Ensemble forecasting is one of relatively new modern methods for time series forecasting that employs averaging or stacking from the results of several methods. This paper focuses on the development of ensemble ARIMA-FFNN for climate forecasting by using averaging method. Two data about monthly rainfall in Indonesia, i.e. Wagir and Pujon region, are used as case study. Root mean of squares errors in training and testing datasets are used for evaluating the forecast accuracy. The results of ensemble ARIMA-FFNN are compared to one classical statistical method, i.e. individual ARIMA, and two modern statistical methods, namely individual FFNN and ensemble FFNN. The results show that ARIMA yields more accurate forecast in training datasets than other methods, whereas in testing datasets show that FFNN is the best method. Additionally, this conclusion in line with the results of M3 competition, i.e. modern methods or complex methods do not necessarily produce more accurate forecast than simpler one.
Cellulose plays an important role in the carbon cycle in nature and is the largest compound. This study aimed to isolate, to characterize and to determine actinobacteria that capable of producing cellulases. The sampling method in this study was carried out by purposive sampling at the outlet point of aeration pond of the wastewater treatment plant (IPAL) from palm oil waste station of PT. Teupin Lada. Isolation of actinobacteria was carried out on Humic Acid Vitamin b Agar (HVA), morphological characterization was carried out on Yeast Malt Agar (YMA), Yeast Starch Agar (YSA), Oatmeal Agar (OA), and microscopic characterization of actinobacteria and measuring the diameter of the clear zone formed on Carboxymethyl Cellulose (CMC) medium using the indicator Congo Red. Eight isolates were obtained from the isolation. Of the 8 isolates obtained, 7 of them were able to produce cellulase enzymes which were measured based on the clear zone formed in the test Congo Red on Carboxymethil Cellulose (CMC), and one isolate did not show any clear zones. The highest value of Cellulolytic Index (IS) was obtained from isolate ATLS-05, namely 8.38 mm. HIGHLIGHTS Cellulose plays an important role in the carbon cycle in nature and is the largest compound The high waste load especially palm oil mill effluent (Elaeis guineensis) or known as Palm Oil Mill Effluent(POME) could cause various problems for the environment and society. POME is wastewater from the palm oil industry, which is one of the most polluting agro-industrial wastes Actinobacteria are one of the soil microbes which have the greatest abundance and play an important role in the decomposition process. One of the roles of soil microbes is too degrading cellulose GRAPHICAL ABSTRACT
UJI PENYERAPAN CS-137 OLEH NANOKOMPOSIT. Penelitian ini dilakukan untuk mengetahui sifat penyerapan berbagai variasi nanokomposit magnet oksida besi dengan bentonit terhadap kontaminan radionuklida Cs-137 dalam larutan. Komposisi nanokomposit magnet oksida besi-bentonit divariasikan berdasarkan perbandingan berat dengan harga: 1 : 0 ; 3 : 1 dan 0 : 1. Penyerapan dilakukan dengan sistem bath, dimana 50 mg nanokomposit dimasukkan ke dalam 10 ml aquades sehingga membentuk suspensi. Larutan standar Cs-137 ditambahkan, sehingga konsentrasi setiap larutan kontaminan menjadi 100; 200; 300, 400; 500 dan 600 Bq/ml. Setelah digoyang selama 24 jam, partikel nanokomposit yang berupa suspensi dipisahkan dengan lempengan magnet. Laju cacah larutan awal dan Beningan diamati dengan Liquid Scintillation Counter (LSC). Penyerapan terbaik 52,0 – 68,21 % untuk nanokomposit dengan ratio oksida-besi bentonit 3 : 1 dan dikuti oleh nanokomposit dengan ratio 1 : 0 (25,85 – 33,07 %) dan nanokomposit dengan ratio 0 : 1 (05,98 – 11,28 %). Dapat disimpulkan bahwa baik oksida besi maupun bentonit dapat menyerap Cs-137 sedang untuk nano komposit yang mengandung oksida besi dan bentonit dapat meningkatkan kemampuan penyerapan Cs-137 yang terdapat dalam larutan. EXPERIMENT OF Cs-137 ABSORPTION BY NANOKOMPOSIT. The aim of this research is to get the absorption characteristics of various compositions of iron oxide magnetic nanocomposite and bentonite to Cs-137 radionuclide contaminant in a solution. The composition of iron oxide magnetic nanocomposite bentonit was varied by the weight ratio of iron oxide / bentonite were: 1 : 0 ; 3 : 1 and 0 : 1. Absorption was carried out by bath system which for 50 mg of nanocomposite was filled into 10 ml aquades until the suspension was formed. Standard solution of Cs-137 was added, so then the concentration (activity) of each solution were100; 200; 300, 400; 500 dan 600 Bq/ml. After the solution were shaked for 24 hours, nanocomposite particles in the suspension was separated using magnetic plate. Counting rate of the solution and effluent were analyzed by Liquid Scintillation Counter (LSC). The best absorption reach 52,90 to 68,21 % by nanocomposite with iron oxide / bentonit ratio 3 : 1, and followed by nanocomposite with ratio 1 : 0 (25,85 - 33,07 %) and nanocomposite with ratio 0 : 1 (05,98 – 11,28 %). It is concluded that either iron oxide or bentonite can absorb Cs-137 and then for the nanocomposite counting of iron oxide and bentonite can increase the absorption of Cs-137 in the solution.
Developing geotourism can improve the use of geological
capacity. It’s better in sustainability. Gunung Ireng is a tourist
destination located at Pengkok Village, Patuk DistrictGunungkidul Regency, Yogyakarta Special Province.
Geology of this area is known as a paleo-volcano with
complete features to be described as crater. People live
around it concern to preserve the geological condition. This
paper aimed to develop the Community-Based Geotourism.
Method used by training and mentoring activities, so that
local people able to maintain the management, advertising,
marketing and selling Gunung Ireng Geotourism. Results
described the community consists of government, nongovernment and private sectors. Those partners mostly able
to support various initiatives. Positive correlation between
the carrying capacity and the visitor rights and guide
obligations is defined. A high expectation to the positive
impact of the community-based geotourism into the unique
geodiversity preservation, economic improvement, and
socio-cultural diversity can be achieved
Minyak dan gas bumi dapat diambil secara langsung melalui sumur-sumur yang dibuat, namun sumur-sumur tersebut tidak akan menghasilkan jumlah minyak dan gas bumi yang konstan setiap hari. Ketika kandungan minyak dan gas mulai turun maka yang harus dilakukan adalah memberikan treatment terhadap sumur tersebut, sehingga minyak dan gas yang masih terkandung di dasar bumi bisa naik dengan jumlah yang lebih banyak. Tujuan dilakukannya penelitian ini adalah untuk membantu perusahaan dalam menganalisis jumlah produksi minyak dan gas bumi selama periode 14 hari selanjutnya, sehingga dapat diketahui apakah selama periode 14 hari selanjutnya diperlukan treatment terhadap sumur. Data yang digunakan adalah jumlah produksi minyak dan gas bumi pada platform “MK” pada tahun 2015. Pemodelan jumlah produksi minyak dan gas bumi dilakukan menggunakan tiga metode, yaitu ARIMA, neural network , dan Hibrida ARIMA- neural network . Hasil yang diperoleh berdasarkan analisis ketiga metode tersebut adalah pada jumlah produksi minyak bumi model terbaik diperoleh dari metode hibrida ARIMA- neural network , dengan hasil ramalan yang cenderung sama selama 14 hari yaitu 1961 barel. Sedangkan jumlah produksi gas bumi model terbaik diperoleh dari metode neural network , dengan ramalan produksi untuk 14 hari selanjutnya cenderung meningkat.
Prosiding Peran Isotop dan Radiasi untuk Indonesia yang Berdaya Saing Padalah buku yang mengumpulkan 27 karya ilmiah dari 32 pemakalah yang telah mempresentasikan karya ilmiahnya pada Seminar Nasional APISORA yang diselenggarakan pada tanggal 8 November 2021 di Pusat Riset Teknologi Aplikasi Isotop dan Radiasi (PRTAIR), Organisasi Riset Teknologi Nuklir (BATAN), Badan Riset Inovasi Nasional (BRIN). Pemakalah berasal dari berbagai institusi/universitas dan berbagai latar belakang kepakaran. Buku ini akan memberikan manfaat bagi para peneliti dan akademisi lainnya, serta menjadi acuan dalam melakukan kegiatan penelitian dan pengembangan aplikasi isotop dan radiasi di Indonesia.
Indonesia adalah bagian dari cincin api dunia, yang hal itu telah berlangsung sejak umur Tersier. Salah satu gunung api yang dibentuk oleh cincin api itu berada di sepanjang Pegunungan Selatan Jawa Tengah – Yogyakarta yang ditunjukkan dengan melimpahnya batuan gunung api menyusun Formasi Kebobutak, Semilir dan Nglanggeran. Di daerah Gunung Ireng Desa Pengkok (Kecamatan Patuk-Kabupaten Gunungkidul) tersingkap dengan baik batuan-batuan gunung api tersebut. Penelitian geologi gunung api telah dilakukan dengan tujuan untuk mengidentifikasi fasies gunung api yang membentuk Gunung Ireng. Metode penelitian yang digunakan adalah analisis stratigrafi batuan gunung api dan geomorfologi detail. Hasil penelitian telah berhasil mengetahui komposisi litologi yang menyusunnya, yaitu retas andesit, lava berstruktur meniang berkomposisi andesit, aglomerat dan breksi andesit. Secara stratigrafi, batuan-batuan itu memiliki hubungan antara yang satu dengan yang lain saling menjari, bahkan intrusi retas pun nampak sebagai bagian yang tak terpisahkan dengan lava, aglomerat dan blocky-breccia. Analisis stratigrafi dan geomorfologi berhasil mengidentifikasi Gunung Ireng adalah bagian dari fasies pusat, yang di dalamnya terdapat bagian tubuh pipa kepundan bagian atas, kubah lava, dan intrusi retas.
Gunung Ireng geosite is an excellent geoheritage that is also a part of the Gunungsewu UNESCO Global Geopark in Pengkok, Gunungkidul Regency. It is widely recognized as an experiential leisure tour destination with the sunrise, sunset, and milky way watching as its activities. The primary attraction is the natural museum of Tertiary submarine paleo-volcanic miniature that was developed during the Early Miocene (±20-23 million years ago). Mentoring in utilizing the resources is necessary. The local community has agreed to develop geotourism as an effort to conserve the cultural, biotic, and geological environment. The certified instructors or mentors and professionals used mentoring methods to increase the local community’s abilities in preparing, managing, and evaluating the geotourism, including management, advertisement, marketing, guidance, web hosting, culinary, and accommodations.. The results are the status of the geoheritage area (by the Ministry of Energy and Mineral Resources No. 13 K.HK.01.MEM.G.2021), the viral of the local Gunung Ireng’s Spot Festival, the local culinary facilities, the CHSE certificate, as well as up to 300% increase in visitors per month before the pandemic and 200-300% increase during the pandemic. Other results that have successfully developed the supporting attractions are the Ahad Pon traditional market, the footsteps flashback of the great da'wah Sunan Kalijogo on Gunung Ireng and the Geological Natural Track of the Ancient Volcano of Gunung Ireng. Those three attractions are the efforts to improve the local community's economy, nature, and cultural conservation as the solid implementations of geotourism activities. Qualitatively, these various efforts are now starting to show impacts, with the increased motivation of the community to focus more on developing this destination, and the increasing attention of local governments to support these conservation activities, although quantitatively it has not to be measured yet.
This paper investigates the ability of a least-squares support vector machine (LSSVM) model to improve the accuracy of streamflow forecasting. Cross-validation and grid-search methods are used to automatically determine the LSSVM parameters in the forecasting process. To assess the effectiveness of this model, monthly streamflow records from two stations, Tg Tulang and Tg Rambutan of the Kinta River in Perak, Peninsular Malaysia, were used as case studies. The performance of the LSSVM model is compared with the conventional statistical autoregressive integrated moving average (ARIMA), the artificial neural network (ANN) and support vector machine (SVM) models using various statistical measures. The results of the comparison indicate that the LSSVM model is a useful tool and a promising new method for streamflow forecasting.
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