Journal of Agroindustrial Technology
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HIDROLISIS Eucheuma cottonii DENGAN ENZIM K-KARAGENASE DALAM MENGHASILKAN GULA REDUKSI UNTUK PRODUKSI BIOETANOL
Get PDFBioethanol is one of the renewable resources derived from sugar fermentation process of carbohydrate substance with microorganismaid. Hydrolysis is the stage to get the simple sugar and is done with using k-carragenasethat is obtained from the isolation result of marine microbe in E.cottonii’s habitat. The objectives of this research were to gain time hydrolysis to produce the enzyme activity and reducing sugar highs by k-karagenase and to determine the best of the substrate concentration and k-carragenasein producing a reduction sugar and the highest ethanol. The research steps was started from isolate rejuvenation of IH22 microbe, enzyme production of crudeextraction k-carragenase and 80% acetone precipitation, determination of the hydrolysis timeand activity of k-carragenase. The next step was the substrate hydrolysis with amounts of 6%, 9%, and 12% (b/v) solids, by enzyme from acetone concentrations of 0%, 2.5%, and 5% (v/v) and then they were fermented for six days with the S.cereviseaeadapted yeast extract. Thek-carragenasse highest enzyme activity was obtained in incubation for 30-60 minutes while the highest reduction sugar was obtained inhydrolysis time for 120 minutes. During the hydrolysis,12% substrate concentration generated the highest reduction sugar and whole sugar of 3.21% and 9.89%, respectively, while 9% substrate with 5% enzyme treatment contained1.49% reduction sugar and 2.75% whole sugar, which was the best substrate in producing ethanol during fermentation process of 1.23% (v/v) and 0.82% (b/v) with 55.78% substrate efficiency and 70.44% fermentation efficieny.Keywords : bioethanol, Eucheuma cottonii, k-carragenasse, S.cerevisia
PENINGKATAN KINERJA RANTAI PASOK BAWANG MERAH (STUDI KASUS: KABUPATEN BREBES)
Get PDFShallots supply chain faces many problems and challenges, so need efforts to improve the performance. This study was conducted to: 1) analyze conditions of the shallots supply chain using the framework discussion of FSCN (Food Supply Chain Network), 2) measure performance of the shallots supply chain using the rating scale method and indicator assessment adapted from the SCOR (Supply Chain Operations Reference) model, and 3) formulate efforts to improve performance of shallots supply chain by conducting gap analysis and problem analysis. The study was conducted in Brebes as the largest shallots production center in Indonesia. The results showed that the members of shallots supply chain are farmers, traders, wholesalers, and retailers or traditional local market traders. The performance measurement to shallots supply chain in Brebes showed the value of 3.57 during the season and 3.28 in off season. Efforts to improve the supply chain performance of shallots in Brebes include building proper inventory system; build partnerships, coordination and collaboration among the members of the chain and institutional capacity building of farmers, address the low availability of shallots especially during the off season; increase the availability of market information; and solve the problems concerning the distribution mechanism.Keywords: shallots, supply chain, performance measurement,performance improvement
PROSES PEMBUATAN SERAT MIKROBIAL (NATA) DARI LIMBAH CAIR PABRIK KELAPA SAWIT
Get PDFProcessing palm oil fruit into crude palm oil (CPO) produces liquid waste (palm oil mill effluent = POME) in large quantities. Besides potential as an environmental pollutant, POME also has a potential as a source of microbial fibers. The objectives of this study wereto determine the formulation of the addition of coconut water into POME in the production of microbial fiber (nata) and to determine the right timing for inoculation of Acetobacter xylinum in the production of microbial fiber (nata). The first factor was the time of keeping the POME, with a level of 7 days, 14 days, and 21 days. The second factor was the addition of coconut water with a level of 0%, 10%; 20%; 30%; and 40% of the total POME. The results of the study were the addition of coconut water into POME to a concentration of 40% was able to increase the thickness and fiber yield of microbial (nata), Acetobacter xylinum was able to grow on media of 100% POME, and keeping the POME up to 21 days could decrease the thickness and yield of wet microbial fibers (nata), but increase the microbial yield of dry fiber (nata) generated.Keywords: CPO, microbial fibers, nata, POM
PENGUKURAN DAN PERBAIKAN KINERJA RANTAI PASOK UKM LAPIS BOGOR SANGKURIANG UNTUK MENINGKATKAN DAYA SAING UKM
Get PDFNowaday, the rate of growth and development small medium enterprise (SME)is in line with increasing enterprise competition. In modern competition today is focusing not only with other company, but also become the competition against supply chain. Therefore, the enterpreneurs have to prepare strategies to fix supply chain for increase SME competitiveness. Lapis Bogor Sangkuriang (LBS) becoming the first inovative of taro sponge cake which is known as signature snack in Bogor. This research aimed to identified supply chain condition, measured supply chain performance based Supply Chain Operation Reference (SCOR) and chosed the priority strategy to improve the supply chain condition with Technique Order Preference Similiarity to Ideal Solutions (TOPSIS). The supply chain pattern of Lapis Bogor Sangkuriang (LBS) consisted of direct supply from supplier to manifacture of LBS and indirect supply or through the cooperative. The supply chain measurement in LBS used SCOR and combined with Analytical Hierarchy Process (AHP) produced the performance scor of 68.5% with the matrix SCORs that had to be improve were upside supply chain adaptability (26.6%) and flexibility (37.5%). The priority strategy to improve the supply chain performance based on TOPSIS was increasing machine and labour productivity.Keywords:competitiveness, improvement, measurement, small medium enterprise, supply chai
Pedoman Bagi Penulis
Get PDFKetentuan Umum1. Penulis harus menjamin bahwa naskah yang dikirimkan adalah asli dan tidak pernah dipublikasikan di jurnal lainnya, yang dinyatakan dengan surat pernyataan seperti terlampir.2. Naskah yang akan dipublikasikan pada Jurnal Teknologi Industri Pertanian dapat berupa hasil penelitian, analisis kebijakan, komunikasi singkat, opini, gagasan dan review.3. Naskah dapat ditulis dalam Bahasa Indonesia atau Bahasa Inggris menggunakan format yang sesuai dengan kaidah bahasa yang digunakan. Editor tidak menerima naskah yang tidak memenuhi persyaratan yang diminta.4. Penentuan layak tidaknya naskah yang akan dipublikasikan ditentukan oleh Dewan Editor Jurnal Teknologi Industri Pertanian atas masukan mitra bestari yang kompeten.5. Naskah dikirimkan ke editor sebanyak tiga eksemplar dalam bentuk naskah asli dan softcopy dalam CD atau dapat dikirim via email. Naskah ditulis dalam Microsoft Word,Gambar/grafik dalam Microsoft Excel dan tuliskan nama pengarang sebagai nama file. Naskah dapat dikirimkan dengan softcopynya kepada : Editor Jurnal Teknologi Industri Pertanian, Departemen Teknologi Industri Pertanian (TIN), Fateta IPB, Kampus IPB Darmaga PO Box 220 Bogor 16002, Telpon/Fax : 0251-8625088; 0251-8621974; dengan alamat e-mail: [email protected] [email protected]. Hak Cipta tulisan yang dimuat ada pada Jurnal Teknologi Industri Pertanian. Penulis yang naskahnya dimuat diharuskan membayar kontribusi biaya penerbitan sebesar Rp 75.000,- per halaman. Biaya tambahan untuk pencetakan halaman berwarna menjadi tanggung jawab penulis.7. Penulis harus mengusulkan 3 nama mitra bebestari yang kompeten dibidangnya dan bergelar doktor beserta alamat lengkapnya yang penulis harapkan dapat mereview naskahnya.Standar Penulisan1. Naskah diketik dengan jarak 1,5 spasi kecuali Judul, Abstrak, Judul Gambar dan Judul Tabel diketik 1 spasi. Naskah diketik di atas kertas A4 dalam 1 kolom dengan jumlah kata antara 4000 sampai 7000 kata termasuk gambar dan tabel.2. Naskah diketik menggunakan program Microsoft Word, Gambar menggunakan JPEG atau TIFF, jika ada grafik, lampirkan juga file masternya/Microsoft Excel. Huruf standar yang digunakan untuk penulisan adalah Times New Roman 12.3. Naskah disusun dengan urutan: judul, nama penulis, alamat lengkap instansi setiap penulis, abstrak, pendahuluan, bahan dan metode, hasil dan pembahasan, kesimpulan,ucapan terima kasih (kalau ada) dan daftar pustaka. Alamat instansi (jalan, nomor, kota, kode pos) dan alamat e-mail penulis perlu dituliskan dengan jelas.4. Tata nama latin binomial atau trinomial (italik) digunakan untuk tanaman, hewan, serangga dan penyakit. Nama lengkap kimia digunakan untuk senyawaan pada penyebutan pertama kali.5. Satuan pengukuran dipakai Sistem Internasional (SI).6. Penulisan angka desimal untuk Bahasa Indonesia dengan koma (,) dan untuk Bahasa Inggris dengan titik (.)
MODEL ASOSIASI PERUBAHAN WARNA PADA INDIKATOR KEMASAN CERDAS DAN PERUBAHAN MUTU PRODUK SUSU
Get PDFColour based indicator for smart packaging is important for customers to get real fresh product and minimize the risk dealing with expiry storage. Currently, there is no exact model to relate these gradual colour changes with what extend of quality rate. Thus in this paper, it proposed a model based on association rules mining to generate relationship of smart packaging colour indicator and the quality of pasteurized milk packaged on the plastic bottle. The objectives of this research were to identify association parameters and to develop an association model of discoloration of smart packaging indicator on natural dyes to the quality changes. For a complete solution, the association model was effective to predict the status of smart packaging by applying the apriory algorithm from a combination of items. This research showed applicability from the association parameters which were obtained from previous research. Furthermore, this research generated top 10 rules out of 77 significant association rules which effectively outlined the quality to discoloration relationship and had strong relationship. Hence, these rules directly were applicable for the implementation of natural dyes to construct a smart packaging indicator.Keywords: smart packaging, association rules mining, color change, quality chang
Kata Pengantar Jurnal Teknologi Industri Pertanian
No full textPRAKATA Pembaca yang budiman,Puji syukur kita panjatkan kehadirat Allah SWT, atas berkat dan rahmatNya kamidapat kembali hadir untuk menyajikan artikel-artikel terkini pada Jurnal Teknologi Industri Pertanian Volume 27 Nomor 1 Edisi April, Tahun 2017. Semua artikel yang dimuat pada Jurnal Teknologi Industri Pertanian ini telah diseleksi dan ditelaah oleh Dewan Editor dan Mitra Bebestari yang kompeten. Hanya artikel-artikel berkualitas baik dan sangat baik yang dapat dimuat pada Jurnal Teknologi Industri Pertanian. Topik-topik yang disajikan pada edisi ini meliputi: Pemodelan statistical control detection adaptive (SCDA) untuk monitoring dan prediksi volume produksi Crude Palm Oil (CPO) nasional; Sintesis surfaktan alkil poliglikosida (APG) berbasis dodekanol dan heksadekanol; Model kinetika perubahan warna label indikator dari klorofil daun singkong; Hidrolisis Eucheuma Cottonii dengan enzim K-Karagenase;modifikasi pengolahan durian fermentasi (Tempoyak);Co-Composting limbah padat Beltpress dan jerami padi;Pengaruh dosis bleaching earth dan waktu pemucatan Crude Palm Oil;pemanfaatan tepung porang (Amorphophallusoncophyllus) sebagai penstabil emulsi M/A dan bahan penyalut pada mikrokapsul minyak ikan;Penghilangan hemiselulosa serat bambu secara enzimatik, model asosiasi perubahan warna pada indikator kemasan cerdas dan perubahan mutu produk susu. Sebagai penutup disajikan artikel yang berjudulSistem penunjang keputusan multi kriteria untuk pengembangan agroindustri kopi gayo menggunakan pendekatan Fuzzy-Eckenrode dan Fuzzy-Topsis. Kepada penulis dan mitra bebestari yang telah berkontribusi pada penerbitan jurnal edisi ini, kami menyampaikan terima kasih yang mendalam. Kami mengundang rekan sejawat peneliti dan praktisi agroindustri mengirimkan naskah untuk disajikan pada jurnal ini. Saran dan kritik yang membangun dari pelanggan, pembaca dan para pihak lainnya sangat kami harapkan. Selamat membaca. Ketua Dewan Editor Marimi
MODEL JARINGAN SYARAF TIRUAN UNTUK MEMPREDIKSI KADAR AIR BAHAN PADA PNEUMATIC CONVEYING RECIRCULATED DRYER
Get PDFRecirculation drying process ofmaterial on pneumatic conveying recirculated dryer (PCRD) are very complexand not linear, so it is very difficult to predict the final required moisture content.The purpose of this study was to develop a model of Artificial Neural Networks (ANN) to predict the final moisture content of the material on the PCRD machine. In this study, PCRD machine has been designed with variability in recirculation, and ANN Graphical User Interface (GUI) application using Neural Network in computer software. AAN models have been designed using the structure of a network with 11 input neurons, hidden multilayers neurons, and one output neuron with backpropagation learning algorithm. Training and testing of models using 54 and 27 data set observations respectively. The validity test results of the model obtained the value of r2 trainning was 0.99 or 99%, and r2 of the testingwas 0.96 or 96%. This indicated that the models are very valid to predict the final moisture content of the materialon the PCRD machine. The results also revealed RMSE, MAE, MRE value of ANN optimization model was 0.118% wb, 0.056% wb, and 0.644% respectively. While the value of RMSE, MAE, MRE ofthe process of the model testing was 0.226% wb, 0.129 % wb, and 1.496% respectively.Keywords: prediction, moisture content, models, pneumatic recirculated conveying dryer, artificial neural networ
KARAKTERISTIK LINDI HASIL FERMENTASI ANAEROBIK SAMPAH KOTA DALAM LISIMETER DAN POTENSI PEMANFAATANNYAMENJADI PUPUK CAIR
Get PDFThis study aimed to characterize the content of the leachate from lisimeter and assess the potential for leachate as liquid fertilizer. Leachate samples were taken from 5 lisimeter containing municipal waste in various sizes; A=(powder), B=(0.1 cm – 0.9 cm), C=(1.0 cm–1.9 cm), D=(2.0 cm – 2.9 cm), and E=(Original). Observation was conducted to leachate quality during bioconversion in 150 days. Result shows that at all treatment of degradation rates in leachate gives decreasing value of BOD, COD,NH4-N, TKN, and Phospate (P) except Kalium (K+) which increased during the bioconversion process. The value of TKN, Phospate, and Kalium (K+) is within safe limit to be dishcarged to the environment in the form of liquid fertilizer. Pollutant characteristics in leachate after anaerobic fermentation treatment in the form of heavy metals Hg, Cr, Cd. Pb, Zn, and Cu analyzed from all treatment shows values within safe limits to be discharged to environment in the form of liquid fertilizer. However, levels of BOD, COD and NH4-N are not yet qualified for discharge and require further treatment.Keywords: leachate, municipal waste, anaerobic fermentation, lysimete
FAKTOR PENENTU SIFAT WARNA TANDAN BUAH SEGAR (TBS) SAWIT UNTUK MEMODELKAN KANDUNGAN MINYAK MENGGUNAKAN EVALUASI NONDESTRUKTIF FOTOGRAMMETRI
Get PDFIn this study, the oil palm fresh fruit bunch (FFB) was harvested and its images were recorded in a photographic studio. The bunch was recorded from various distances (2, 7, 10, 15m) using five lighting configuration, i.e. ultraviolet lamp (600 watts), visible lamp (600 and 1000 watt), as well as IR lamp (600 and 1000 watts). The FFB images were processed in order to obtain 15 colour components making up the image, consist of three primary colours (R, G, B) and their transformations (H, S, I, RI, GI, BI, RG, RB, GB, GR, BR, BG). The prediction model of FFB’s oil content was built to evaluate the amount of oil on FFB accurately based on its image. The model was built using deep neural networks, where the colour components served as inputs, and 10 hiden layers were introduced to describe the relationship between all these variables and oil content. Of various recording setup, only four were selected based on their coefficient of correlation, namely: 10m_UV (R2 = 1); 10m_Vis2 (R2 = 1); 10m_IR2 (R2 = 1); and 2m_IR2 (R2 = 0.981). The determinant colour of the FFB’s image which mostly influence the prediction models were the ratio of R to B (RB) for 10m_UV; the value of H and S on 10m_Vis2; the I and S of the 10m_IR2; and RB, H, and B for the 2m_IR2 treatment.Keywords: deep neural network, FFB, nondestructive, oil content, photogrammetr