Judul: Heavy Metal (Hg, Cd, Pb and Cu) in Long Whiskered catfish Mystus gulio (Hamilton, 1822) in Bojonegara Waters
Abstrak: Aktivitas antropogenik seperti industri, domestik dan pelayaran merupakan penyumbang utama masuknya logam berat di perairan Bojonegara dan sekitarnya. Penelitian ini dilaksanakan pada bulan Agustus hingga Oktober 2020 di perairan Bojonegara, Teluk Banten. Penelitian ini bertujuan untuk menentukan tingkat akumulasi logam berat (Hg, Cd, Pb dan Cu) yang terkandung dalam daging ikan lundu Mystus gulio (Hamilton, 1822) di perairan Bojonegara, Teluk Banten. Lokasi penelitian ditentukan menggunakan teknik purposive sampling. Konsentrasi logam berat Hg, Cd, Pb, Cu pada daging ikan lundu berturut-turut <0,001 mg kg-1 (Hg), <0,005 mg kg-1 (Cd), <0,030 mg kg-1 (Pb) dan 0,699-10,920 mg kg-1 (Cu), nilai tersebut berada di bawah baku mutu menurut PerBPOM RI (2018) dan SK Departemen Kesehatan RI tahun 1989. Akumulasi Cu>Pb>Cd>Hg terjadi pada daging ikan lundu ukuran kecil maupun besar. Bioakumulasi ikan lundu yang ditangkap di perairan Bojonegara, Teluk Banten tergolong dalam akumulasi sedang hingga tinggi untuk logam berat Cu. Bioakumulasi logam berat Hg, Cd, dan Pb termasuk ke dalam kategori akumulasi rendah., Anthropogenic activities such as industrial, domestic, and shipping are the main contributors to the entry of heavy metals into the Banten Bay and the surrounding areas. This research was conducted from August to October 2020 in the coastal waters of Bojonegara, Banten Bay. This study aim to estimate the accumulation of heavy metals (Hg, Cd, Pb and, Cu) contained in long whiskered catfish Mystus gulio (Hamilton, 1822) in the Bojonegara coastal waters. The research location was determined using a purposive sampling technique. Based on the analysis, the heavy metal content in the fish meat were <0,001 mg kg-1 (Hg), <0,005 mg kg-1 (Cd), <0,030 mg kg-1 (Pb) and 0,699-10,920 mg kg-1 (Cu); the values were less than BPOM (2018) and Regulation of the Minister of Health Republic of Indonesia 382/1989 standard. The accumulation of Cu>Pb>Cd>Hg occurred in the small and large fish. The fish caught in Bojonegara Coastal Waters of Banten Bay have moderate to high accumulation levels of Copper (Cu). The accumulation level of Hg, Cd, Pb is included in the low category.
Keyword: accumulation of heavy metals, Banten Bay, heavy metals, Mystus gulio

Judul: Heavy Metal (Hg, Cd, Pb, and Cu) in the Blue Swimming Crab (Portunus pelagicus) at Bojonegara Coastal Waters, Banten Bay
Abstrak: Perairan pantai Bojonegara, Teluk Banten merupakan zona industri di wilayah Serang Barat yang dicirikan dengan banyaknya pabrik di sekitar pantai yang berpotensi menghasilkan bahan pencemar seperti logam berat dll. Bahan ini masuk ke dalam perairan dan berakumulasi dalam tubuh organisme perairan termasuk rajungan. Penelitian ini bertujuan menganalisis tingkat akumulasi kandungan logam berat pada rajungan (Portunus pelagicus) di Teluk Banten. Pengambilan sampel dilaksanakan pada bulan Agustus hingga Oktober 2020. Analisis kandungan logam berat dilakukan dengan menggunakan alat AAS (Atomic Absorption Spectrophotometer). Hasil pengamatan menunjukkan kandungan logam berat Hg, Cd, Pb, dan Cu berbeda nyata antara rajungan besar dan kecil (p<0,05). Kandungan akumulasi logam berat Cu pada rajungan kecil berkisar 3,22-4,34 mg kg-1 dan rajungan besar berkisar 6,64-9,52 mg kg-1 sedangkan kandungan logam berat Hg, Cd, dan Pb pada rajungan berada di bawah deteksi alat AAS. Bioakumulasi logam Cu pada rajungan tersebut termasuk akumulasi sedang hingga tinggi sedangkan logam logam Hg, Cd dan Pb tergolong akumulasi yang rendah. Batas aman konsumsi rajungan yaitu 22,0588 kg daging/minggu untuk orang dewasa dan 5,5147 kg daging/minggu untuk anak-anak., Bojonegara coast, Banten Bay is an industrial zone in the West Serang region, which is characterized by the presence of some factories around the coast. These have potential to produce and pour the pollutants such as heavy metals into the water and accumulate into the body of aquatic organisms like blue swimming crab. This study aims to analyze the level of heavy metal accumulation in the blue swimming crab (Portunus pelagicus) of Banten Bay waters. Sampling was carried out from August to October 2020. Analysis of heavy metal content was carried out using AAS (Atomic Absorption Spectrophotometer). During the observation, the heavy metal content of Hg, Cd, Pb, and Cu were significantly different between large and small blue swimming crab (p<0,05). The accumulation of heavy metal Cu in small blue swimming crab ranged from 3,22-4,34 mg kg-1 and large blue swimming crab ranged from 6,64-9,52 mg kg-1 while the heavy metal content of Hg, Cd, and Pb in small crabs was below detection AAS. Bioaccumulation of Cu in blue swimming included moderate to high, while heavy metal Hg, Cd, and Pb it was low accumulation. The safe limit for consumption blue swimming crab is 22,0588 kg of meat/week for adults and 5,5147 kg of meat/week for children.
Keyword: Accumulation, blue swimming crab, Bojonegara coastal waters, heavy metals

Judul: Pengenalan kata berbasiskan fonem dengan pemodelan resilient backpropagation
Abstrak: The aim of this research is to know the performance of Neural Network as a model for word recognition. The research uses Resilient Backpropagation for modeling and Mel-Frequency Cepstral Coefficient (MFCC) for feature extraction. The voice data used comes from one speaker. Total words used are 70 words that consist of 50 words as a dictionary of words and 20 words, that each word repeated 10 times. Dictionary words consist of 50 words from a combination of phonemes used in the research. Phonemes used in this research are 10 phonemes consist of 4 vowels and 6 consonants phonemes. From the 20 words, each word is repeated 10 times, 7 times used as training data and 3 times are used as test data. The output from testing process are word transcription. The convertion process from the word transcription into word is done manually by 5 person. This research produces two models. Average accuracy obtained from model with 100 hidden neuron is 75% for test data and 61% for the dictionary of words. The best average accuracy obtained is 93% for test data and 62 % for the dictionary of words generated by testing the model with 1000 hidden neurons. Overfitting occurs in the second model with 1000 hidden neurons. It causes the model can only produce good output for data that has been trained.
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