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All Journal International Journal of Electrical and Computer Engineering HAYATI Journal of Biosciences MEDIA PETERNAKAN - Journal of Animal Science and Technology Jurnal Ilmu Pertanian Indonesia ACTA VETERINARIA INDONESIANA Jurnal Pengolahan Hasil Perikanan Indonesia Jurnal Primatologi Indonesia Media Veteriner Buletin Peternakan Jurnal Veteriner JURNAL GIZI INDONESIA Jurnal Ilmiah Aplikasi Isotop Radiasi Majalah Kedokteran Bandung BIOTROPIA - The Southeast Asian Journal of Tropical Biology Jurnal Keteknikan Pertanian Jurnal Simetris Jurnal Sain Peternakan Indonesia Jurnal Ilmu-Ilmu Peternakan (Indonesian Journal of Animal Science) Jurnal Ilmu Ternak Veteriner Jurnal Peternakan Indonesia AGRIVITA, Journal of Agricultural Science Jurnal Edukasi dan Penelitian Informatika (JEPIN) JITRO (Jurnal Ilmiah dan Teknologi Peternakan Tropis) agriTECH IJFAC (Indonesian Journal of Fundamental and Applied Chemistry) JURNAL BIOLOGI INDONESIA Jurnal Ilmu Nutrisi dan Teknologi Pakan Jurnal Perikanan Universitas Gadjah Mada Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Jurnal Riset Akuakultur Jurnal Ilmu Peternakan Terapan Computer Science and Information Technologies ZOOTEC Livestock and Animal Research Makara Journal of Science Jurnal Kedokteran Hewan Jurnal Agripet
DEWI APRI ASTUTI
Departemen Ilmu Nutrisi Dan Teknologi Pakan, Fakultas Peternakan, Institut Pertanian Bogor, Jln Agathis, Kampus IPB, Dramaga, Bogor, Jawa Barat, Indonesia 16680
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Immunology & microbiology Materials Science & Nanotechnology Medicine & Pharmacology Veterinary Other

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GENETIC VARIATION OF cDNA OF LDLR GENE IN HYPORESPONDER CYNOMOLGUS MACAQUES (Macaca fascicularis) Taher, Achmad; Solihin, Dedy Duryadi; Sulistiyani, Sulistiyani; Sajuthi, Dondin; Astuti, Dewi Apri
Jurnal Kedokteran Hewan Vol 11, No 3 (2017): September
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21157/j.ked.hewan.v11i3.2939

Abstract

The study aimed to identify genetic variation of cDNA sequence from low density lipoprotein receptor (LDLR) gene of hyporesponder cynomolgus macaques. The animal used in this study was one hyporesponder cynomolgus macaque obtained from selection result in Primate Research Center-Bogor Institute of Agriculture (PSSP IPB). Amplification of cDNA from LDLR gene was performed using polymerase chain reaction (PCR) method with 4 pairs of walking primer. Alignment of amplification result sequence from 4 pairs of walking primer generated target sequence of 2353 bp which located on position 188-2540. Analysis of target sequence alignment on reference sequence in GenBank found 8 single nucleotide polymorphism (SNP), namely c408CT; c.1200CT; c.1497CT; c.1644TC; 1791TC; 1804AG; 2088CT; and 2377GA. Of 8 SNPs, c.1804AG and 2377GA. Two SNP (c.1804AG; dan 2377GA) caused changing of amino acids composition namely p.K602E (lysine glutamate) and p.V793I (valine isoleucine). This result proved the potential use of genetic variation of cDNA sequence from LDLR gene as genetic marker for selection of hyporesponder cynomolgus macaques.
Different Flushing Frequency on Blood Metabolites Profile of Ewes and Their Lambs at Pre-Weaning Period Fassah, Dilla Mareistia; Taniasari, Mila; Daeli, Fanny Rahmasari; Diapari, Didid; Astuti, Dewi Apri; Khotijah, Lilis
Buletin Peternakan Vol 48, No 3 (2024): BULETIN PETERNAKAN VOL. 48 (3) AUGUST 2024
Publisher : Faculty of Animal Science, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21059/buletinpeternak.v48i3.93637

Abstract

This study determined the effects of different flushing frequency on performance and blood metabolite profile of ewes and their suckling lambs at pre-weaning period. Twelve multiparous Garut ewes (2 years-old, BW 30.06 ± 6.20 kg) and 18 lambs born to experimental ewes (lambing weight 2.49 ± 0.56 kg) were used in this study. Ewes were randomly assigned into four treatment groups in a complete block design, namely: without flushing (T0: control), flushing at the beginning of mating (T1: 2 weeks before and after mating), two times flushing (T2: T1 + 4 weeks flushing at mid-gestation), and three times flushing (T3: T2 + 2 weeks flushing at before and after parturition). Three times flushing increased ((p<0.05) the crude fat intake, while different flushing frequencies did not affect (p>0.05) dry matter intake and intakes of crude protein, crude fiber, nitrogen-free extract, and total digestible nutrients of ewes at the pre-weaning period. Different flushing frequencies did not change (p>0.05) the productive performances of ewes during the pre-weaning period. Flushing application improved (p<0.05) the average daily gain of pre-weaning lambs at 14 days, but it did not affect the weaning weight of lambs. Two times flushing showed no pre-weaning mortality rate (p<0.05). Flushing application tended to decrease (p=0.08) blood plasma triglyceride of ewes at 21- days, while two times flushing frequency tended to increase blood plasma cholesterol (p=0.05) and triglyceride (p=0.08) of lambs at 21 days. In conclusion, increased flushing frequency supports ewes and their twin lamb growth performance and blood metabolite profile at the pre-weaning period
Herbal Mineral Block Supplementation Containing Turmeric Flour, Black Soldier Fly, and Micro Minerals on Performance and Blood Profile of Dorper Crossbred Sheep Daulay, Kausar; Astuti, Dewi Apri; Suharti, Sri; Tarigan, Andi
Buletin Peternakan Vol 48, No 4 (2024): BULETIN PETERNAKAN VOL. 48 (4) NOVEMBER 2024
Publisher : Faculty of Animal Science, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21059/buletinpeternak.v48i4.96217

Abstract

This study aimed to determine the effect of herbal mineral block (HMB) supplementation containing turmeric flour, black soldier fly (BSF), and micro minerals on the performance and blood profile of Dorper crossbred sheep. Ten growing sheep and ten lactating sheep were divided into two treatment groups (P0: complete feed without HMB supplementation and P1: complete feed with HMB supplementation). The research design used was a factorial completely randomized design (2 × 2) with 5 replications. Factor physiological status of growing and lactating sheep and factor supplementation with and without HMB. The data were analyzed using ANOVA and Duncan’s test. The results showed no interaction between physiological status and HMB supplementation on sheep performance (nutrient intake, initial and final body weight, daily body weight gain, and feed efficiency) and blood profile (hematology, metabolites, and minerals). The physiological status had a very significant effect (p<0.01) on nutrient intake, initial and final body weight, daily body weight gain, feed efficiency, and significantly (p<0.05) on serum phosphorus. Supplementation of HMB significantly (p<0.05) increased serum calcium which was crucial for bone an teeth development in growing sheep and milk production in lactating sheep. Serum phosphorus was higher in growing sheep, supporting their bone growth and energy metabolis compared to lactating sheep as it was diverted to the mammary gland.
Evaluation of BSF Larva Meal and Oil as White Shrimp Feed on Growth Performance, Body Composition, and Health Response Rizal, Muhammad; Astuti, Dewi Apri; Fahmi, Melta Rini
Jurnal Perikanan Universitas Gadjah Mada Vol 26, No 2 (2024)
Publisher : Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jfs.97636

Abstract

The goal of this study was to evaluate the use of BSF larvae meal and oil as feed components in order to determine their impact on Litopenaeus vannamei shrimp growth performance, nutritional composition, and health response. Three shrimp ponds, each with a diameter of 20 m, were stocked with 72.000 Litopenaeus vannamei post larvae (PL-8), resulting in a stocking density of 229 shrimp per square meter. The trial diets comprised three types: control diet (K), diet containing BSF larvae meal (A), and diet containing BSF larvae meal plus oil (B). The parameters observed in this study included shrimp growth and productivity, feed consumption, feed conversion ratio (FCR), survival rate, nutritional composition (proximate, amino acid profile and fatty acid profile), total bacteria in the shrimp's digestive tract, and total hemocyte count in the shrimp's hemolymph. It was found that subtituting fish meal with 34% BSF larvae meal did not affect the growth performance of shrimp raised in shrimp ponds, compared to the control treatment. The assessment of the amino acid profile has revealed minimal variation between treatment. Nevertheless, both treatments A and B exhibited a decreased concentration of unsaturated fatty acids, specifically omega-3 and omega-6, in comparison to control. Meanwhile, treatment B had the highest levels of saturated fatty acid and omega-9 fatty acid content.  
Effects of Semi-Automated Preprocessing in The Beef Freshness Prediction based on Near Infrared Spectroscopy Raafi'udin, Ridwan; Purwanto, Yohanes Aris; Sitanggang, Imas Sukaesih; Astuti, Dewi Apri
Simetris: Jurnal Teknik Mesin, Elektro dan Ilmu Komputer Vol. 16 No. 2 (2025): JURNAL SIMETRIS VOLUME 16 NO 2 TAHUN 2025
Publisher : Fakultas Teknik Universitas Muria Kudus

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24176/simet.v16i2.15142

Abstract

This study investigates the application of near-infrared spectroscopy (NIR) within the wavelength range of 1350–2550 nm to predict key quality parameters of beef, specifically focusing on tenderloin cuts. The quality indicators assessed include drip loss, color, pH, moisture content, storage duration, and total plate count (TPC) as a measure of microbial load. Predictive modeling was conducted using three machine learning algorithms: Partial Least Squares (PLS), Support Vector Regression (SVR), and Random Forest Regressor (RFR). To enhance model accuracy, a semi-automated preprocessing pipeline was employed utilizing the Nippy library. This library integrates several spectral preprocessing techniques including Savitzky-Golay filtering, Standard Normal Variate (SNV), Robust Normal Variate (RNV), Local Standard Normal Variate (LSNV), as well as clipping, resampling, baseline correction, and smoothing.  Among the models developed using raw spectral data, the RFR model exhibited the highest performance, achieving coefficient of determination (R²) values of 0.82 for drip loss, 0.65 for color, 0.67 for pH, 0.61 for moisture content, 0.81 for storage duration, and 0.76 for TPC. Post preprocessing, the predictive accuracy improved significantly with R² values increasing to 0.89, 0.82, 0.87, 0.85, 0.91, and 0.90 respectively for the same parameters. These findings underscore the potential of combining advanced machine learning techniques with robust preprocessing methods to enhance the non-destructive, rapid assessment of beef quality parameters. This approach offers a promising tool for quality control in the meat processing industry, facilitating more efficient and accurate monitoring of product standards.
Model Klasifikasi Lahan Hijaun Pakan Ternak Ruminansia Dengan Algoritma Random Forest Pada Kabupaten Lumajang Marlina, Dwi; Sitanggang, Imas Sukaesih; Annisa, Annisa; Astuti, Dewi Apri
Simetris: Jurnal Teknik Mesin, Elektro dan Ilmu Komputer Vol. 16 No. 2 (2025): JURNAL SIMETRIS VOLUME 16 NO 2 TAHUN 2025
Publisher : Fakultas Teknik Universitas Muria Kudus

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24176/simet.v16i2.15967

Abstract

Informasi mengenai ketersediaan lahan hijauan pakan ternak ruminansia pada tutupan lahan memerlukan data spasial yang akurat, salah satunya dapat diperoleh melalui teknologi penginderaan jauh. Citra satelit Landsat 8 mampu menyediakan informasi mengenai tutupan lahan, termasuk lahan hijauan, badan air, pemukiman, industri, dan jalan. Citra satelit tidak hanya menginformasikan lahan hijauan saja tetapi dapat menginformasikan tutupan lahan seperti badan air, pemukinan, industri, dan jalan. Oleh karena itu, diperlukan proses klasifikasi tutupan lahan untuk mengindentifikasi area yang berfungsi sebagai sumber hijauan pakan ternak ruminansia. Identifikasi ini penting untuk mengetahui ketersediaan pakan, yang selanjutnya dapat digunakan sebagai dasar dalam memprediksi biomassa vegetasi. Penelitian ini bertujuan untuk mengklasifikasi tutupan lahan hijauan yang berperan sebagai pakan ternak ruminansia. Metode yang digunakan adalah algoritma random forest dengan memanfaatkan citra satelit Landsat 8 untuk wilayah , Kabupaten Lumajang pada periode tahun 2018 hingga 2022. Hasil klasifikasi menghasilkan tiga kelas utama lahan hijaua, yaitu perkebunan, pertanian/sawah, dan semak belukar. Model klasifikasi yang dibangun mencapai tingkat akurasi sebesai 93%. Berdasarkan hasil analisis, rat-rata lahan hijauan di Kabupaten Lumajang terdiri atas lahan perkebunan sebuas 23.865,78 ha, pertanian/sawah seluas 18.363,21 ha, dan semak belukar seluas 949,98 ha. Hasil penelitian menunjukkan bahwa lahan hijauan di Kabupaten Lumajang didominasi oleh perkebunan, sehingga daerah ini memiliki potensi yang baik untuk pengembangan hijauan sebagai pakan ternak ruminansia. Ketersediaan lahan yang luas diharapkan dapat mendukung usaha peternakan dan pengelolaan sumber daya pakan di wilayah tersebut.
Neural Network Innovation for Analyzing Physiological Changes in Cattle Within Modern Transportation Systems Dhika, Harry; Buono, Agus; Neyman, Shelvie Nidya; Astuti, Dewi Apri
Simetris: Jurnal Teknik Mesin, Elektro dan Ilmu Komputer Vol. 16 No. 2 (2025): JURNAL SIMETRIS VOLUME 16 NO 2 TAHUN 2025
Publisher : Fakultas Teknik Universitas Muria Kudus

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24176/simet.v16i2.16007

Abstract

The distribution of cattle before Eid al-Adha often leads to transport-induced stress, negatively affecting livestock performance and economic value. This study aims to develop a predictive model of post-transport cattle performance using Artificial Neural Networks (ANN). The dataset includes physiological parameters (rectal temperature, heart rate, and respiration) and blood metabolites (glucose and creatinine) collected before and after transportation. Data augmentation and feature selection were applied using Pearson correlation to address class imbalance. The ANN model was tuned with regularisation and dropout techniques to prevent overfitting. Evaluation results show that the model achieved 91% accuracy, with F1-scores of 0.90 (Increase), 0.97 (Stable), and 0.87 (Decrease). These findings demonstrate that ANN can capture complex patterns of physiological conditions in cattle and provide reliable predictions. This model has the potential to serve as the basis for developing an early warning system to minimize the risk of performance decline in cattle due to transport stress more adaptively and efficiently.
PREGNANT AND LACTATING Macaca nigra: BEHAVIOR AND FOOD SELECTION Perwitasari-Farajallah, Dyah; Arismayanti, Eka; Qomariah, Indira Nurul; Pasetha, Andre; Astuti, Dewi Apri; Waterman, James O.
BIOTROPIA Vol. 29 No. 2 (2022): BIOTROPIA Vol. 29 No. 2 Agustus 2022
Publisher : SEAMEO BIOTROP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11598/btb.2022.29.2.1687

Abstract

Pregnancy and lactation are reproductive phases that require large amounts of energy. Females in the reproductive period need good quality and quantity of food to provide nutrition for the fetus, milk production and child care. The mother will adapt to changes in behavior patterns and food type to meet these needs. The influence of parity and environmental conditions can affect the behavior patterns of females. During pregnancy, the Macaca nigra is known to have different proportion of activities in each period, while the behavior during the lactation phase in each mester is unknown. Therefore, this study aimed to analyze the behavior patterns in each mester and the food selection of Macaca nigra during the pregnancy and lactation phases, as well as the influence of female parity and environmental toward the behavior patterns. There were 39 females Macaca nigra observed from two groups from August 2018 to July 2019. An instantaneous focal sampling method was performed to observe females’ daily activities, continuous focal sampling to monitor food types and a selectivity index to analyze food type preferences. The results showed that the female Macaca nigra pattern was influenced by the reproductive phase, female parity and environmental conditions. Females at the end of the pregnancy and lactation phases had a high proportion of feeding and eat more arthropods. Primiparous females mostly performed resting activities. Food preference was influenced by reproductive factors and food availability. The choice of fruit could be affected by fruit availability, and their favorite food was D. mangiferum and Euginia sp.  
Co-Authors - Hernawati . Sumiati A Setiyono Achmad - Taher ACHMAD FARAJALLAH Achmad Taher Achmad Taher Achmad, Taher Agik Suprayogi Agita Rakhmawati Agus Buono Ainia Herminiati Akeme Cyril Njume Alma Agnia Alusyanti Primawati Anar, Muhammad Agung Firdhawansyah Andi Tarigan Andri Cahya Irawan Andri Cahya Irawan Anja Meryandini Anneke Anggraeni Anneke Anggraeni Annisa Annisa Annisa Annisa Anuraga Jayanegara Aris Purwanto Arismayanti Eka Armaji, Yone Asep Gunawan Asep Sudarman Aulia Evi Susanti Aulia Nurul Saputri Budi Setiawan Cece Sumantri Chairrusyuhur Arman Chusnul Choliq D Diapari D M Suci Daeli, Fanny Rahmasari Daulay, Kausar Didid Diapari Djokowoerjo Sastradipradja Dondin Sajuthi dortiana sijung, maria Dwierra Evvyernie DYAH PERWITASARI -FARAJALLAH Ekowati Handharyani Elizabeth Wina Elizabeth Wina Elmy mariana Elmy Mariana Elok Budi Retnani Endah Yuniarti Entang Iskandar Erika B. Laconi Evy Damayanthi f, Dilla Mareistia Fahmi, Melta Rini Fery Dwi Riptianingsih Firdus . Firkani, Rahmatiana Widi Fitriana, Eko Lela Hairani, Atikah Hanny Hafiar Harlystiarini Harlystiarini Harnowo Permadi Harry Dhika, Harry Heri Ahmad Sukria Hernawati Hernawati I Gusti Bagus Wiksuana I Komang Gede Wiryawan I NENGAH BUDIARSA I wayan Teguh Wibawan Ida Wiryanti Imas Sukaesih Sitanggang Irawan Sugoro Irawan Sugoro Irawan Sugoro Irma Herawati Suparto Jakaria Jakaria Janah, Fatiah Finanur Jean-Baptise Menassol K Komalasari Kevin Alexander, Kevin Klaus Becker Kokom Komalasari Komang G. Wiryawan Kurnia Bagus Ariyanto L Khotijah Lilis Khotijah Linar Zalinar Udin Lucia Cyrilla Eko Nugrohowati Luki Abdullah Mareistia Fassah, Dilla Marlina, Dwi Mohamad Yamin Mohamad Yamin Mohamad Yamin Mohammad Yamin Muhammad Agung Firdhawansyah Anar MUHAMMAD RIZAL Muladno - nabawi, Soviro Nurul Lisa Nahid Ritcher Nahrowi Nahrowi Nanda Nadhifa Nuraini Nanis Nurhidayah Natsir Sandiah NE Maharani Nella Nurhazizah Novita Anggraeni Nur Bambang Priyo Utomo Nurina Rahmawati Pamungkas, Joko Panca Dewi Manu Hara Karti PASETHA, ANDRE Pijoh, Deyv Pipih Suptijah Pursani paridjo Putri Sri Rahayu Qomariah, Indira Nurul R. Iis Arifiantini Rangkuti, Farhan Ananda Rangkuti, Farhan Ananda Rangkuti Razak Achmad Hamzah Retno Wulansari Ria Oktarina Ridwan Raafi'udin Ridwan, Habibi Rima Shidqiyya Hidayati Martin Rimbawan , Rini Herlina Mulyono Riptianingsih, Fery Dwi Rita Mutia Rizki Palupi Ronnie Permana Ronny Rachman Noor Rudy Priyanto Shelvie Nidya Neyman Sitanggang, Imas S. Siti Aslimah Siti Zubaidah Slamet Widodo Slamet Widodo sri murtini . SRI RAHAYU Sri Rahayu Sri Rahmatul Laila Sri Supraptini Mansjoer Suharti, Sri Sukarman Sukarman SULISTIYANI SULISTIYANI Sulistiyani Sulistiyani SULISTIYANI SULISTIYANI Sulistiyani, Sulistiyani Sumiati . Sumiati . Sumiati . . Sumiati Sumiati SYAHRIAL SYAHRIAL Syamsul Arifin Taher, Achmad Taniasari, Mila TARUNI SRI PRAWAST MIEN KAOMINI ANY ARYANI DEDY DURYADI SOLIHIN Teguh Wahyono Tiurma Pasaribu Triansyah, Irvan Walberto Sinaga Wasmen Manalu Waterman, James O. Widya Hermana Wirdateti . Yuli Retnani