Determining the location of the arsenal in an effort to increase the carrying capacity of marine forces in the critical area of the North Natuna sea

Strategic environmental dynamics in the North Natuna Sea area raises potential threat spots to the territory of the Republic of Indonesia where the Indonesian Navy needs to determine a maritime security strategy where one of the things that must be prepared is the distribution of logistics in the form of ammunition and weapons through development warehouse Arsenal. Through this research, an alternative strategic location was determined as an Arsenal warehouse as a storage place for ammunition supplies used to support the KRI carrying out operational tasks. Alternative construction locations for Arsenal are Lanal Bintan, Lanal Ranai, Lanal Bangka Belitung and Lantamal IV Pontianak. Based on Perkasal No. 17 of 2008 The criteria used and the absolute requirements for determining the location are security, transportation access and supporting facilities. Data collection for this research was carried out using the method of distributing questionnaires and conducting interviews expert. The Delphi method was used in this research to determine and agree on relevant and valid criteria and sub-criteria to be researched at the next stage. Next Method Analytic Network Process (ANP) is used to determine the best alternative with pdata processing process uses Software Super Decision. Then the structure of complex cause and effect relationships is visualized using a matrix and images using the method Decision Making Trial And Evaluation Laboratory (DEMATEL). The results of this research show that the priority of the alternative Arsenal warehouse location is Lanal Bintan with a weight value of 0.536308. Security criteria and sub-criteria for being safe from enemy attacks are the most dominant criteria in determining Arsenal warehouse location decisions

Klasifikasi Inti Sawit Berdasarkan Analisis Tekstur dan Morfologi Menggunakan K-Nearest Neighborhood (KNN)

As the by product of palm oil, palm kernel contains high-quality oil. The manual inspection has low efficiency, subjective and inconsistent results due different perspectives between the buyer and the seller regarding the kernel quality. This research aims to determine the quality of palm kernel using the texture and morphological image analysis. Texture analysis performed on the kernel images separation to obtain the value of the mean, variance, skewness, kurtosis, entropy, energy, contrast, correlation, and homogeneity. Morphology analysis performed on the kernel images separation to obtain the value of the area, perimeter, metrics, and eccentricity. The classification was performed by KNearest Neighbor (KNN) method. Based on a simulation, the classification system could classify the palm kernel into the whole kernels, broken, and shells. The highest accuracy of 66.59 % was obtained by using a combination of mean and morphology when k was 1

Pengembangan dan Uji Kinerja Mesin Pemupuk Dosis Variabel pada Budidaya Padi Sawah dengan Konsep Pertanian Presisi

This paper discussed about the development of electronically controlled fertilizer applicator machine based on modified riding type paddy transplanter tractor. The machine had ability to perform variable rate of application dose using urea, phosphor, and NPK compound. The developed variable rate applicator (VRA) equipped with digital controlled metering devices so that the dose of application can be given accurately and the amount of application can be change in flexible way according to recommended dose. The machine has 4 unit of metering devices, has 8 application rows, and equipped with pneumatic diffusers. RTK-DGPS was used to monitor the position in the field. Performance test has been done for several parameters, included uniformity of air flow at each diffuser, granular fertilizer spreader pattern, and linearity of actual amount of fertilizer with respect to the commanded dose. Average rate of air flow in each diffuser was 0.0073 m3/s, with 7.23 % CV. Total working width of the machine was about 5 m. Field capacity was about 0.12 ha/hours. The results of the tests on metering dose showed that the develop VRA could spread fertilizer uniformly and gave accurate application dose. The yield result showed that uniformity of unhulled rice production was reached 74.7%

APLIKASI ARTIFICIAL NEURAL NETWORK DALAM PEMUPUKAN N, P, DAN K PADA BUDIDAYA TEBU

Data historis dosis pemupukan pada budidaya tebu dan hasil yang diperoleh (hasil tebu dan kadar gula) sangat bermanfaat untuk mengetahui dosis pemupukan yang memberikan hasil yang tinggi.  Hubungan tersebut dapat diformulasikan dengan artificial neural network. Penelitian ini bertujuan membangun model artificial neural network sehingga dapat ditentukan kebutuhan jumlah hara N, P, dan K pada target hasil tebu (yield) dan kadar gula yang diharapkan. Hasil penelitian menunjukkan bahwa model Artificial Neural Network (ANN) yang dibangun untuk memformulasikan hubungan antara jumlah hara yang dibutuhkan dengan hasil tebu dan kadar gula memiliki akurasi R2=0.93 untuk pupuk pertama N, R2=0.88 untuk pupuk pertama P, R2=0.88 untuk pupuk kedua N, dan R2=0.92 untuk pupuk kedua K. Kata kunci: dosis pupuk, hasil tebu, kadar gula, artificial neural network