Judul: The Effect of Coal Ash and Lignite enriched Compost on the Biological Properties of Ultisols in Central Lampung
Abstrak: Organisme tanah berperan penting terhadap kesuburan tanah. Sumber energi yang digunakan untuk mendukung kehidupan organisme tanah yaitu bahan organik. Pemanfaatan pembenah tanah berupa kompos, abu batubara (fly ash dan bottom ash) atau sering disingkat FABA dan lignit merupakan solusi alternatif untuk memberdayakan organisme tanah. Bahan pembenah tanah berupa kompos diperkaya FABA dan lignit dapat mempengaruhi tingkat aktivitas mikrob dan makro fauna tanah. Penelitian ini bertujuan mengetahui pengaruh pemberian bahan pembenah tanah terhadap kesuburan biologi tanah, yaitu mikrob tanah, respirasi tanah dan cacing tanah. Pembenah tanah kompos, kompos+FABA (75:25), dan kompos+FABA+lignit (70:20:10) masing-masing sebanyak 50 ton/ha diberikan secara palir (P) dan tebar merata (T) pada Ultisol. Hasil pengamatan didominasi oleh total mikrob tanah. Perlakuan yang menghasilkan jumlah total mikrob tanah dan respirasi tanah paling tinggi adalah perlakuan kompos+FABA-palir (KF-P). Hasil perlakuan yang menghasilkan jumlah cacing tanah paling tinggi adalah kompos+FABA-tebar (KF-T), sedangkan biomassa cacing tanah tertinggi pada perlakuan kompos-tebar (K-T). Hasil uji korelasi dan regeresi menghasilkan pengaruh positif antara sifat biologi tanah (populasi mikrob dan respirasi tanah) dan sifat-sifat kimia tanah yang meliputi C-organik, pH tanah, dan N-total. Pemberian pembenah tanah berupa kompos diperkaya FABA dan lignit, dengan teknik aplikasi tebar dan palir memberikan pengaruh baik terhadap populasi mikrob dan fauna tanah. Pembenah tanah yang diaplikasikan secara palir memberikan asupan nutrisi yang lebih baik.
Keyword: earthworm, FABA, soil microbes, row treatment, soil respiration

Judul: Amelioration of Compost and Coal Ash on an Ultisol of Pineapple Plantation: Temporal Dynamics of Soil Chemical Properties
Abstrak: Kendala utama sifat kimia Ultisols untuk pertanian meliputi rendahnya pH, bahan organik, KTK, dan ketersediaan hara. Penelitian ini bertujuan mengevaluasi dinamika temporal sifat kimia tanah pada 0, 2, 6, 9, dan 10 bulan setelah ameliorasi (BSA) kompos dan abu batu bara (FABA) pada Ultisol di lahan perkebunan nanas. Penelitian terdiri dari percobaan lapang dan percobaan perkolasi di rumah kaca dengan RAL, keduanya terdiri dari 6 taraf perlakuan yaitu kontrol, kompos 50 ton/ha (KT 50), Kompos+FABA 50 ton/ha (KFT 50), KFA 25, KFA 15, dan KFA 5, T= tebar dan A=alur. Selain amelioran ini, tanah juga dipupuk lengkap. Analisis dengan metode rutin dilakukan terhadap sifat-sifat kimia tanah lapisan 0-20 cm pada 0 dan 2 BSA dari percobaan lapang, pada 9 dan 10 BSA dari percobaan perkolasi, dan pada 6 BSA berdasarkan ekstrapolasi. Perlakuan berpengaruh sangat nyata. Secara umum, sifat-sifat kimia tanah terbaik diperoleh pada perlakuan KFA 25. Kadar hara semakin turun dengan waktu akibat proses pencucian. Pada perlakuan terbaik 10 BSA, kadar C-organik, N-total dan KTK tanah lebih tinggi dari kadar awal meskipun masih tergolong rendah, sedangkan P-tersedia juga lebih tinggi dari kadar awal dan tetap tergolong sangat tinggi. Namun, kadar K-dd, Cadd, dan Mg-dd lebih rendah dari kadar awal dan tetap tergolong sangat rendah. Untuk mempertahankan produktivitas tanaman, maka disarankan untuk memberikan pupuk N dan K serta ameliorasi kompos dan FABA pada 10 BSA., The main chemical constraints of Ultisols for agriculture include low soil pH, organic matter, CEC, and nutrients availability. This study aims to evaluate temporal dynamics of soil chemical properties at 0, 2, 6, 9, and 10 months after amelioration (MAA) of compost and coal ash (FABA) on an Ultisol of pineapple plantation. The study consisted of field and greenhouse percolation experiments, both with CRD consisting of control, 50 ton/ha compost (CB 50), 50 tons/ha compost+FABA (CFB 50), CFR 25, CFR 15, and CFR 5 treatment levels, where B = broadcast and R = row application. Besides, the soil was completely fertilized. Chemical analyses were done using routine methods on soil samples of 0-20 cm layer at 0 and 2, 9 and 10, and 6 MAA, respectively from the field experiment, from the percolation experiment, and based on extrapolation. The treatment’s effects were very significant. In general, the best results were obtained at CFR 25 treatment level. The nutrient status decreased with time due to leaching processes. From the best treatment at 10 MAA, compared to the corresponding initial status, soil organic-C, total-N, and CEC were higher than, although still classified as low, whilst P-availability was also higher than, but still classified as very high. However, the soil exchangeable-K, -Ca, and -Mg were lower than the initial levels and still classified as very low. To maintain plant productivity, it is suggested to apply supplementary N and K fertilizers and compost and FABA ameliorants at 10 MMA.
Keyword: ameliorant, broadcast, leaching, percolation, row

Judul: Pemodelan Nilai Tukar Rupiah terhadap Dollar Amerika Menggunakan Deret Waktu Hidden Markov Empat Waktu Sebelumnya
Abstrak: The exchange rate of Rupiah to US Dollar fluctuates according to time in a long period. An existing exchange rate might happen again in the future. Assume that the causes of the fluctuation are not observed directly and form a Markov chain, then the exchange rate of Rupiah to US Dollar can be modeled by the hidden Markov time series. In this research, the model used to describe the exchange rate of Rupiah to US Dollar is the four previous time in hidden Markov time series. This model assumes that the exchange rate of Rupiah to US Dollar depends on Markov chain explained by the cause of occurence and the four previous exchange rates of Rupiah to US Dollar. The model parameter is estimated by using the maximum likelihood method, while the estimation itself is calculated using the expectation maximization algorithm, which is implemented using Mathematica. After estimating the parameter, the exchange rate of Rupiah to US Dollar are calculated. The results are as follows. The symmetric mean absolute percentage error (SMAPE) is 2,1%, the maximum absolute error is 19,16%, the minimum absolute error is 0,0036%, and only 1,95% of the whole absolute percentage error that is bigger than 10%. These results show that the four previous time in hidden Markov time series can describe the exchange rate of Rupiah to US Dollar very well.
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