Judul: Developing Spatial Decision Tree using NBTree Algorithm for Hotspot Distribution in Riau.
Abstrak: One of environment problems that emerged almost every year in Indonesia is forest fire in many regions including Riau. Forest fires cause negative impacts to the environment, such as transboundary haze pollution, health and life problem, and material damages. This phenomenon effects not only on community in Riau but also in neighbor coutries such as Singapore and Malay. Hotspot distribution is important for preventing occurrence of forest and land fire. Hotspot distribution data can be analyzed using spatial data mining techniques. One of techniques in spatial data mining is spatial decision tree. Spatial decision tree will build classifier from spatial data that can be used to create classification rules. This research aimed to develop classifier to predict the amount of hotspot in a territory according to several thematic layers: industrial timber plantation, logging concession, and land use. This research uses spatial join index and complete operator to provide a spatial dataset in which the conventional spatial decision tree algorithm can be applied to the data set. Then, NBTree algorithm will be used to develop a spatial decision tree. The result of this research is a classifier that contains 17 classification rules with accuracy 68,35%. Keywords: spatial decision tree, spatial join index, complete operator, NBTree algorithm
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Judul: Klasifikasi Data Spasial untuk Kemunculan Hotspot di Provinsi Riau Menggunakan Algoritme ID3
Abstrak: Forest fire is one of the environmental issues that occurs almost every year in Indonesia including in Riau Province, which causes negative impacts for human life. The large data of hotspot distribution can be analyzed using one of spatial data mining techniques, namely spatial decision tree. The purpose of this research is to classify the hotspot occurences in Riau province in order to obtain the classification rules. In this research, the spatial decision tree is developed using ID3 algorithm. The result shows that the highest accuracy is 70.80%. The classification model consists 125 classification rules that can be used to predict the hotspot occurrences.
Keyword: spatial decision tree, hotspots, classification, ID3 Algorithm

Judul: Penetapan Umur Simpan Telur Asin Rendah Kolesterol pada Penyimpanan Suhu Ruang
Abstrak: Pemanfaatan telur bebek sebagai bahan pangan salah satunya yaitu telur asin. Namun, muncul kesadaran masyarakat akan tingginya kandungan kolesterol pada telur asin sehingga dikembangkan inovasi telur asin rendah kolesterol. Produk telur asin di pasaran memiliki umur simpan pendek tetapi belum diidentifikasi parameter penentu kerusakan produk. Penelitian ini bertujuan untuk mengetahui perubahan mutu dan menetapkan umur simpan telur asin selama penyimpanan suhu ruang. Penelitian ini dilakukan dengan membuat telur asin kemudian dilakukan pengemasan vakum, lalu disimpan hingga terjadi kerusakan pada suhu ruang. Penentuan umur simpan dilakukan dengan metode extended storage studies berdasarkan parameter kadar air, pH, kadar kolesterol, kecerahan, organoleptik, serta uji total plate count. Hasil karakteristik penyimpanan hari ke-10 telur asin diperoleh nilai tingkat kecerahan putih telur sebesar 25,96, kecerahan kuning telur 25,98, pH 7,19, kadar air putih telur 84,64%, kadar air kuning telur 38,72%, dan total mikroba 4,1 × 105 cfu/mL. Kadar kolesterol sebesar 233,39 mg/100 g pada hari pertama dan mengalami penurunan menjadi 131,61 mg/100 g pada hari kesepuluh. Mutu telur asin mengalami perubahan yang mengarah pada kerusakan selama penyimpanan suhu ruang. Telur asin tanpa kemasan memiliki umur simpan hingga 9 hari dengan total mikroba sebesar 1,0 x 105 cfu/mL., The utilization of duck eggs as a food ingredient includes salted eggs. However, public awareness of the high cholesterol content in salted eggs has led to the development of low-cholesterol salted egg innovations. Salted egg products in the market have a short shelf life, but the determining parameters for product spoilage have not been identified. This research aims to understand the quality changes and establish the shelf life of salted eggs during room temperature storage. The study involves producing salted eggs, vacuum packaging them, and then storing them at room temperature until spoilage occurs. The determination of the shelf life is based on extended storage studies, considering parameters such as moisture content, pH, cholesterol content, brightness, organoleptic, as well as a total plate count test. The characteristic results after 10 days of storage show that the brightness of the egg whites is 25.96, the brightness of the egg yolks is 25.98, pH is 7.19, the moisture content of egg whites is 84.64%, the moisture content of egg yolks is 38.72%, and the total microbial count is 4.1 × 105 cfu/mL. The cholesterol content decreases from 233.39 mg/100 g on the first day to 131.61 mg/100 g on the tenth day. The quality of salted eggs undergoes changes that lead to spoilage during room temperature storage. Unpackaged salted eggs have a shelf life of up to 9 days with a total microbial count of 1.0 x 105 cfu/mL.
Keyword: Duck eggs, Low cholesterol, Salted eggs, Shelf life