Judul: Aktivitas antibakteri ekstrak daun dan bunga kitolod (laurentia longiflora (L). Peterm) terhadap beberapa bakteri penyebab konjungtivitas
Abstrak: Leaf and flower Kitolod (Laurentia longiflora (L). Peterm) have been used by Indonesian community as a traditional medicine to treat eye disease such as red eye (conjunctivity). The aim of this study was to test antibacterial activity of leaf and flower ethanol extracts of kitolod against Staphylococcus aureus, Streptococcus pneumonia and Pseudomonas aeruginosa, and to identify the compound of those extracts responsible for the antibacterial activity. Preparation of ethanol extract of kitolod leaf and flower was carried out by maceration with 70% ethanol. Antibacterial activity from those extracts was analyzed by agar diffusion methode using paper disc and chloramphenicol 20% as a positive control. The antibacterial compounds of those extracts were identified by GCMS (Gas Chromatography Mass Spectrometer) pyrolisis. The results of this study showed that ethanol extracts of kitolod leaf and flower inhibited Staphylococcus aureus with inhibition zone diameter are 19,33 mm and 15,66 mm respectively. However, the extracts could not inhibit Streptococcus pneumonia and Pseudomonas aeruginosa. The minimum inhibitory concentration (MIC) of the extracts was determined by the dilution methode using paper disc. Minimum inhibitory concentration values of the ethanol extract of kitolod leaf and flower was 25 mg/ml. The compounds of ethanol extract of kitolod leaf showing antibacterial activity were fatty acid and their derivatives (chloro acetic acid, acetic acid, and palmitic acid); acetophenone; benzyl alcohol; 6 methyl-5-hepten-2-ol; 2,3-dehydrobenzofuran; flavonoid (aesculetin and 4 ethenyl 2 methoxy phenol) and Heptanal. While compounds responsible for antibacterial activity of ethanol extract of kitolod flower were fatty acid and its derivatives (stearic acid, palmitic acid, methyl palmitate, myristic acid, lauric acid, acetic acid, and heptadecane-(8) carbonic); Nitroform; acetophenone; 4 ethenyl 2 methoxy phenol; Levoglucosan; xanthosine; styrene; 2,3-butanediol and 2,3-dihydro benzofuran.
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Judul: Antibacterial Activity and Identification of Bioactive Compounds from Mangkokan Leaf Extract (Polyscias scutellaria)
Abstrak: Tanaman mangkokan (Polyscias scutellaria) merupakan salah satu tanaman obat Indonesia yang biasanya dimanfaatkan sebagai obat tradisional, tanaman hias, tanaman pagar, dan sumber pangan. Ekstrak daun mangkokan mengandung senyawa dengan aktivitas antibakteri. Penelitian ini bertujuan menguji aktivitas antibakteri ekstrak daun mangkokan, serta mengidentifikasi senyawa bioaktif yang terkandung dalam ekstrak. Ekstraksi daun mangkokan dilakukan menggunakan pelarut metanol, etanol, etil asetat, dan n-heksana. Ekstrak diuji aktivitas antibakteri dan diidentifikasi senyawa bioaktifnya menggunakan GC-MS. Hasil uji antibakteri menunjukkan bahwa ekstrak metanol dan etanol memiliki aktivitas antibakteri terhadap Staphylococcus aureus, Escherichia coli, Pseudomonas aeruginosa, dan Bacillus subtilis. Ekstrak n-heksana hanya memiliki aktivitas antibakteri terhadap E. coli, sedangkan ekstrak etil asetat tidak menunjukkan aktivitas antibakteri. Berdasarkan hasil analisis GC-MS, semua ekstrak daun mangkokan mengandung senyawa bioaktif dengan aktivitas antibakteri. Penelitian lebih lanjut diperlukan untuk menampilkan potensi antibakteri ekstrak daun mangkokan secara lebih baik., The mangkokan plant (Polyscias scutellaria) is one of the Indonesian medicinal plants which are usually used as a traditional medicine, ornamental plant, hedge plant, and food source. Mangkokan leaf extract contain antibacterial activity compounds. This study aims to examine the antibacterial activity of mangkokan leaf extract, as well as to identify the bioactive compounds contained in the extract. Mangkokan leaf extraction was carried out using methanol, ethanol, ethyl acetate, and n-hexane solvents. The extracts were tested for antibacterial activity and the bioactive compounds were identified using GC-MS. The results of the antibacterial test showed that the methanol and ethanol extracts had antibacterial activity against Staphylococcus aureus, Escherichia coli, Pseudomonas aeruginosa, and Bacillus subtilis. The n-hexane extract only had antibacterial activity against E. coli, while the ethyl acetate extract did not show antibacterial activity. Based on the results of GC-MS analysis, all mangkokan leaf extracts contained bioactive compounds which have antibacterial activities. Further research is needed to reveal the antibacterial potential of mangkokan leaf extract.
Keyword: Antibacterial, Bioactive compounds, mangkokan leaf extract

Judul: Peramalan Curah Hujan dengan Model ARIMA (Autoregressive Integrated Moving Average) dan VECM (Vector Error Correction Model).
Abstrak: Peramalan curah hujan diperlukan untuk memprediksi curah hujan pada periode berikutnya. Penelitian ini menggunakan 2 (dua) model peramalan yaitu model ARIMA (Autoregressive Integrated Moving Average) dan VECM (Vector Error Correction Model). ARIMA merupakan model peramalan yang berdasarkan pada data deret waktu peubah amatan itu sendiri sebagai pembentuk modelnya. VECM merupakan model peramalan yang melibatkan 1 (satu) atau lebih data deret waktu peubah penjelas sebagai pembentuk modelnya. Berdasarkan model ARIMA, model yang terpilih sebagai model terbaik adalah ARIMA (1, 1, 2). Validasi model dari data pengujian pada model ARIMA (1, 1, 2) berdasarkan MAD dan RMSE sebesar 14.06 dan 17.29. Pada VECM, peubah penjelas yang digunakan yakni suhu, kelembaban, dan lama penyinaran. Berdasarkan VECM (1) yang diperoleh, terdapat dua hubungan terhadap perubahan curah hujan, yakni hubungan jangka panjang dan jangka pendek. Pada hubungan jangka panjang, perubahan curah hujan dipengaruhi oleh curah hujan dan lama penyinaran masing-masing 1 (satu) periode sebelumnya. Pada hubungan jangka pendek, perubahan curah hujan hanya dipengaruhi oleh perubahan lama penyinaran 1 (satu) periode sebelumnya. Validasi VECM (1) dari data pengujian berdasarkan MAD dan RMSE sebesar 13.46 dan 16.81. Sehingga pada penelitian ini, VECM (1) dapat lebih baik meramalkan curah hujan dibanding model ARIMA (1, 1, 2).
Keyword: curah hujan, model ARIMA, VECM