Livestock is a source of animal protein that contains essential acids that improve human intelligence and health. Popular livestock in Indonesia is cow. Consumption of meat per capita is increased by 0.1% kg / capita / year. The high demand for beef in Indonesia is due to the increasing of population in Indonesia by 1.49% per year. More than 90% of cows are reared by rural communities with less of knowledge about livestock and have low economic capabilities. In addition, the number of experts or veterinarians are also limited. One of the solutions that can be done to socialize the knowledge of experts or veterinarians is by using expert system. Some methods that can be used in expert systems are Bayesian network and Dempster-Shafer method. The purpose of this research is to analyze the comparison of cow disease diagnosis with bayesian network and Dempster-Shafer method. In order to know which method is better in diagnosing cow disease. The data used is 21 cow diseases with 77 symptoms. Each method is tested with the same 10 cases. The conclusions obtained by Bayesian network and Dempster-Shafer method. Both of methods give the same diagnosis results but with different percentage. The mean value of diagnosis percentage by Dempster-Shafer method is 87,2% while bayesian network method is 75,3%. Thus, it can be said that the Dempster-Shafer method is better at diagnosing cow disease.

Increasing computing power is now achieved by replacing the programming paradigm with parallel programming. Parallel computing is a method of solving problems by dividing the computational load into small parts of the computation sub-process. This study describes the comparative analysis of parallel computations in the Selection Sort and Radix Sort algorithms. The data used are in the form of whole numbers and decimal numbers totaling 100 to 2 million data. The test was carried out with three scenarios, namely using two processors, four processors, and 3 computers connected to each other via a LAN network. The results showed that the parallel Selection Sort algorithm for small data was better than the parallel Radix Sort. On the other hand, parallel Radix Sort is better for millions of data than Selection Sort.

This study aims to design and build a Field-Guide Application of Butterflies' Species at University of Lampung based on Android. This application is expected to be used as a means of information to determine the classification, family, local name, morphology, butterflies' food and the benefits of butterflies at University of Lampung. This study uses Waterfall Method and design of Unified Modeling Language (UML), as well as using Black Box Testing to test functional and application. Data in this study consisted of primary data including name of butterfly families, local names, butterfly images (caterpillar, butterfly), descriptions of butterfly species; and secondary data including information about the application, families, local names, butterfly images and descriptions of butterflies (sub-family, genus, species, wingspan, flying speed and food) at University of Lampung. This study uses 5 categories of families and 37 species of butterflies at University of Lampung.The result of the research shows: Equivalence Partitioning Testing result shows that the Application Butterfly of Unila is compatible with all Android OS versions with minimum requirements are 4.0 inch, 4.5 inch, 5.0 inch, 5.5 to 6 inch resolution and based on the classes tested, it indicates that Application Butterfly of Unila works properly. The average of user friendly user ratings obtained is 4.11 included in either category. The average assessment of the interactive variables obtained is 4.08 included in either category. The result of testing data based on user friendly and interactive variable indicates that the application is included in category of Good and tend to Very Good.

Kemampuan dan keterampilan guru baik menggunakan maupun mengadakan media pembelajaran dalam proses belajar mengajar di dalam kelas bukan lagi merupakan suatu hal yang dapat diabaikan, akan tetapi ini merupakan suatu keharusan, mengingat dalam era pembangunan pendidikan di masa sekarang dan mendatang bertitik tolak pada kualitas keluarannya. Tujuan dalam pelatihan ini untuk meningkatkan pengetahuan, kemampuan dalam membuat dan kemampuan dalam menggunakan media pembelajaran. Metode yang digunakan dalam pelatihan ada 2, yaitu: ceramah (40%) dan praktik (60%) dengan jumlah peserta sebanyak 65 orang guru.  Hasil pengabdian menunjukkan bahwa tingkat pemahaman berupa sikap, penguasaan, dan pembuatan media pembelajaran oleh peserta dilakukan dengan semangat yang ditunjukkan dari hasil post test yang memperoleh nilai yang baik para peserta sebanyak 65 orang atau 76,47%.

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Pengomposan ialah salah satu dari berbagai metode pengolahan sampah organik dimana bertujuan untuk mengurangi dan juga mengubah komposisi sampah menjadi produk yang bermanfaat. Artikel ini berupaya memberikan gambaran dan penjelasan terkait program kerja pembuatan pupuk kompos, meliputi proses, tahapan, hasil, dan manfaatnya. Penulisan artikel ini menggunakan pendekatan kualitatif dengan dengan model deskriptif-eksplanatif. Hasilnya, masyarakat menerima pemahaman dan wawasan baru dalam hal pemanfaatan limbah rumah tangga. Selain itu, masyarakat dapat mengurangi penggunaan pupuk kimia dan pupuk buatan pabrik yang umumnya sudah digunakan oleh masyarakat desa, sehingga dapat meminimalkan pengeluaran masyarakat petani desa dalam proses bercocok tanam. Artikel ini terbatas pada pelaksanaan KKN Mandiri Putra Daerah Periode 1 2021. Artikel ini juga berkontribusi dalam keilmuan pertanian serta praktik dan strategi pengimplementasian poin SDGs.

The importance of monitoring forest health is needed to support a sustainable forest management system. A healthy forest can be said to be still carrying out its functions. Monitoring the health of mangrove forests is helpful in an effort to mitigate coastal disasters. The purpose of this service was to provide knowledge and understanding to members of KTH Lestari Indah regarding forest health. This activity was carried out on Sunday, October 24, 2021, at the mangrove forest tour, Margasari Village, Labuhan Maringgai sub-district, East Lampung Regency. The methods used in this activity were lectures and practices. Based on the evaluation results with pre-test and post-test instruments given to participants regarding the material in service activities, participants experienced an increase in knowledge of 7.13%. This increase shows a reasonably good understanding of the training participants, so this training is expected to help the community increase knowledge and participation in mangrove forest management and discovery of sustainable mangrove forests.

<p><em>Tuberkulosis (TB atau TBC) merupakan salah satu penyakit infeksi yang disebabkan oleh Bakteri Mycobacterium tuberculosis. Bakteri tersebut merupakan bakteri yang sangat kuat sehingga dalam pengobatannya memerlukan waktu yang cukup lama. Pengobatan penyakit tuberkulosis dilakukan selama 6-9 bulan secara rutin dengan sedikitnya 3 macam jenis obat. Saat ini kebanyakan masyarakat menganggap batuk dalam jangka waktu berbulan-bulan merupakan batuk biasa, jika dicermati salah satu gejala yang ditimbulkan penyakit tuberkulosis, yaitu batuk dalam jangka waktu yang panjang. Pada penelitian ini digunakan data penderita tuberkulosis di Kota Bandar Lampung, data cuaca dan matrix jarak antara kejadian penderita tuberkulosis yang satu dengan kejadian yang lainnya dalam lingkup kecamatan. Jumlah dari keseluruhan data sebanyak 600 data dengan 44 variabel. Penelitian ini juga menggunakan 3 kernel yaitu, Linear, Gaussian, dan Polynomial dengan menggunakan Metode SVM dengan kernel Linear mendapatkan nilai rata-rata R² sebesar 51.43 %, pada percobaan dengan metode SVM dengan kernel Gaussian mendapatkan nilai rata-rata R² sebesar 58.53 % dan pada percobaan dengan metode SVM dengan kernel Polynomial mendapatkan nilai rata-rata R² sebesar 36.03 %.</em></p><p><strong><em>Kata Kunci</em></strong><em> : Prediksi penderita tuberculosis, tuberculosis, Machine Learning, Support Vector Machine.</em></p><p class="Abstrak"><em>Tuberculosis (TB / TBC) is one of infectious disease caused by Mycobacterium tuberculosis bacteria. These bacteria are very strong bacteria so for the treatment takes a long time. Tuberculosis treatment is carried out for 6-9 months regularly with at least 3 types of drugs. Currently, most of people consider a cough for months is a common cough, if looked by one of the symptoms caused by tuberculosis, which is a cough for a long time. In this research, data on tuberculosis patients in the city of Bandar Lampung were used, weather data and the distance matrix between the case of tuberculosis patients with other case within the district. The total number of data is 600 data with 44 variables. This research also uses 3 kernels</em><em> </em><em>namely, Linear, Gaussian, and Polynomial by using the SVM method with the Linear kernel getting an average R² value of 51.43%, in the experiment with the SVM method with a gaussian kernel getting an average R² value of 58.53% and at Experiments with the SVM method with the Polynomial kernel obtained an average value of R² of 36.03%</em><em> .</em></p><p class="Abstrak"><strong><em>Keywords</em></strong><em> : Prediction of tuberculosis sufferers, tuberculosis, Machine Learning, Support Vector Machine.</em></p>