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Current e-learning system is still in the form collection of online uniform material for individual access without guidance on how to learn from it effectively.  Such condition will not challenge smart students to learn deeper that force them to abandon the system.  To increase the quality of the system, intelligent e-learning must be used.  In this kind of system, it can personalize its users that the learning materials recommended to a student will be different from the ones recommended to others students based on their profiles.  Such system also offers curriculum sequence technology which enables the students to plan their own learning sequence.  Technologies that can be used to develop such system include: web mining, adaptive information filtering, intelligent collaborative learning, and semantic web

 E-learning is becoming an important tool in education.  Hence, more and more education institutions use it.  However, most of the e-learing systems used in most education institutions are the passive ones.  Passive here means that they cannot adapt to users’ need or in other words they cannot personalize its users and provide only what users need accordingly.  In order the system to be usefull to the users, it must be able to personalize them.  One form of personalization in intelligent e-learning is the ability to recommend learning materials that fit to their needs.  Such feature is called recommender.  This paper proposes an intelligent recommender system using Semantic Web which is able to recommend learning materials to users based on their interest. To guide the users in learning and understand fully on a specific topic, a subject network, which is a relationship among subject, is used.  The subject network will be presented in a list that suggests the order of learning

Typhonium flagelliforme (Lodd.) Blume), also known as Keladi tikus,  familia Araceae, is one of the restorative plant for anti cancer. This study was isolated and  identification of chemical compounds  from n-buthanol phase of the plant. This research is continued from previous research which is done by phytochemical screening, n-butanol phase was isolated using  column chromatography. The fractions were analyzed using TLC and the toxicity test using BSLT (Brine Shrimp Lethality Test). The fraction who have the smallest LC₅₀ value was identified by UV-VIS Spectrophotometer, FTIR Spectrophotometer and Gas Liquid Chromatography-Mass Spectrometer. The results showed the B.4.3.1 fraction is the most active fraction with LC₅₀ 209.89 ppm.Based on the result of GCMS, in the n-butanol phase of Typhonium flagelliforme (Lodd.) Blume) is guess contains flavonoid compounds as dihidroflavonol groups, flavon, isoflavon and auron. 

Keywords : isolation,  Typhonium flagelliforme (Lodd). Blume, n-butanol phase, BSLT, 

                   identification

Penelitian ini dilakukan untuk mengetahui aktivitas antioksidan hasil pengeringan semprot ekstrak n-heksana dan ekstrak methanol daun keladi tikus (Typhonium divaricatum (L) Decne menggunakan maltodekstrin dengan konsentrasi 35,40 dan 45% sebagai pengisi dan penambah kelarutan. Terhadap serbuk n-heksana dan metanol dilakukan uji aktivitas antioksidan menggunakan metode peredaman radikal bebas DPPH (1,1-difenil-2-pikrilhidrazil).  Hasil uji terhadap serbuk n-heksana  menggunakan maltodekstrin 35,40 dan 45% diperoleh nilai IC₅₀ berturut-turut 283,29 bpj, 167,99 bpj dan 121,15 bpj. Hasil uji terhadap serbuk metanol  menggunakan maltodekstrin 40,45 dan 55%  diperoleh nilai IC₅₀ berturut-turut adalah 58,78 bpj, 59,78 bpj dan 54,09 bpj. Dari hasil uji menunjukkan bahwa serbuk methanol memiliki nilai IC₅₀ lebih tinggi dibandingkan dengan serbuk n-heksana, tetapi lebih kecil dibandingkan dengan vitamin C sebagai kontrol dengan nilai IC₅₀ 7,59 bpj.

Kata kunci : keladi tikus (Typhonium divaricatum (L) Decne, maltodekstrin, pengeringan semprot, DPPH