Judul: Karakteristik Biopelet Limbah Ampas Tebu dan Batang Singkong
Abstrak: Limbah ampas tebu (bagasse) dan batang singkong merupakan biomassa yang berpotensi menjadi alternatif bahan bakar terbarukan untuk memenuhi kebutuhan energi yang kian meningkat. Penelitian ini bertujuan untuk menganalisis karakteristik biopelet dan menentukan formulasi biopelet terbaik dari campuran limbah ampas tebu dan batang singkong. Pembuatan biopelet menggunakan pelletizer tipe rotary dies dengan perbandingan komposisi bahan baku yaitu A1 (100% serbuk batang singkong), A2 (100% limbah ampas tebu), A3 (20% limbah ampas tebu : 80% serbuk batang singkong), A4 (80% limbah ampas tebu : 20% serbuk batang singkong), A5 (50% limbah ampas tebu : 50% serbuk batang singkong), A6 (65% limbah ampas tebu : 35% serbuk batang singkong), A7 (35% limbah ampas tebu: 65% serbuk batang singkong). Penentuan biopelet terbaik berdasarkan pembobotan dengan tingkat kepentingan parameter dengan bobot tertinggi hingga terendah yaitu nilai kalor, kadar abu, kadar zat terbang, kerapatan, kadar air, dan laju pembakaran. Formulasi terbaik dari campuran kedua bahan baku berdasarkan SNI 8675-2018 didapatkan dari perlakuan A5 dengan rata-rata hasil uji kerapatan sebesar 0,60 g/cm³, kadar air 8,29%, kadar zat terbang 77,63%, kadar abu 4,10%, kadar karbon terikat 9,98%, nilai kalor 17,40 MJ/kg, keteguhan 96,55%, laju pembakaran 3,57 kg/jam, serta suhu pembakaran 761°C., Sugarcane bagasse and cassava stems are biomass waste which have potential as alternative renewable fuels by converting it into biopellets. This research aims to analyze the characteristics of biopellets made from a mixture of sugarcane bagasse and cassava stems waste, and determine the best formulation based on SNI no 8765-2018. A rotary dies type pelletizer has been used to produce the pellets. Pellets formulation was represented by the ratio of raw material composition, they were A1 (100% cassava stem powder), A2 (100% sugarcane bagasse waste), A3 (20% sugarcane bagasse waste : 80% cassava stem powder), A4 (80% bagasse waste : 20% cassava stem powder), A5 (50% sugarcane bagasse waste : 50% cassava stem powder), A6 (65% sugarcane bagasse waste : 35% cassava stem powder), A7 (35% sugarcane bagasse waste : 65 % cassava stem powder). Determination of the best biopellets is based on the scoring with the level of lightness of the parameters with the highest to lowest score is calorific value, ash content, volatile matter content, density, moisture content, and combustion rate. The best formulation obtained from A5 composition (50% bagasse and 50% cassava stem) with average density of 0,60 g/cm³, water content of 8,29%, volatile matter content of 77,63%, ash content of 4,10%, bound carbon content of 9,98%, calorific value 17,40 MJ/kg, durability 96,55%, and combustion rate 3,67 kg/hour, combustion temperature 761°C.
Keyword: biomassa, biopelet, bagasse, batang singkong, pelletizer

Judul: Study of Biopellet Formulation Based on Albasia Wood Powder with a Mixture of Straw and Rice Husk Charcoal
Abstrak: Serbuk kayu albasia dan limbah padi merupakan salah satu sumber bahan bakar alternatif potensial berasal dari biomassa yang dapat dimanfaatkan menjadi biopelet sebagai solusi pemanfaatan limbah. Tujuan penelitian ini adalah menganalisis dan mengetahui karakteristik biopelet berbahan dasar serbuk kayu albasia dengan campuran jerami dan arang sekam serta mengetahui komposisi formulasi terbaik dari bahan dasar biopelet tersebut sebagai energi bahan bakar alternatif. Pembuatan biopelet menggunakan pelletizer tipe fixed dies dengan perbandingan formulasi bahan baku yaitu A0 (arang sekam 90% : perekat 10%), A1 (jerami padi 90% : perekat 10%), A2 (serbuk kayu albasia 90% : perekat 10%), A3 (serbuk kayu albasia 25% : jerami 25% : arang sekam 40% perekat 10%), A4 (serbuk kayu albasia 25% : jerami 40% : arang sekam 25% : perekat 10%), dan A5 (serbuk kayu albasia 40% : jerami 25% : arang sekam 25% : perekat 10%). Perlakuan terbaik biopelet diperoleh pada komposisi serbuk kayu albasia 90% dan perekat 10% berdasarkan nilai kadar air 10,62%, kadar abu 1,83%, dan kerapatan apparent 0,725 g/cm3 yang memenuhi standar SNI 8675:2018. Nilai kalor dari biopelet tersebut yaitu 17,16 MJ/kg., Albasia sawdust and rice waste are potential alternative fuel sources derived from biomass that can be used as biopellets as a solution for waste utilization. The purpose of this study was to analyze and determine the characteristics of biopellets made from albasia wood powder with a mixture of straw and husk charcoal and to determine the composition of the best formulation of these biopellets as alternative fuel energy. Making biopellets using a fixed dies type pelletizer with a ratio of raw material formulations, namely A0 (90% husk charcoal : 10% adhesive), A1 (90% rice straw : 10% adhesive), A2 (90% albasia wood powder : 10% adhesive), A3 (25% albasia wood powder : 25% straw : 40% husk charcoal : 10% adhesive), A4 (25% albasia wood powder : 40% straw : 25% husk charcoal : 10% adhesive), and A5 (40% albasia wood powder : 25% straw : 25% husk charcoal : 10% adhesive). The best treatment for biopellet was obtained at the composition of 90% albasia wood powder and 10% adhesive based on the value of water content of 10,62%, ash content of 1,83%, and apparent density of 0,725 g/cm3 which meet the standards of SNI 8675:2018. The calorific value of the biopellet is 17,16 MJ/kg.
Keyword: albasia sawdust, biopellet, fixed dies pelletizer, husk charcoal, rice straw

Judul: Implementation of Spatio-Temporal Change Query in Relational Database.
Abstrak: Geographic object changes in various views. Object changes are recorded using a model of static storage. No historical connection between old version data and new version data has been built. For that, a storage model of spatio-temporal queries that can analyze spatio-temporal changes has been developed. The object changes the geometry are grouped according to the taxonomy of Spatio-Temporal Pattern Change. This research has been able to apply the query patterns change including born, expand, merge, contract, split, normal and die. This query based on geometric (area) changes. The implementation of spatio-temporal change queries represents an object changes continuously with easy, change detection is done by comparing two versions of data. Keyword: spatio-temporal change query, spatio-temporal change pattern.
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