Uji Coba Resin Penukar Ion Indion 225 H sebagai Adsorben pada Penurunan Kadar Kromium di Dalam Air Limbah
Bibliographic record
Abstract
ABSTRACT Chromium is extensively used in the leather tanning process, with only 60 - 70% utilized, leaving the remainder as waste. Effective waste management is essential to mitigating environmental impact. This study aims to conduct tests and understand the effectiveness of Indion 225 H as an adsorbent for removing chromium from wastewater by analyzing variables such as the mass of adsorbent per wastewater volume and contact time. The study seeks to optimize chromium removal and develop a mathematical model to explain the adsorption process. Experiments were conducted using a batch system with adsorbent masses ranging from 0.1 to 0.6 grams per 20 ml of wastewater and contact time from 3 to 5 hours. Results indicate that Indion 225 H can reduce chromium content in the solution by 33%, with optimal conditions being a contact time of 5 hours and adsorbent chromium content in the solution by 33%, with optimal conditions being 0.6 grams per 20 ml of wastewater. The Langmuir Isotherm model accurately describes the adsorption phenomena, and the adsorption kinetics follow a second-order model. ABSTRAK Gambut tropis memiliki nilai ekologis tinggi bagi ekosistem global, dan keberlangsungannya bergantung pada keterlibatan masyarakat. Dukungan masyarakat merupakan elemen penting keberhasilan pengembangan ekowisata di Kesatuan Hidrologi Gambut (KHG) Kahayan-Sebangau. Tidak hanya sebagai penerima manfaat, masyarakat berperan menjaga ekosistem. Dukungan dapat diwujudkan melalui partisipasi aktif dalam perencanaan dan pelaksanaan ekowisata. Partisipasi tersebut bermanfaat di bidang ekonomi, sosial, maupun ekologis seperti keberlangsungan ekowisata, mencegah potensi konflik, dan degradasi lingkungan. Penelitian ini meneliti faktor-faktor ekonomi, sosial, dan lingkungan yang memengaruhi dukungan masyarakat lokal terhadap pariwisata ekologis di lahan gambut Kalimantan Tengah. Penelitian menggunakan pendekatan metode campuran yang menggabungkan data kualitatif dan kuantitatif digunakan, dan dianalisis melalui partial least squares-structural equation modeling (PLS-SEM). Temuan penelitian menunjukkan dampak ekonomi dan sosial berpengaruh signifikan terhadap dukungan masyarakat, ketika dampak lingkungan memoderasi hubungan yang terjadi. Dampak ekonomi positif meliputi peningkatkan lapangan kerja, pendapatan masyarakat, dan pembangunan infrastruktur pariwisata. Secara sosial meliputi peningkatan interaksi dan program pemberdayaan masyarakat. Namun, ada juga dampak negatif seperti pembangunan yang tidak seimbang, konflik antar masyarakat, dan degradasi lingkungan. Data dikumpulkan melalui wawancara dan kuesioner kepada 100 masyarakat lokal, jawaban menggunakan skala Likert dan responden mewakili berbagai kelompok umur, tingkat pendidikan, dan sektor pekerjaan. Analisis menunjukkan validitas konvergen dan diskriminan terpenuhi dengan nilai loading factor >0,708 dan nilai average variance extraction (AVE) >0,5. Model penelitian memenuhi kriteria fit standardization root mean square (SRMR) <0,1. Kesimpulan penelitian bahwa dukungan masyarakat lokal sangat bergantung pada dampak ekonomi, sosial, dan lingkungan. Mengembangkan ekowisata yang memperhatikan ketiga aspek tersebut dapat meningkatkan kesejahteraan masyarakat dan kelestarian lingkungan.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".