Acute Respiratory Infection (ARI) is an infectious disease. One of the performance indicators of infectious disease control and handling programs is disease discovery. However, the problem that often occurs is the limited number of medical analysts, the number of patients, and the experience of medical analysts in identifying bacterial processes so that the examination is relatively longer. Based on these problems, an automatic and accurate classification system of bacteria that causes Acute Respiratory Infection (ARI) was created. The research process is preprocessing images (color conversion and contrast stretching), segmentation, feature extraction, and KNN classification. The parameters used are bacterial count, area, perimeter, and shape factor. The best training data and test data comparison is 90%: 10% of 480 data. The KNN classification method is very good for classifying bacteria. The highest level of accuracy is 91.67%, precision is 92.4%, and recall is 91.7% with three variations of K values, namely K = 3, K = 5, and K = 7.

The research objective is to develop a monitoring system for the growth of red spinach plants based on image processing techniques from images captured using multiple cameras. The plant used is red spinach (Amaranthusgangeticus L.). Three cameras are installed in the top, side and front position of the plants in the photo box with lighting every 2 days up to 39 days. Model development uses a sample of 236 plants divided into 178 plants used model and 58 plants for model testing every two days. This model tested by the determination coefecient (R2) to measure how much the independent variables ability to explain the dependent variable. The network architecture were three input, first hidden layer (5 neurons), second hidden layer (5 neurons), and output layers with 1 neuron. ANN function with value of the learning level is 0.001. The activation function to predict fresh weight and leaf area of plants is tansig-logsig-tansig and tansig-tansig-logsig. ANN model can predict fresh plant weight with MSE value of 0.02385 and RMSE of 0.154, while for leaf area MSE value of 0.26428 and RMSE of 0.514.

The objective of this case study was to evaluate good lighting levels in laying hens. The data were collected for three months at UD. Mahakarya Farm Banyuwangi. A total of 4.400 heads of layer chicken were used in this study. The lighting intensityused were 15 lux in cage A and 10 lux in cage B. The average of egg production were75.91% and 73.57% for cage A (15 lux) and cage B (10 lux), respectively. The average of egg weight were 59.37 g and 59.23 gfor cage A (15 lux) and cage B (10 lux), respectively. The results of this study presented that layer chicken aged 25 weeks produced better production efficiency values by 10 lux. At the end of production period(38 weeks) increased production efficiency by 15 lux.

Jember Regency is one of the agropolitan center areas in East Java. The abundance production of plantation, livestock, and fishery as the agribusiness opportunities cannot be enjoyed maximally by the farmers, especially for those who live in the countryside. The long marketing channel makes the farmers to have no choice, so that they sell their crops to the traders and other busnissemen. The government of Jember Regency through the institutional approach tries to do a rural economy restructurisation through an Agribusiness Market development program. Regional approach with factorial analysis was used in this research to structure the complex problem by making the priority sequence of problems and the solutions in choosing a location which involved the participatory of all relevant stakeholders. The choice of an ideal location was a way to accommodate the parties' interests, various tactical-strategic objectives by considering several factors. Based on the sucsess determinant of the goal achievement, the following were the priority sequence of Agribusiness Market locations in Jember Regency: Bangsalsari District, Ajung Districts, Rambipuji District, and Gumukmas District.

Penelitian ini bertujuan untuk mengevaluasi karakteristik peternak terhadap tingkat keberhasilan inseminasi buatan (IB) di Kecamatan Nusawungu, Kabupaten Cilacap, Jawa Tengah. Karakteristik peternak yang diamati antara lain usia, tingkat pendidikan, pekerjaan, pengalaman beternak, dan tingkat kemampuan peternak dalam mendeteksi birahi sapi. Koleksi data primer dilakukan dengan metode survei menggunakan kuisioner dan data sekunder melalui data rekording dari dinas peternakan terkait. Metode pengambilan sampel menggunakan random sampling. Data yang terkumpul ditabulasi, diolah, dan disajikan secara deskriptif. Hasil penelitian menunjukkan bahwa mayoritas peternak berusia 41-60 tahun (50%), tingkat pendidikan SMA/SMK (46%), pekerjaan sebagai petani (60%), dan pengalaman beternak sekitar 6-10 tahun (53%). Tingkat kemampuan peternak dalam mendeteksi birahi sapi sebesar 74% melalui tanda-tanda berupa sapi gelisah, bersuara, menaiki ternak lain, dan/atau keluar lendir bening dari vulva sapi. Hasil penelitian dapat disimpulkan bahwa karakteristik peternak dapat menjadi salah satu faktor yang mempengaruhi tingkat kebuntingan sapi potong rakyat di Kecamatan Nusawungu Kabupaten Cilacap.