Judul: Tingkat pencemaran air kali Cakung ditinjau dari sifat fisiko - kimia khususnya logam berat dan keanekaragaman jenis hewan bentos makro
Abstrak: Kali Cakung yang mengalir dari hulu ke hilir melewati daerah industri, yang diperkirakan industri tersebut mengandung limbah logam berat yang akan mengalir ke sungai. Sedangkan Kali Cakung menurut Surat Keputusan Gubernur DKI Jakarta No. 484 Tahun 1977 diperuntukkan untuk perikanan, pertanian dan buangan industri. Logam berat pada perairan akan diserap oleh plankton dan bentos, melalui rantai makanan plankton dan bentos dimakan oleh ikan dan kerang-kerangan, kemudian dimakan lagi oleh manusia. Berarti logam berat yang terakumulasi dalam tubuh ikan atau kerang-kerangan akan masuk ke dalam tubuh manusia, sehingga dapat mengganggu kesehatan…dst
Keyword: konsep ekosistem, kualitas air, fisika perairan, kimia perairan, organisme bantos

Judul: Study kualitas fisika - kimia air kali cakung sehubungan dengan daerah industri pulogadung di dki jakarta
Abstrak: Tujuan penelitian ini adalah untuk mempelajari pecemaran Kali Cakung sehubungan dengan limbah industri dan sapah rumah tangga, bagi keperluan pertanian dan perikananı erta kemungkinan pencegahannya. Metode pengambilan contoh air dilakukan secara transek horizontal menyilang arah aliran sungat dan transek vertical kea rah dasar perairan. Pada transek horizontal, pengambilan contoh dilakukan di pinggir kiri, kanan dan di bagian tengah su-ngai, sedangkan pada transek vertikal, pengambilan contoh dilakukan pada kedalaman 0, 20, 60 dan 80 persen dari permukaan air. Pengambilan contoh dilakukan dengan botot "water sampler" dan parameter yang diteliti adalah parameter sifat fisika dan kimia air. Pengamatan dilakukan pada bulan Nopember - Desember 1978. dst ...
Keyword: Softwater;, Hard waters;, Water quality;, Bogor Agricultural University;

Judul: Application of Mel Frequency Cepstrum Coefficients (MFCC) as Feature Extraction on Phoneme Recognition with Probabilistic Neural Network (PNN) as Classifier
Abstrak: Voice recognition (speech recognition) is one field of study in voice processing. This technology can convert voice signals into a form of written information (text). With this technology, people can interact with a computer. MFCC feature extraction computes the cepstral coefficients by considering the human hearing. This research is a phoneme recognition using feature extraction MFCC and PNN as feature matching model. This study compares the coefficient, overlap, and the test data without noise and with noise. MFCC is used with 13, 20, 26 coefficients and 0%, 25%, 50% overlap. Noise is added by 30 dB, 20 dB and 10 dB. From the comparison of the three overlaps, produced the best accuracy at 50% overlap with an accuracy of 94,71%. From comparing the three coefficients, better accuracy resulting in coefficients of 20 and 26 with an accuracy of 97,12% at 50% overlap. After comparing between the coefficients of 20 and 26 with overlap of 25% then the coefficient 26 is obtained that better accuracy of 94,23%. This shows that in this study the coefficient 26 is the best. In this research, there are three noise variables. The variables are 10 dB, 20 dB, and 30 dB. The best accuracy reached when the noise variable is 30 dB rather than 10 dB or 20 dB because the accuracy has the closest accuracy compared by the accuracy when noise was not added into the data. When the noise variable is 30 dB, the percentage of accuracy is 85,3%.
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