Lindi merupakan salah satu permasalahan lingkungan yang timbul seiring dengan banyaknya timbulan sampah. Warna gelap lindi yang disebabkan oleh senyawa biologis menjadi salah satu parameter pencemar pertama yang dapat diidentifikasi. Oleh karena itu, diperlukan adanya alternatif teknologi untuk mengolah lindi. Adsorpsi merupakan proses yang efektif dalam penyisihan polutan. Penelitian ini bertujuan untuk menganalisis pengaruh parameter operasional proses adsorpsi dan menganalisis kondisi optimum proses adsorpsi untuk penyisihan warna lindi. Proses optimasi pada penelitian ini dilakukan menggunakan Response Surface Methodology dengan desain Box Bhenken. Sampel lindi diambil dari TPA Cipayung Depok. Powdered Activated Carbon (PAC) dengan luas permukaan BET sebesar 528,2 m2/g, total volume pori sebesar 0,4469 cm3/g, dan rata-rata ukuran atau radius pori sebesar 1,655 nm digunakan sebagai adsorben. Response Surface Methodology desain Box Bhenken digunakan dengan tiga level dan tiga faktor berupa konsentrasi polutan (250 – 4600 Pt-Co), konsentrasi adsorben (1 – 10 g/L), dan pH (4 – 8) sebagai variabel bebas serta penyisihan warna sebagai variabel tetap (respon) pada proses adsorpsi lindi. Hasil penelitian menunjukkan bahwa penyisihan warna pada proses adsorpsi meningkat seiring dengan peningkatan konsentrasi adsorben (r = 0,841) serta penurunan konsentrasi polutan (r = -0,292) dan pH (r = -0,168). Hasil dari model regresi kuadratik orde dua diperoleh koefisien determinasi R2 sebesar 0,9816 untuk mengoptimasi proses adsorpsi. Nilai optimum penyisihan warna mencapai 98% pada kondisi konsentrasi polutan 250 Pt-Co, konsentrasi adsorben 10 g/L, dan pH 6. Berdasarkan uji konfirmasi yang dilakukan selama 3 kali, didapatkan hasil aktual eksperimen yang sesuai dengan nilai prediksi dari model (desirability = 1). Analisis statistik serta kedekatan hasil prediksi dan aktual menunjukkan model yang diperoleh dapat digunakan dalam pengoptimalan kinerja proses adsorpsi melalui parameter opersionalnya. Hasil penelitian ini dapat menjadi solusi bagi pengolahan lanjutan lindi.

---

Leachate is one of the environmental problems that arise along with the amount of waste that generated. The dark color of leachate caused by biological compounds usually become one of the key parameters in pollutant that can be identified. Therefore, it is necessary to have an alternative technology to treat leachate. Adsorption is an effective process in pollutant removal. This study aims to analyze the effect of the operational parameters of the adsorption process and to analyze the optimum condition of the adsorption process for the removal of leachate color. The optimization process in this study was carried out using the Response Surface Methodology with the Box Bhenken design. The leachate samples were taken from the landfill site TPA Cipayung Depok. Powdered Activated Carbon (PAC) with a BET surface area of ​​528.2 m2/g, a total pore volume of 0.4469 cm3/g, and an average pore size or radius of 1.655 nm were used as adsorbent. Response Surface Methodology Box Bhenken design was applied with three levels and three factors of pollutant concentration (250 – 4600 Pt-Co), adsorbent concentration (1 – 10 g/L), and pH (4 – 8) as independent variables with color removal as a dependent variable (response) in the leachate adsorption process. The results showed that the color removal in the adsorption process increased along with the increasing in adsorbent concentration (r = 0.841) and a decrease in pollutant concentration (r = -0.292) and pH (r = -0.168). The result of second-order quadratic regression model obtained a coefficient of determination R2 of 0.9816 to optimize the adsorption process. The optimum value of color removal reached 98% under conditions of pollutant concentration of 250 Pt-Co, adsorbent concentration of 10 g/L, and pH 6. The confirmation test which was carried out for 3 times revealed the actual experimental results that obtained in accordance with the predicted value of the model (desirability = 1). Statistical analysis as well as the proximity of the predicted and actual results showed the obtained model could be used in optimizing the adsorption process performance through its operational parameters. The results of this study can be a solution for advance leachate treatment.