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"Pendahuluan: Dampak kesehatan akibat pajanan pelarut organik cukup serius baik yang bersifat akut maupun kronis. Pengendalian lingkungan kelja dan pemantauan kesehatan pekerja harus dilakukan sedini mungkin. Penggantian bahan pelarut organik dengan bahan lain yang lebih aman adalah pilihan terbaik untuk mengurangi dampak pada kesehatan pekelja. Namun pcnggantian bahan pelarut dengan bahan lain dapat berdampak pada proses produksi maupun mutu produksi. Oleh karena itu analisis dampak kesehatan pekelja sedini munglcin menjadi bagian yang sangat penting, sehingga ganggllan kesehatan pekcrja dapat diketahui secara dini untuk dilakukan penanganan. Metode: Menggunakan metode penelitian potong lintang (Cross-Sectional study). Variabcl bebas adalah kadar MBK di udara tempat kexja dan kadar MEK di dalam air seni. Variabel terikat berupa gangguan kesehatan {penyakit lculit, saluran napas, iritasi mata dan gejala dini gangguan sistem sarat), Data penelitian adalah data primer dan sekunder dari hasil pengukuxan, pemeriksaan dan catatan medis. Hasil: Kadar MEK di tempat kexja textinggi adalah 249 ppm, sedangkan pajanan terendah adalah 103 ppm. 30,2% responden ditemukan terpajan di alas NAB. Kadar IPB di dalam air scni tcrtinggi adalah 5,21 mg/1, sedangkan hasil terendah adalah 0,01 mg/l. Sebanyak 27,9% responden di atas IPB. Prevalensi gangguan kesehatan peke1ja akibat pajanan pelarut organik MEK adalah: penyakit kuiit (34,9%); penyakit saluran napas (55,8%); iritasi mata (4,7%); dan gejala dini gangguan sistem saraf (44,2%). Prevalensi gangguan kesehatan lebih banyak ditemukan pada pekerja yang terpajan MEK di atas NAB dibandingkan dengan di bawah atau sama dengan NAB. Kesimpulan: Hasil analisis muitivaliat membuktjkan adanya hubungan yang bermakna antara kadar MEK di udara tcmpat kcrja, kadar MEK di dalam air seni, status gizi dan lama kerja dengan gejala dini gangguan sistem sarai.

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Introduction: The effect on health due to the exposure of Methyl Ethyl Ketone organic compound is a serious condition which related to acute and chronic eifccts. Exposure controlling work environments and monitoring the health status of employees must be done properly. Substituting the MEK organic compound with another safer substance is the best solution to reduce the health effect. However, it will give an impact to the product line and quality product. Early health effect detection is an important to find out the possibility of adverse health effect and manage the finding.

Method: Cross-Sectional Study is thc method in this research. The independent variables are the level of MEK in the work place and the level of MEK in the urine. The dependent variables are health effects (skin diseases, respiratory tract, eye irritation and early neurotoxic symptom). The data are taken from the Primary and Secondary Sources that are obtained by conducting a measurement, a physical exam as well as collecting and analyzing the medical records.

Results: The highest level of MBI( in the work place is 249 ppm and the lowest is 103 ppm. There are 30.2% respondents exposed to MEK above the Thresh Hold Limit Value (TLV). The highest Biological Exposure Index (BEI) urine is 5.2lmg/l and the lowest is 0.01 mg/l. There are 27.9% respondents with the level of MEK above the BEI. The prevalence of health effect due to the exposure of MEK is skin diseases (34.9%), 'respiratory tract diseases (55.8%), eye irritation (4.7%) and early neurotoxic symptom (44.2%). The prevalence of health problem is more Hequent to the respondents who are above the TLV than less than the TLV.

Conclusion: Multivariate analysis indicated a significant correlation among MEK, BEI, nutritional status and length of work with early neurotoxic symptom."

"Penelitian bertujuan untuk membuat model spasial deforestasi tahun 1996 ndash; 2007, 2007 ndash; 2016, 1996 ndash; 2016 dan prediksi deforestasi periode 2016 - 2035. Selain itu, penelitian juga dimaksudkan untuk mengetahui biomassategakan dan cadangan karbon. Metode pendekatan yang digunakan adalah analisis kuantitatif dan deskriptif berbasis spasial. Deforestasi yang berlangsung selama periode 1996 hingga 2016 menyebabkan Kabupaten Bengkulu Utara kehilangan hutan seluas 27.154 ha. Pada periode tersebut umumnya deforestasi terjadi pada kawasan hutan produksi di kecamatan Pinang Raya dan Giri Mulya. Kemudian, berdasarkan analisis NDVI pada citra Landsat tahun 2016, kawasan hutan dengan karakteristik NDVI rendah, sedang dan tinggi secara berturut-turut memiliki biomassategakan 132,23 ton/ha, 287,59 ton/ha, dan 560,20 ton/ha. Sedangkan cadangan karbon pada NDVI rendah 62,15 ton C/ha, NDVI sedang 135,17 ton C/ha, dan NDVI tinggi 263,29 ton C/ha. Hasil perhitungan ini cukup valid karena sesuai dengan catatan Puslitbang Perubahan Iklim dan Kebijakan KLHK RI yang mengatakan bahwa cadangan karbon pada berbagai kelas tutupan lahan di hutan alam berkisar antara 7,5 ndash; 264,70 ton C/ha. Sementara itu, berdasarkan model spasial prediksi deforestasi tahun 2016 - 2035 Bengkulu Utara terancam kehilangan hutan seluas 21.345 ha. Deforestasi semakin meluas ke arah hutan lindung dan konservasi. Ketinggian dan lereng merupakan faktor pendorong deforestasi pada periode ini.Kata kunci: Model spasial, deforestasi, cadangan karbon.

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The study aimed to create spatial deforestation models 1996 2007, 2007 2016, 1996 2016 and predicted deforestation period 2016 2035. In addition, the study also aimed to determine biomass and carbon stock. The approach method used is spatial based quantitative and descriptive analysis. Deforestation that lasted from 1996 to 2016 caused the North Bengkulu Regency to lose 27,154 ha of forest. In that period, generally deforestation occurred in production forest area located in Pinang Raya and Giri Mulya sub districts. Then, based on NDVI analysis on Landsat image 2016, forest area with low, moderate and high NDVI characteristic biomass 132,23 ton ha, 287,59 ton ha and 560,20 ton ha respectively. While carbon stocks in low NDVI was 62.15 ton C ha, moderate NDVI was 135.17 ton C ha, and high NDVI was 263.29 ton C ha. The results of this calculation was quite valid because in accordance with the record of the Center for Climate Change Policy KLHK RI said that carbon stocks in various classes of land cover in natural forests ranged from 7.5 to 264.70 tons C ha. Meanwhile, based on the spatial model of prediction of deforestation in 2016 2035 North Bengkulu threatened loss of forest area of 21,345 ha. Deforestation is increasingly widespread towards protected forests and conservation. Elevation and slope are the drivers of deforestation in this period. Keywords Spatial model, deforestation, carbon stock"

"ABSTRAKFast Fourier Transform (FFT) adalah suatu metoda ataualgoritma untuk mempercepat operasi penyelesaian transformasifourier diskrit. Algoritma FFT ada dua macam, yakniDecimation in Time (DIT) dan Decimation in FrequencyAlgoritma FFT-DIT lebih populer daripada algoritma FFT-DIFkarena hanya memerlukan satu operasi perkalian untuktitiknya. Pada tugas akhir ini akan dirancang suatu chip VLSIuntuk algoritria Fast Fourier Transform Decimation in Time(FFT-DIT) satu titik kupu-kupu (dua titik transforniasi)dengan menggunakan teknologi CMOS. Data masukan maupun datakeluaran berupa bilangan imajiner dengan format 8-bit mantisadan 4-bit eksponen. Transistor yang dipakai sebanyak 9438buah dan waktu yang dibutuhkan untuk menyelesaikantransformasi adalah 600 nano detik. perancangan dilakukandengan menggunakan software CAD CIRCAD II pada komputer HP-9000."

"ABSTRACTLombok is located between Bali and Sumbawa Island. This island is popular as tourist destination, especially for marine tourism. On the other hand, marine fauna from Lombok is not so popular as their beautiful beaches. One kind of marine fauna is snail, neriti snails are common and easy to find along the beach. T here are twelve species of Nerita snails found in Lombok recently. Nine 0fthem were having their representations in the collections of Museum Zoology Bogor; while the rest three are not yet collected. One of museum collection, Nerita acellata Le Guillou, 1841, is never reported from Lombok before."