas (CD) production function and the Translog production function (TRS). In the model for food, input variables were extended to form an extended food model (food-1). In the multi-factor model (BFR), three model variants were developed based on the input variable specifications, namely the ordinary variant (BS), the ratio variant (RT) and the ratio-weighted variant (WT). These models were designed by considering the availability of data on input and output variables specific to semi-arid tropical regions such as West Timor. Parametric frontier models were constructed and selected to obtain the best model for each type of crop. The best SFA-MI-PAT-FT model for paddy was the SFA-MI-PAT-FT-PD model based on the Translog production function assuming the efficiency distribution was half normal and time invariant. The best SFA-MI-PAT-FT model for corn was the SFA-MI-PAT- FT-JG model based on the Translog production function assuming truncated normal and time invariant efficiency distribution. The best SFA-MI-PAT-FT model for food was the SFA-MI-PAT-FT-PGN-1 model based on the Translog production function assuming truncated normal and time invariant efficiency distribution. The best SFA-MI-PAT-BFR model for paddy was the SFA-MI-PAT-BFR-PD-WT model based on the Translog production function assuming normal truncated efficiency distribution and time varying. The best SFA-MI-PAT-BFR model for corn was the SFA-MI- PAT-BFR-JG-WT model based on the Cobb-Douglas (CD) production function variant weighted ratio assuming normal truncated efficiency distribution and time invariant. The best SFA-MI-PAT-BFR model for food was the SFA-MI-PAT-BFR-PGN-1-WT model based on the Translog production function assuming half normal and time invariant efficiency distribution. Based on the SFA-MI-PAT-FT-PD model, the average TFPATPaddy index was 1.002 which was influenced by the EFCPaddy index of 1,000 and TECPaddy index of 1.002. Based on the SFA-MI-PAT-BFR-JG-WT model, the average TFPATCorn index growth was 0.987 with the average EFCCorn index and TECCorn index of 0.991 and 0.996, respectively. Based on the SFA-MI-PAT-BFR-PGN-1-WT model, the average TFPATFood index was 1.013 with an average component of the EFCFood index of 1,000 and the TECFood index of 1.013. Based on the SFA-MI-PAT-BFR-PD-WT model, the average TFPATPaddy index was 1.002 which was influenced by the average EFCPaddy index of 1,000 and the average TECPaddy index of 1.002. In the parametric frontier model assuming this time varying, it can be identified that the TFPATPaddy index increased by 5.56% due to a decrease in the EFCPaddy index by 0.01% and an increase in the TECPaddy index by 5.56%. Based on the SFA-MI-PAT-BFR-JG-WT model, the average TFPATCorn index was 1.010, with the EFCCorn average component being 1,000 and the TECCorn index 1.010. Based on the SFA- MI-PAT-BFR-PGN-1-WT model, the average TFPATFood index was 0.920. The average EFCFood index was 1,000 and the TECFood index was 0.921. Parametric frontier model of efficiency effect of Stochastic frontier analysis - Malmquist index was built to analyze the influence of environmental, social and economic factors on the efficiency of water use in paddy, corn and food crops. The model was built based on the CD production function and the TRS production function with the assumption that the efficiency distribution was half normal and truncated normal. The model was built based on a single factor and multiple factors (the SFA-MI-PAT-FT-TE model and the SFA-MI-PAT-BFR-TE model). Regarding the selection of the single-factor models, the selected SFA-MI-PAT-FT- TE-PD model was based on the TRS production function assuming a half normal efficiency distribution. The selected SFA-MI-PAT-FT-TE-JG model was the TRS production function based model assuming normal truncated efficiency distribution. The selected SFA-MI-PAT-FT-TE-PGN-1 model was based on the TRS production function assuming a half normal efficiency distribution. Regarding the selection of the multi-factor models, the selected SFA-MI-PAT-BFR-TE-PD-WT model was based on the CD production function assuming a half normal efficiency distribution. The selected SFA-MI- PAT-BFR-TE-JG-RT model was based on the CD production function assuming a normal truncated efficiency distribution. The selected SFA-MI-PAT-BFR-TE-PGN-WT model was based on the TRS production function assuming a half normal efficiency distribution. Based on the selected SFA-MI-PAT-FT-TE-PD model; Social and economic factors significantly influence the efficiency of water use of paddy. Based on the selected SFA-MI- PAT-FT-TE-JG model; environmental factors, social factors and economic factors significantly influence the efficiency of water use of corn. Based on the selected SFA-MI- PAT-FT-TE-PGN-1 model, social and economic factors have a significant effect on the efficiency food crop water use. Based on the selected SFA-MI-PAT-BFR-TE-PD-WT model; environmental factors, social factors and economic factors significantly influence the efficiency of water use of paddy. Based on the selected SFA-MI-PAT-BFR-TE-JG-RT model; environmental factors, social factors and economic factors significantly influence the efficiency of water use of corn. Based on the selected SFA-MI-PAT-BFR-TE-PGN-WT model, economic factors significantly influence the efficiency of food crop water use. The TFPAT index growth differs based on the measurement and decomposition model. The growth of the TFPATPaddy index of non-parametric and parametric single factor was higher than the TFPATPaddy index for non-parametric and parametric multi-factor. The growth of TFPATPaddy and TECPaddy indexes of non-parametric single factor had the highest (1.017 and 1.027), while the TFPATPaddy and TECPaddy non-parametric multi-factor indexes had the lowest (0.963 and 0.972). The EFCPaddy index growth was relatively constant and hight ranges from 0.990 to 1,000. The TFPATPaddy index growth was more influenced by the TECPaddy index growth.Growth index of TFPATCorn and TECCorn single factor parametric corn had the highest growth index (1.017 and 1.027), compared to non- parametric multi-factor that had the lowest growth indexes (0.960 and 0.953). The EFCCorn index growth was relatively constant and haight ranges from 0.990 to 1.007. The growth of the TECCorn index has more influence on the growth of the TFPATCorn index. In terms of the TFPATFood index growth; the three TFPATFood indexes of single- factor non-parametric had the highest growth index (1.014), while the TFPATFood index of multi-factor parametric had the lowest index (0.920). The EFCFood index growth was relatively uniform and high. The lowest growth of the EFCFood index (0.986) was the non- parametric single factor SISO index. The growth of the TECFood index of single-factor non- parametric SISO, had the highest index (1.028) while the TECFood index for multi-factor parametric had the lowest index (0.921). The growth of the TECFood index has more influence on the growth of the TFPATFood index.Belu district has the highest TFPATPaddy index of 1.026 with the EFCPaddy index of 1.006 and the TECPaddy index of 1.020. Belu district has the highest TFPATCorn index of 0.997 with an EFCCorn index of 1.003 and a TECCorn index of 0.994. The high TFPATPaddy and TFPATCorn indices were caused by environmental factors, cultural factors and local wisdom of farmers in Belu district. Kupang City has the highest TFPATFood index of 1.016 with the EFCFood index of 1,000 and the TECFood index of 1.016. Farmers in Kupang City have relatively better quality human resources, access to production factors, infrastructure, economic capacity and market access than other districts. It was recommended that based on the EFCPaddy index and the lowest EFCCorn index, PATPaddy and PATCorn could be increased by 1% without the addition of CWUPaddy and CWUCorn. Based on the lowest EFCFood index, PATFood could be increased by 1.40% without the need for additional CWUFood. The increasing of crop water productivity (PAT) was done by the increasing of the TFPAT with the components TEC need to get more priority. The EFC should be maintained and enhanced by taking into account environmental factors, social factors and economic factors. Furthermore, improving TEC should be targeted sustainability that based on local wisdom and application of organic inputs. It was necessary to analyze TFPAT in other regions in Indonesia so that more complete scientific information was obtained. We recommend using a price data panel based on constant prices to minimize the effect of inflation. It was advised to use more independent variables and external variables in the multi-factor model. It was necessary to analyze the growth of water productivity for other agricultural crops
| Item Type: | Thesis (Doktor) |
|---|---|
| Identification Number: | 0620100001 |
| Uncontrolled Keywords: | Produktivitas air untuk tanaman, pangan, Timor Barat, efisiensi, teknologi produksi,Crop water productivity, food, West Timor, efficiency, production technology |
| Subjects: | 300 Social sciences > 338 Production > 338.1 Agriculture |
| Divisions: | S2/S3 > Doktor Teknologi Industri Pertanian, Fakultas Teknologi Pertanian |
| Depositing User: | soegeng sugeng |
| Date Deposited: | 20 Jul 2022 03:13 |
| Last Modified: | 08 Oct 2024 02:50 |
| URI: | http://repository.ub.ac.id/id/eprint/192395 |
![[thumbnail of Jonathan E. Koehuan.pdf]](http://repository.ub.ac.id/style/images/fileicons/text.png) |
Text
Jonathan E. Koehuan.pdf Download (6MB) |
Actions (login required)
 |
View Item |