Judul: Kualitas Papan Partikel Beremisi Formaldehida Rendah dari Limbah Inti Kenaf (Hibiscus cannabinus L.)
Abstrak: The objective of this research is to find out the optimum pMDI-UF mixing level and paraffin content. The optimum conditions were determined based on the physical and mechanical properties and formaldehyde emission of the produced particleboard. pMDI-UF mixing levels were 1 : 1; 1 : 2; 1 : 3; 1 : 4, and 0 : 1. The resin content level was 10% based on the kenaf core particle oven dry. Meanwhile, the paraffin contents were 0%, 2%, 4%, 6%, and 8%. The research results are as follows : 1) The best performance was resulted by core kenaf particleboard bonded by pMDI-UF 1 : 4 and 8% paraffin level, pMDI-UF 1 : 1 and 4% paraffin level, and pMDI-UF 1 : 4 and 4% paraffin level, respectively. The boards properties fulfill the JIS A 5908:2003 standard, except the modulus of elasticity (MOE) properties. pMDI – UF mixing level 1 : 1 and 4% paraffin level with those of 1 : 4 and 4% paraffin level release the lowest formaldehyde emission (0,4 mg/l) and fulfill the criteria F*** set up by JIS A 5908:2003. The produced core kenaf particleboard performed better quality compared to those of commercial particleboard and fiberboard.
Keyword: Particleboard, Core kenaf waste, Low emission formaldehyde, Perekat, Parafin

Judul: Kualitas Papan Partikel Core Kenaf (Hibiscus cannabinus L.) dengan Menggunakan Polipropilena Daur Ulang.
Abstrak: INTRODUCTION : Scarcity of raw materials for particleboard industry was occurred which is caused by the lack of wood supply that up till now comes from production functioned natural forest or planted forest. Wood supply from those areas has been decreased which is caused by less sustainable harvesting system and increasing of wood demands. Those conditions courage the ideas to find other ligno-cellulosed materials to replace wood; one of them are by using kenaf (Hibiscus cannabinus L.) core. Kenaf plant has been researched as substitute for particleboard raw material which composited by using formaldehyde adhesive (Puspita 2004; Susanta 2004; Ronaldi 2004). Utilization of formaldehyde adhesive has been appreciably produce negative impact to environment. To decrease negative impact from formaldehyde utilization, adhesive, which is used, could originate from plastic waste such as polypropylene which appreciable more eco-friendly, has high potential to be used, and produce better product dimensional stability. MATERIALS AND METHOD: Particleboard was made by mix kenaf (Hibiscus cannabinus L.) powder with polypropylene plastic. Mixture of those two materials consists of some kenaf powder/polypropylene mixture composition; those are 50:50, 40:60 and 30:70. Examined physical characters are density, moisture content, water absorption rate and thickness swelling rate. Examined mechanical characters are MOE, MOR, and screw holding power. RESULTS : From research results, utilization of kenaf powder/polypropylene mixture composition from 50:50 to 30:70 for particleboard production produce density, MOE, MOR and screw holding power with similar values. But, for physical character such as moisture content, water absorption rate and thickness swelling has different value, where the best kenaf powder/polypropylene mixture composition are 40:60 and 30:70.
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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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