Judul: Milk Production Model Development
Abstrak: Dalam upaya meningkatkan tingkat produksi susu dalam negeri, Indonesia mendatangkan sapi perah dari Eropa. Perbedaan iklim antara daerah asal dan Indonesia diperkirakan berpengaruh besar pada produksi susu. Penelitian ini bertujuan menghitung besar pengaruh keragaman iklim dan faktor lainnya terhadap produksi susu sapi perah dan menyusun model prediksi produksi susu. Penelitian dilakukan di Kabupaten Semarang di tiga lokasi yaitu Kecamatan Getasan (1081m mdpl), Kecamatan Tengaran (702 mdpl), dan Kecamatan Ungaran Barat (418 mdpl). Data produksi susu, pemberian pakan dan minum harian sapi perah dikumpulkan melalui pengukuran langsung pada 265 ekor sapi dari Maret hingga Mei 2023. Umur sapi diperoleh dari wawancara, data suhu dan kelembaban melalui pengukuran langsung dengan thermo-hygrometer. Metode penelitian menggunakan analisis regresi. Hasil penelitian menunjukkan bahwa peningkatan produksi susu sejalan dengan meningkatnya umur. Faktor umur dapat menjelaskan keragaman produksi susu sampai 80%. Lebih lanjut keragaman produksi susu berbagai tingkat umur dipengaruhi secara nyata oleh kondisi iklim yaitu tingkat kepanasan atau kelengasan udara (Temperature Humidity Index-THI) serta jumlah konsentrat dan jumlah minum yang diberikan. Faktor ini dapat menjelaskan keragaman produksi susu pada tingkat umur sampai 20%. Hasil ini menunjukkan bahwa hampir semua keragaman produksi susu dapat dijelaskan oleh umur dan pemberian pakan/minum serta THI. Secara umum kondisi lingkungan yang nyaman bagi ternak ialah wilayah yang memiliki THI kurang dari 72. Pada THI yang tinggi sapi akan mengalami stress dan produksi susu menurun., In an effort to increase the level of domestic milk production, Indonesia imports dairy cows from Europe. The difference in climate between the area of origin and Indonesia is expected to have major effect on milk production. This study aims to calculate the effect of climate variability and other factors on milk production of dairy cows and to develop a milk production prediction model. The research was conducted in Semarang Regency in three locations, namely Getasan Subdistrict (1081 mdpl), Tengaran Subdistrict (702 mdpl), and West Ungaran Subdistrict (418 mdpl). Data on milk production, daily feeding and drinking of dairy cows were collected through direct measurement on 265 cows from March to May 2023. Cow age was obtained from interviews, temperature and humidity data through direct measurement with a thermo-hygrometer. The research method used regression analysis.The results showed that milk production increased in line with increasing age. The age factor can explain the variability of milk production up to 80%. Furthermore, the varaibility of milk production at various ages was significantly influenced by climatic conditions, namely the level of heat or air humidity (Temperature Humidity Index- THI) as well as the amount of concentrate and the amount of drinking water given. This factor can explain up to 20% of the variation milk production at age level. These results indicate that almost all of the variability in milk yield can be explained by age and feeding/drinking and THI. In general, comfortable environmental conditions for livestock are areas with THI of less than 72. At high THI, cows will experience stress so that milk production will decrease.
Keyword: milk production, multiple linear regression analysis, sapi perah, Dairy Cows, THI

Judul: Hubungan antara Produksi dan Kualitas Susu Sapi Perah dengan Faktor yang Mempengaruhi (Studi Kasus di Pondok Ranggon, Jakarta Timur)
Abstrak: Dairy cows are the large ruminants that mostly kept by Indonesian dairy farmers. The dairy farms of Indonesia located not only in the villages, but also in the urban areas, such as Pondok Ranggon in East Jakarta. Recent study was done to observe effect of technical factors on milk production and quality of dairy farms in Pondok Ranggon in East Jakarta. The parameters were environmental conditions, feeding patterns, animal conditions, lactation performance, and milk quality. The data were analyzed using multiple regression analysis. To overcome less of roughage supply, farmers used agro-industry by products such as tofu waste, soybean waste, and rice bran. The averages of roughage, concentrate, tofu waste, soybean waste and rice bran that offered to the animals were 20,85±4,27; 0,67±0,73; 28,94±7,62; 2,26±4,51; and 0,01±0,09 kg/h/d, respectively. Under this feeding regime, the average milk produced was 9,28±3,22 kg/h/d. The averages of fat, lactose, protein, solid non fat, density of milk quality were 4,44%; 4,20%; 3,91%; 8,83%; and 1,032 g/ml. The relationship of milk production(Y) on roughage (X1), concentrate (X2), tofu waste (X3), soybean waste (X4) and rice bran (X5) was Y1=2,672X10,256 X20,014 X30,018 X4-0,008 X5-0,055. The influenced of age, number of lactation, lactation days, pregnancy and body weight on milk production and quality were also confirmed. It was concluded that maximum milk production in Pondok Ranggon was produced by the cows at 2,5 years age, in the first lactation, at the second months of lactation, from heavier cows, or in the non pregnant cows.
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Judul: Desain Gerbang Logika Kuantum Fredkin Multi- Kontrol Berbasis Gerbang Toffoli Melalui Superposisi Gerbang Elementer
Abstrak: Gerbang Fredkin dapat dimanfaatkan sebagai sel pembangun rangkaian fulladder untuk proses komputasi. Karena sifatnya yang reversibel, gerbang tersebut dapat dibuat dari sususan gerbang-gerbang elementer dengan basis gerbang Toffoli. Pada penelitian ini, penulis mencari desain dari gerbang Fredkin multi-kontrol berbasis gerbang Toffoli dengan mengkombinasikan tiga jenis gerbang elementer, yaitu CNOT, CV, dan CV†. Penelitian ini juga memperhitungkan jumlah gerbang elementer yang digunakan (quantum cost) dan jalur tambahan (ancillae input) dari desain-desain gerbang Fredkin yang dihasilkan. Dari hasil penelitian ditunjukkan bahwa gerbang Fredkin multi-kontrol dapat dibentuk oleh susunan tiga gerbang Toffoli multi-kontrol. Kemudian, gerbang-gerbang tersebut dapat direkonstruksi menjadi susunan gerbang-gerbang elementernya. Jumlah quantum cost dan ancillae input akan semakin besar seiring bertambahnya jumlah kontrol yang digunakan.
Keyword: Gerbang Fredkin multi-kontrol, gerbang Toffoli multi-kontrol, gerbang elementer