Judul: Tata kelola terhadap Organisme Pengganggu Tumbuhan/Organisme Pengganggu Tumbuhan Karantina (OPT/OPTK) di Balai Karantina Pertanian Kelas II Cilegon, Banten
Abstrak: Organisme Pengganggu Tumbuhan/ Organisme Pengganggu Tumbuhan Karantina (OPT/OPTK) merupakan organisme yang dapat membawa penyakit baru ke suatu wilayah dan baru bisa masuk ke suatu wilayah jika media pembawa yang masuk ke suatu wilayah tersebut tidak mendapat tata kelola dari pihak atau instansi yang bertanggung jawab. Oleh karena itu, pemerintah membuat kebijakan yang tertuang dalam Undang Undang nomor 21 tahun 2019 mengenai tindakan karantina 8P (pemeriksaan, pengasingan, pengamatan, perlakuan, penahanan, penolakan, pemusnahan dan pembebasan) yang hanya dapat dilakukan oleh Balai Karantina Pertanian dalam mencegah masuknya media pembawa penyakit baru masuk ke wilayah Indonesia. Tujuan khusus dari kegiatan magang ini mempelajari secara langsung implementasi, tata kelola, dan manajemen tindakan karantina di Balai Karantina Pertanian Kelas II Cilegon. Pelaksanaan kegiatan magang dilakukan dengan melakukan praktik langsung pada setiap kegiatan tindakan karantina, dan diskusi maupun wawancara yang dilakukan dengan petugas karantina pertanian yang bertugas. Implementasi tindakan karantina di Balai Karantina Pertanian Kelas II Cilegon sudah sesuai dengan tugas pokok dan fungsi (TUPOKSI) BKP Kelas II Cilegon untuk mencegah masuk dan tersebarnya OPT/OPTK kedalam wilayah NKRI melalui wilayah kerja BKP II Cilegon. Implementasi TUPOKSI BKP Kelas II Cilegon dilakukan melalui pemeriksaan terhadap media pembawa pada kegiatan ekspor, impor, dan antar area, kemudian pengambilan sampel, pengujian sampel, dan pemusnahan. Meskipun demikian, ada beberapa hal perlu dievaluasi yaitu teknis pengambilan sampel agar sesuai ketentuan sehingga peran karantina tumbuhan semakin baik dalam menjalankan perannya.
Keyword: inspection, management, tupoksi, the law number 19 2019, 8P

Judul: Pengawasan Titik Masuk OPT dan OPTK di Balai Karantina Pertanian Kelas II Tanjung Pinang Kepulauan Riau
Abstrak: Tindakan perkarantinaan di Indonesia diatur oleh rumusan kebijakan pemerintah yang dituangkan dalam Undang Undang Nomor 21 Tahun 2019 tentang tindakan karantina 8P termasuk pemeriksaan, pengasingan, pengamatan, perlakuan, penahanan, penolakan, pemusnahan, dan pembebasan yang dilakukan hanya oleh Balai Karantina Pertanian. Tujuan penelitian ini untuk mendapatkan informasi data hama OPT dan OPT Karantina (OPTK) yang masuk melalui pelabuhan serta mempelajari manajemen pengawasan perkarantinaan tumbuhan di Balai Karantina Pertanian Kelas 2 Tanjung Pinang, Kepulauan Riau. Penelitian dilakukan melalui kegiatan magang dengan cara praktik langsung pada setiap kegiatan tindakan karantina, diikuti diskusi maupun wawancara dengan petugas karantina pertanian yang berkaitan dengan tugas pokok dan peran Balai Karantina Pertanian. Penentuan spesies OPT karantina dipelajari melalui identifikasi morfologi serangga hasil pengambilan sampel dari pelabuhan dengan menelusuri dan mengacu pada daftar hama karantina sesuai dengan Peraturan Menteri Pertanian Nomor 31/Permentan/KR.010/7/2018. Empat spesies serangga gudang telah teridentifikasi pada sampel bahan yang masuk melewati pelabuhan, yaitu Necrobia rufipes, Oryzaephilus surinamensis, Sitophilus oryzae, dan Tribolium castaneum. Keempat spesies hama gudang ini bukan termasuk OPTK.
Keyword: identification, quarantine action, quarantine in law, storage product insect

Judul: The Effects of Variance of Interest rate to Variance of Annuity Future Values
Abstrak: Time value of money is a concept that refers to the difference of the value of money due to time difference. The value of money for present time would not be the same as the value of money in the future. The value of money for present time is called as Present Value (PV) of the money and the value of money for future time is called Future Value (FV) of the money. Determination the value of money, for present and future time, depends on the time and rate of return. The value of money is determined by several factors such as inflation, fluctuation of interest rates, and government policy in securities and taxation. Due to fluctuation of the value of money we need a FV formulation, it is useful for knowing whether an investment can be profitable or not, and this information is useful also in budget analysis. Annuity is defined as a series of payments made for a specific period. The payment, fixed or varied, can be made at the beginning or at the end of the period. Annuity paid at the beginning of the period is called annuity-due and annuity paid at the end of the period is called immediate annuity-certain. The accumulated value of the annuity after few years later is called as a final value or a future value. Burnecki et al. (2003) have discussed about the FV of a fixed-rate annuity in which payments are made according to the arithmetic or geometric series. They have also examined FV for annuities in which payments are made according to arithmetic or geometric series with random rates of interest. This paper examines FV for annuity-due in which payments are made according to arithmetic or geometric series with interest rates as a random variable, which is normal distribution ,  . Future value formula is expressed in recursive form. FV for annuity-due which payments are made according to the arithmetic or geometric series with random rates of interest is calculated by theoretical way and simulation way. The random rates of interest is denoted as k k i  i  , where k i an independent random variable; i is a constant and k  is a random variable which has normal distribution ,  . By using the determined parameters, a sequence of random rates of interest are generated for theoretical calculation. Meanwhile for the simulation, the random rates of interest is generated 1000 times for the simulation. The generated data give mean value, variance, and standard deviation. Moreover, error of mean value, variance, and standard deviation from the theoretical and simulation results are calculated. Error calculation uses Symmetric Mean Absolute Percentage Error (SMAPE). The smaller the value of SMAPE is the more accurate the simulation. The interest rate variances are varied from 0.000036 to 0.0001 to study the relationship between variance of rates of interest and variance of future value. The theoretical and simulation results show that when the variance of random rates of interest increases, then the variance of FV increases linearly. FV of the annuity-due in
Keyword: