Judul: Analysis of Provision and Commercialisation Perception of Fibre Feed in Rural Dairy Farms in Lembang - West Bandung District
Abstrak: Penelitian ini bertujuan untuk mengetahui sumber pakan serat yang biasanya digunakan, menganalisis kegiatan penyediaan pakan serat di peternakan sapi perah Lembang pada musim kemarau, mengetahui rantai pasok pakan serat, menganalisis nilai tambah usaha peternakan, mengetahui minat beli peternak terhadap pakan serat, serta mengetahui faktor peternak dan pilihan jenis pakan dalam pembelian pakan serat. Wawancara dilakukan kepada 50 peternak untuk memperoleh informasi pola penyediaan, rantai pasok pakan serat, dan nilai tambah usaha peternakan. Metode survei secara purposive digunakan dalam mengetahui persepsi peternak terhadap komersialisasi pakan serat dengan responden sebanyak 100 peternak. Pengambilan sampel berupa pakan serat yang digunakan di peternakan tersebut menggunakan teknik pengambilan acak sederhana. Data yang diperoleh dianalisis secara deskriptif. Pakan serat yang diberikan kepada sapi perah berupa rumput budi daya, tumbuhan alam, legum, dan limbah tanaman yang seluruhnya berasal dari daerah sekitar (≤ 30 km) dengan kandungan nutrien yang bervariasi. Terdapat 16 pola penyediaan pakan serat pada musim kemarau dengan pola terbanyak yaitu kombinasi mengarit di lahan sendiri dan membeli. Berdasarkan perhitungan RFV, legum dan limbah sayuran memiliki kualitas yang baik. Rantai pasok pakan serat relatif pendek (1–4 aktor) karena pakan serat yang digunakan umumnya dalam bentuk segar dan tanpa diolah. Rataan nilai tambah (Rp1324 kg-1) dan keuntungan usaha peternakan (Rp820.82 kg-1) memiliki nilai positif walaupun dengan pemberian pakan serat yang berbeda-beda. Sebagian besar peternak rakyat sapi perah di Kecamatan Lembang memiliki persepsi baik terhadap komersialisasi pakan serat (96%). Rumput gajah menjadi pilihan terbesar dalam pembelian pakan serat yang akan dibeli oleh peternak (62%). Kualitas merupakan faktor utama keputusan peternak dalam pembelian pakan tersebut (33%)., This study aims to explore and understand the source of fibre feed that is frequently utilised, analyse the activities of fibre feed provision in dairy farms during the dry season, investigate the fibre feed supply chain, analyse the valueadded characteristic of dairy farms, to understand the perceptions of dairy farmers in Lembang District regarding their interest in purchasing fibre feed, and to explore the choice of feed types as well as factors in determining the purchase of fibre feed by the farmers. The data was collected by adopting an interview method with 50 farmers to gather information regarding the provision pattern, supply chain of respective fibre feed, and value-added of dairy farms. The purposive sampling method was implemented in this study with a sample of 100 farmers to understand the perceptions of dairy farmers regarding fibre feed commercialisation. The fibre feed sample in the dairy farms was taken using a simple random sampling technique. The data acquired was analysed using descriptive analysis. The result implied that the fibre feed that had been given to the dairy cows was cultivated grass, natural grass, legumes, and plant residue that entirely supplied from neighbourhood area (≤ 30 km), which had different nutrient content. There were 16 provision patterns of fibre feed in the dry season, the vast majority of provision pattern was the combination of foraging from the farmer’s land and feed purchasing. By referring to the RFV calculations, legumes and vegetable waste have good quality. The fibre feed supply chain was relatively short, which was about (1–4
Keyword: fibre feed, perception, provision pattern, supply chains, value added

Judul: Ketersediaan Serat Efektif dan Kandungan Tanin Ransum Sapi Perah pada Peternakan Rakyat di Lembang serta Pengaruhnya Terhadap Produksi dan Kualitas Susu
Abstrak: Fiber is one of the important nutrients in the diet, especially for ruminants because fiber is a source of energy for the rumen microbes. Availability fiber is an important factor in the formulation of feed for ruminants because of shortage and excess fiber would affect the health of ruminants. This study aims to determine the feed materials used and the adequacy of nutrients, especially fiber effectively given to cattle. This research was carried out by conducting exploratory interviews and sampling of feed materials. Data were collected in five villages with each village consists of 6 breeder. Preparation of rations for ruminants is currently expected not only by BK, CP and TDN but also by fibers mainly NDF and ADF. NDF and ADF content of feed materials ranging from 26.45% - 92.13% and 22:44% - 54.51%, with the total number of awarding NDF and ADF in the ration of 65.33% and 38.57%. Variations in the content of NDF and ADF on feed materials resulting from forage sources used are also varied, especially in the dry season, so that farmers are using agricultural waste as a substitute source of fiber from grass. Agricultural waste contains anti-nutritional tannins especially when excessive aka damage the health of livestock. Tannin content ranging from 0.03%, feed ingredients - 2:43% with tannins in the ration of 0.023%. NDF and ADF content of the ration exceeds the needs of dairy cows which led to reduced energy density and can reduce production. Tannin content in the diet is very small so it does not interfere with the health of livestock.
Keyword: fiber, tanin, Neutral Detergent Fiber, Milk Cow, Lembang

Judul: Quantum Convolutional Neural Network (QCNN) for Classification Brain Tumor MRI Image
Abstrak: Penelitian ini bertujuan untuk mengembangkan model deteksi tumor otak menggunakan citra MRI dengan metode Quantum Convolutional Neural Network. Data yang digunakan adalah citra MRI otak yang terdiri dari citra tumor otak glioma, meningioma, hipofisis, dan negatif tumor yang dibagi kedalam data latih dan uji dengan rasio 80:20. Selanjutnya data latih dilakukan penyeimbangan dengan teknik oversampling. Dilakukan pengembangan model untuk mendeteksi tumor otak (biner), dan juga model untuk mengklasifikasikan jenis tumor otak (multiclass). Parameter yang digunakan dalam pengembangan model adalah jumlah ukuran filer = 2 dan kedalaman = 4, dengan qubit 4, dan dilatih dengan jumlah epoch sebanyak 10. Data akan diproses dengan metode Quantum Convolutional Neural Network yang terdiri dari lapisan quantum convolution, lapisan flatten, dan lapisan dense. Model multiclass mendapatkan akurasi 52%, setelah data latih diseimbangkan akurasi model meningkat menjadi 62%, sedangkan model biner mendapatkan akurasi 88%, setelah data latih diseimbangkan akurasi model meningkat menjadi 89%.
Keyword: Citra MRI, Klasifikasi Citra, QCNN, Tumor Otak