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Record W2418179244 · doi:10.14203/metalurgi.v26i2.12

PELUANG PENELITIAN UNTUK MEMPERBAIKI TEKNOLOGI PROSES UNTUK MENGOLAH BIJIH NIKEL LATERIT KADAR RENDAH INDONESIA[

2015· article· id· W2418179244 on OpenAlexaboutno aff
Puguh Prasetiyo

Bibliographic record

VenueMetalurgi · 2015
Typearticle
Languageid
FieldEngineering
TopicMining Techniques and Economics
Canadian institutionsnot available
Fundersnot available
KeywordsPhysicsHumanitiesPolitical scienceForestryGeographyArt

Abstract

fetched live from OpenAlex

Indonesia kaya dengan SDA (Sumber Daya alam) bijih  nikel oksida yang  lazim disebut  laterit. Laterit berkadar nikel tinggi saprolit (Ni>1,8%) sudah diolah dengan jalur proses pirometalurgi di Sulawesi Tenggara untuk memproduksi ferro nikel (FeNi) oleh PT Aneka Tambang di Pomalaa, atau untuk memproduksi Ni-matte oleh Vale INCO di Soroako. Laterit berkadar nikel rendah yang terdiri dari limonit dan saprolit dengan Ni<1,8 %, belum diolah di tanah air. Untuk  mengolahnya digunakan proses Caron atau proses HPAL/PAL (HighPressure Acid Leaching). Dimana kedua proses tersebut termasuk jalur proses hidrometalurgi. Pemerintah telah memberi ijin kepada pihak asing untuk mengolah laterit kadar rendah pulau Gag Papua dengan proses Caron pada PT Pasific Nickel USA pada tahun 1967 (menjelang awal Orde Baru). Akibat harga minyak dunia yang naik secara dramatis setelah 1973, maka PT Pasific Nickel membatalkan rencananya dan mengembalikan ijin ke pemerintah. Ijin juga diberikan pada dua PMA (Penanaman Modal Asing) pada Januari 1998 (menjelang akhir Orde Baru) untuk mengolah laterit kadar rendah dengan proses HPAL/PAL, yaitu PT BHP Australia untuk mengo lah laterit pulau Gag Papua, dan PT Weda Bay Nickel (WBN) Canada untuk mengo lah laterit teluk Weda Halmahera.  Dalam perjalanan waktu PT WBN Canada dimiliki Eramet Perancis sejak Mei 2006, dan sampai saat ini (2011) tidak ada kepastian kapan PT WBN Eramet Perancis merealisasikan proyeknya. Sedangkan PT BHP Australia mengembalikan ijin pulau Gag ke pemerintah pada awal tahun 2009. Kenyataan mundurnya tiga (3) PMA dari Indonesia untuk mengo lah laterit kadar rendah dengan jalur proses hidrometalurgi. Bisa menjadi peluang bagi pemerintah untuk menguasai sebagian teknologi yang akan digunakan oleh pihak asing untuk mengolah  laterit  kadar  rendah.  Penguasaan  teknologi tersebut  diperoleh  dari aktifitas  penelitian,  dan  hasil penelitian dipatenkan. Dengan demikian diharapkan pemerintah bisa punya posisi tawar untuk meningkatkan kepemilikan saham dengan pihak asing. Apabila di kemudian hari ada pihak asing yang berminat mengolah laterit pulau Gag Papua dan wilayah lain di Kawasan Timur Indonesia. Atas dasar penjelasan diatas maka dibuat tulisan ini Abstract The low grade laterite (limonite and saprolite with Ni < 1.8 %) has not yet processed in Indonesia. It uses process hydrometallurgy. The government of Indonesia has been give permission to foreign company to process the low grade laterite with hydrometallurgy (Caron process and HPAL process). Process Caron is used to process laterite Gag island Papua for PT Pasific Nickel USA on 1967. The dramatical increase price of fuel oil after 1973, it become PT Pasific Nickel give up plan and it give back the permission to the government. Process HPAL (High Pressure Acid Leaching) are used to process laterite teluk Weda (Weda Bay) Halmahera for PT Weda Bay Nickel (WBN) Canada and Gag island Papua for BHP Australia. Two companies got the permission on last new era on January 1998. The permission of Gag island Papua is returned by BHP Australia on first year 2009 and the uncertainity when PT WBN Eramet France (PT WBN Canada takes over by Eramet on May 2006) to build HPAL plant. It becomes opportunity to control the part of technology to process the low laterite via research. So the government has bargaining position to increase share at foreign company.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.355
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.042
GPT teacher head0.242
Teacher spread0.201 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2015
Admission routes1
Has abstractyes

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