OPTIMALISASI USAHATANI JAGUNG (Zea mays L.) DI KAMPUNG TUMBIT MELAYU KECAMATAN TELUK BAYUR KABUPATEN BERAU

ABSTRAKPenelitian ini bertujuan untuk mengetahui tingkat produksi optimal usahatani jagung(Zea mays L.), besarnya penerimaan optimal, serta keuntungan optimal.Penelitian ini dilakukan di Kampung Tumbit Melayu Kecamatan Teluk Bayur Kabupaten Berau.Metode pengambilan responden yang digunakan dalam penelitian ini adalah Metode Sensus. Pengambilan data dilakukan dengan cara observasi ke lokasi penelitian dan mengadakan wawancara dengan responden. Petani responden ditentukan secara Sensus sebanyak 31 (tiga puluh satu) orang yang sebelumnya dikelompokkan terlebih dahulu dalam strata berdasarkan luas lahan. Analisis data yang digunakan adalah regresi kuadratik untuk persamaan biaya dan regresi linier untuk persamaan penerimaan. Hasil penelitian menunjukkan bahwa rata-rata produksi yang dicapai responden sebanyak 2.992 kg/ha dengan keuntungan sebesar Rp 5.805.718,-/ha untuk satu kali panen. Dari hasil analisis diketahui persamaan biaya yaitu TC = dan persamaan penerimaan yaitu TR = . Jumlah produksi pada tingkat penerimaan optimal sebesar 4.057 kg. Besarnya penerimaan Rp 14.195.443,-/ha dan keuntungan optimal Rp 7.006.233,-/ha untuk satu kali musim tanam. Kata kunci : Tingkat Produksi; Penerimaan Optoimal; Keuntungan OptimalABSTRACTThis study aims to determine the optimal level of production of corn farming (Zea mays L.), the optimal amount of acceptance, and optimal profits. This research was conducted in Kampung Tumbit Melayu, Teluk Bayur District, Berau Regency.The sampling method used in this study is the Census method. Data is collected by observation to the research location and conducting interviews with respondents. Respondent farmers were determined by Census as many as 31 (thirty one) people who were previously grouped first in strata based on land area. Analysis of the data used is quadratic regression for the cost equation and linear regression for the revenue equation.The result of the research showed that the averange produc was 2.992 kg per hectare with profit as much Rp 5.805.718,- per hectare for one harvest. Than cost equition was TC = revenue equition TR = . The quantity of optimal production was 4.057 kg. The revenue was Rp 14.195.443,-and optimal profit was Rp 7.006.233,- per hectare for one harvest.Keywords: Production Level; Optimal Acceptance; Optimal Profit

ZERO COST EQUATION

In economic science, the role of the initial concept is played by zero value, which is born before the very first exchange. To detect it, tools such as an analytical model of the labor process and an analytical model of the personal consumption process are needed. Thus, the sequence of searching for the basic concept of the economy is as follows: first, we dress the labor process and the process of personal consumption in an analytical form, then, using the obtained models, we derive the equation of zero value.

Can new disruption research suggest defenses against threats and opportunities for innovators?

Purpose Under the co-direction of John Hagel, Deloitte’s Center for the Edge has been publishing important new studies of disruption with an ‘outcome-based approach to disruption.’ This research is discovering patterns that may help leaders institute defenses against threats and identify opportunities for innovators Design/methodology/approach Deloitte research is focusing on patterns of disruption that hit more than one market, but not all markets. It is examining: what are the characteristics of markets that would make them vulnerable to a particular pattern? Findings After six months of research, Deloitte has identified nine patterns that meet its outcome-based criteria. A number of the patterns are based on creating network effects that grow so quickly they become hard to compete with if the rival firm does not already have an established market position. Another set of the patterns identifies ways to fundamentally transform the value-cost equation, but without network effects. Research limitations/implications More patterns may be discerned as the research proceeds. Practical implications For example, if incumbents and innovators just think about driverless cars as the auto industry, they are never going to fully see the disruption that is coming. By contrast, by thinking about it as a mobility ecosystem, then many other key players, risks and opportunities become apparent Originality/value The patterns identified by Deloitte research may provide leaders with insights into how to defend against specific disruptions and also offer innovators inspiration for new opportunities in established markets and Blue Ocean ventures.