40 research outputs found
Disinfection Performance Against Salmonella Typhi in Water by Radio Frequency Inductive Couple Plasma System
The disinfection performance of the radio frequency inductively coupled plasma (RFICP) system against Salmonella Typhi in water was examined using continuous flow experiments. The evaluation was based on disinfection efficiency, death rate constant, disinfection yield, and energy consumption. For all experiments the electromagnetic flux generated in the plasma reactor varied from 4 to 6 W/cm2. The disinfection efficiency and death rate constant of Salmonella Typhi decreased with the increase of the initial number of Salmonella Typhi bacteria. The disinfection yield increased from 784 to 1889 CFU/KWh and the energy consumption decreased from 0.28 to 0.07 KWh/L with the flowrate increasing from 5 to 20 mL/minute. The flowrate is an important parameter in predicting disinfection performance against pathogenic bacteria in water to design drinking water treatment plants
Keterampilan Kerja Ilmiah pada Materi Titrasi Asam Basa Menggunakan Model Pembelajaran Inkuiri Terbimbing
The aims of the study were to describe the profile of scientific work skills of students before and after the guided inquiry learning model is applied to the material acid-base titration as well as different scientific working skills of students XI IPA SMA Negeri 3 Sintang students before and after the guided inquiry learning model is applied to the material acid-base titration. Pre-experiment with one grup pretest-posttest was used as study method. Students of XI IPA 1 academic year 2015/2016 participated in the study were selected by purposive sampling. Data were collected through measurement and direct comunication technics using interview guideline and scientific work skills test. After being given training with guided inqury learning model, an increase in the skills of scientific work that are by 44,4%, 36,1% % dan 2,8% in the category of less skilled, and unskilled respectively while the results show that the 2 posttest scientific work skills of students that are skilled in a row amounted to 61,1% dan 38,9% in the category of skilled and highly. Wilcoxon test results showed there were differences of scientific work skills before and after learning
Sistem Identifikasi Batik Alami Dan Batik Sintetis Berdasarkan Karakteristik Warna Citra Dengan Metode K-means Clustering
Batik adalah kain khas Indonesia yang memiliki berbagai motif dan warna. Pewarnaan batik dibagi menjadi 2 yaitu batik alami dan batik sintetis. Proses pemilihan batik alami dan sintetis umumnya sangat bergantung pada persepsi manusia terhadap komposisi warna. Produsen batik melakukan pengamatan visual secara langsung untuk membedakan warnanya. Kelemahan dari cara ini yaitu keterbatasan visual manusia dan tingkat kelelahan sehingga warna satu dan lainnya dapat tertukar. Perkembangan ilmu pengetahuan dan teknologi pengolahan citra digital memungkinkan untuk membedakan batik alami dan sintetis secara otomatis dengan bantuan aplikasi pengolahan citra. Identifikasi batik alami dan sintetis ini menerapkan metode K-Means Clustering. Pendukung identifikasi menggunakan bantuan media camera digital sebagai pengambilan gambar batik yang kemudian dihitung nilai normalisasi RGB. Tingkat keberhasilan identifikasi yang didapatkan dengan menggunakan metode K-Means adalah 92.8%. Dari hasil identifikasi yang diperoleh menghasilkan 2 output yaitu Batik Alami 100% dan Batik Sintetis 85.71%
Pengembangan Sistem Pengenalan Wajah Dengan Metode Pengklasifikasian Hibrid Berbasis Jaringan Fungsi Basis Radial Dan Pohon Keputusan Induktif
Face recognition is a difficult task mostly because of the inherent variability of the image formation process ranging from the position/cropping of the face and its environment (distance and illumination) is totally controlled, to those involving little or no control over the background and viewpoint. Moreover, those are allowing for major changes in facial appearance due to factors expression, aging, and accessories such as glasses or changes in hairstyle. A solution has been proposed by considering hybrid classification architectures deal with the benefit of robustness via consensus provided by ensembles of Radial Basis Functions (RBF) networks and categorical classification using decision trees. A specific approach considers an ensemble of RBF Networks through its ability to cope with variability in the image formation. The experiments were carried out on images drawn randomly 50 unique subjects totalling to 500 facial images with rotation ± 50 encoded in greyscale. The faces are then normalized to account for geometrical and illumination changes using information about the eye location. Specifically performance true positive by Ensambles RBF1 (ERBF1) increased on ± 13,86% measures up to RBF while ERBF2 by ± 15,93%. On the contrary the false negative rate decreased by amount of ±5,8% for ERBF1 and somewhat less to ±5,6% for ERBF2. When the connectionist ERBF model is coupled with an Inductive Decision Tree - C4.5 - the performance improves over the case while only the connectionist ERBF module is used
Klasifikasi Kehamilan Beresiko dengan Menggunakan Metode K-nearest Neighbor (Studi Kasus Dinas Kesehatan Kabupaten Malang)
Masing-masing kehamilan pasti memiliki resiko yang berbeda-beda. Di Kabupaten Malang tingkat kehamilan berisiko ditargetkan hanya 20% dari total ibu hamil yang ada pada masing-masing wilayah, akan tetapi angka yang ditargetkan tidak selalu sesuai dengan hasil yang ada di lapangan. Di wilayah kerja Dinas Kesehatan Kabupaten Malang tepatnya di bagian selatan, keberadaan dokter spesialis kandungan sangatlah minim sehingga pemeriksaan kehamilan hanya sebatas di puskesmas maupun bidan praktek mandiri saja. Dengan kondisi seperti itu, jika terjadi permasalahan terhadap kondisi kehamilan seseorang akan memerlukan waktu untuk berkonsultasi terhadap dokter yang ada di pusat kota. Dalam penelitian ini akan membahas mengenai klasifikasi kehamilan beresiko dengan menggunakan metode K-Nearest Neighbor, dengan adanya klasifikasi ini diharapkan mampu mendeteksi sejak dini dan mengurangi angka kematian ibu, janin dan bayi akibat kehamilan beresiko. Hasil uji dalam mengukur akurasi metode ini menggunakan metode validasi dengan membandingkan data yang diperoleh dari dinas kesehatan (puskesmas) dengan sistem dan menghasilkan tingkat akurasi nilai sebesar 93 % dengan menggunakan nilai K = 5, maka metode ini dapat dikategorikan baik dalam mengklasifikasi kehamilan beresiko ini