ABSTRAKFokus penelitian ini adalah pembuatan sistem alat ukur kadar gas CH 4 dan pengukuran kadar gas CH 4 di lahan gambut. Sistem alat ukur terdiri dari rangkaian catu daya, sensor TGS2611, voltage follower, mikrokontoler ATMega8535, LCD karakter 16x2 dan komputer. Sensor TGS2611 dikalibrasi dengan gas metana yang dihasilkan dari reaktor biogas, sehingga diperoleh proporsi konsentrasi gas metana dan tegangan. Mikrokontroler ATMega8535 merupakan perangkat yang mengendalikan semua bagian dalam sistem alat ukur ini. Basic Compiler merupakan perangkat lunak yang bertanggung jawab untuk ambil data sensor, menghitung persamaan karakteristik, mengirim data ke LCD 16 x 2. Untuk mengartar muka antara sistem alat ukur dengan komputer menggunakan bahasa pemrograman Delphi.7. Hasil pengukuran dapat ditunjukkan secara terus menerus, waktu nyata dan pencatatan otomatis. Pengukuran kadar gas CH 4 pada lahan gambut menggunakan chamber berukuran 60 x 50 x 40 cm. Chamber berfungsi untuk memerangkap emisi gas CH 4 pada lahan gambut. Pengukuran dilakukan selama 2 jam menghasilkan perubahan konsentrasi gas CH 4 dari rentang 237 ppm sampai 295 ppm. Data hasil pengukuran disimpan dalam file dengan format *.xlsx. Kata Kunci:Chamber; Lahan gambut; Metana; Mikrokontroler ATMega8535; Sensor TGS2611; ABSTRACTThe research are focused on fabrication of measuring instrument for measure methane gas concentration on peatland. Measuring instrument consists of power supply unit, TGS2611 metahne gas sensor, voltage follower, ATMega8535 microcontroller, 16 x 2 LCD character and personal computer. TGS2611 is calibrated with methane from biogas present proportion between gas concentration and voltage. ATMega8535 module is a device to manage all part in measuring instrument. The software that responsible to take sensor data, calculating characteristic equation and sending data to 16 x 2 LCD character are Basic Compiler. To interface between measuring instrument and personal computer is maintained by Delph.7. The result of measuremnet can showed on 16 x 2 LCD caharacter and PC monitor continously, real time and recorded automatically. Closed-Chamber Measurement with dimension 60 x 50 x 40 cm 3 is used to trap methane on peatland. Mesurement during 2 hour on peatland produce 237 to 295 ppm.
Machine vision berbasis jaringan saraf tiruan dan pemrosesan gambar digital merupakan metode alternatif yang dapat dilakukan untuk mengidentifikasi dan mengevaluasi keragaman varietas padi. Berbeda dengan metode pengamatan langsung yang memiliki tingkat subjektivitas tinggi dan metode kimiawi (PCR) yang bersifat destruktif dan mahal, machine vision berbasis jaringan saraf tiruan menawarkan sistem identifikasi dan evaluasi secara cepat, praktis, murah, akurat, serta bersifat non-destruktif. Paper ini membahas machine vision berbasis jaringan saraf tiruan sebagai teknologi alternatif untuk identifikasi varietas padi rawa Kalimantan Selatan berdasarkan ciri morfologinya, yaitu area, perimeter, major axis, minor axis, circularity, aspect ratio, roundness, dan feret untuk setiap sampel benih padi. Dalam paper ini, sistem identifikasi varietas benih padi menggunakan jaringan saraf radial basis probabilistic dengan optimalisasi bobot hidden center menggunakan algoritme orthogonal least square. Dari proses learning dihasilkan performa pelatihan sebesar 88.32% dan performa pengujian sebesar 88.21% dengan tingkat keberhasilan pada proses pelatihan dari masing-masing varietas bayar papuyu, bayar putih, benih kuning, benih putih, ketan, siam gadis, siam unus, dan karan dukuh masing-masing sebesar 100.00%, 92.59%, 88.89%, 92.59%, 92.59%, 81.48%, 100.00%, dan 100.00%. Untuk proses pengujian, tingkat keberhasilan masing-masing varietas ialah 100.00%, 87.50%, 88.89%, 100.00%, 88.89%, 88.89%, 100.00%, dan 100.00%.<br /><br />Kata Kunci: benih padi, machine vision, morfologi, RBP-OLS
Poverty is a condition of living in an inability to meet the minimum needs of life or basic needs. In Indonesia, poverty is one of the main problems that still need an optimal solution. Several government programs to address the problem of poverty have been carried out, but not infrequently the implementation is not right on target. The importance of this assistance is expected to improve the welfare of the community so it is very unfortunate if the assistance has not been right on target. This study aims to determine the status of poverty in Hulu Sungai Tengah Regency. By observing a problem above, it can be necessary to use a grouping method in determining poverty status. so that in this study using the cluster method, namely K-Means in clustering population data. Based on the results of data analysis using 353 head of family in the population data of HST Regency, it can be concluded that there are three poverty status clusters, namely low-level poverty (cluster 3) with a total of 130 head of family, medium-level poverty (cluster 2) with a total of 130 head of family. 111 head of family, and high poverty level (cluster 1) with a total of 112 head of family.
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