ACADSTAFF UGM
| Judul/Title | Coal Rank Data Analytic for ASTM and PSDBMP Classification |
| Penulis/Author | Dr. Mardhani Riasetiawan, SE Ak, M.T. (1) ; Prof. Dr. Ir. Ferian Anggara, S.T., M.Eng., IPM. (2); Vanisha Syahra (3); Prof. Dr. Techn. Ahmad Ashari, M.I.Kom. (4); Drs. Bambang Nurcahyo Prastowo, M.Sc. (5); INNEKE CYNTHIA K (6); PRABOWO WAHYU SUDARNO (7) |
| Tanggal/Date | 1 2023 |
| Kata Kunci/Keyword | |
| Abstrak/Abstract | Massive production of coal in Indonesia becomes the background why big data is possible to be implemented in coal big data management and analysis. Big data can be a helpful way to transform the data technology, since it is quite impossible to do all analyses manually. Our study implemented the basic concept of big data: Big Data Management (BDM) and Big Data Analytic (BDA). We implemented the BDM concept in arranging the data structure, started from the ‘borehole’ information that provide a lot of information such as lithology, coal seam, coal thickness, etc. Calorific Value (adb) and Proximate and Ultimate Analysis were used to implement the BDA concept which is knowledge discovery to obtain the classification of the coal. We used the Python environment to produce the source code in order to automatically classify the coal according to Indonesian Coal Standardization (PSDBMP) and coal rank ASTM. We figured out according to the Indonesian Coal Standardization (PSDBMP), the calorific value (in adb) is dominated in low to medium calorie for 14 boreholes. The coal rank in ASTM analysis is dominated as Lignite A and B for 14 boreholes. For the last analysis according to the atomic ratio of VK diagram shown that the coal classified as in Lignite and Subbituminous Coal. Thus, by implementing big data concept, we can easily analyze the coal classification if we have huge amount of data |
| Rumpun Ilmu | Ilmu Komputer |
| Bahasa Asli/Original Language | English |
| Level | Internasional |
| Status |