Electronic Theses and Dissertation

Minyak nilam adalah minyak atsiri yang dihasilkan dari tanaman nilam melalui proses penyulingan uap. Salah satu penghasil minyak nilam terbaik berasal dari Aceh. Minyak nilam memiliki permintaan yang tinggi di berbagai industri seperti kosmetik, parfum, sabun dan farmasi. Namun, tingginya permintaan mendorong sebagian pelaku usaha melakukan praktik pencampuran, salah satunya dengan minyak terpentin. Pencampuran tersebut dapat menurunkan kualitas dan kemurnian minyak nilam. Oleh karena itu, pengujian keaslian minyak nilam menjadi penting untuk menjamin mutu produk akhir. Salah satu parameter yang digunakan dalam menguji keaslian tersebut adalah indeks bias. Metode pengukuran indeks bias umumnya dilakukan secara konvensional, namun seiring berkembangnya teknologi near infrared reflectance spectroscopy (NIRS) mulai diterapkan karena bersifat cepat, non-destruktif, dan ramah lingkungan. Penelitian ini bertujuan untuk menguji kemampuan teknologi NIRS dengan metode principal component regression (PCR) dalam mendeteksi perubahan indeks bias pada minyak nilam yang telah dicampur dengan minyak terpentin serta menganalisis pengaruh penggunaan pre-treatment spektrum terhadap kualitas model prediksi yang dihasilkan.
Minyak nilam dan minyak terpentin digunakan sebagai bahan dalam penelitian. Minyak nilam diuji menggunakan gas cromatography and mass spectrometry (GC-MS) di Balai Riset dan Standardisasi (Baristand) Banda Aceh untuk mengetahui keasliannya. Kemudian minyak nilam dicampurkan dengan minyak terpentin untuk menghasilkan variasi sampel, total sampel dalam penelitian ini berjumlah 31 yang terdiri atas satu sampel minyak nilam, satu sampel minyak terpentin dan 29 sampel minyak campuran. Akuisisi spektrum dilakukan menggunakan FT-NIR Thermo Nicolet Antaris IITM. Pengukuran indeks bias menggunakan hand refractometer. Data yang diperoleh kemudian dimodelkan menggunakan metode principal component regression (PCR), serta menerapkan penggunaan pre-treatment derivative 1, mean normalize dan de-trending. Dalam proses pemodelan menggunakan software unscrambler® X Version 10.4.
Hasil penelitian ini menunjukkan: (1) Teknologi near infrared reflectance spectroscopy (NIRS) dengan metode principal component regression (PCR) berpeluang mampu mendeteksi perubahan indeks bias pada minyak nilam campuran minyak terpentin. (2) Penggunaan pre-treatment derivative 1 terbukti mampu meningkatkan kualitas model prediksi. Model terbaik diperoleh pada PC ke-18 dengan nilai koefisien korelasi (r) sebesar 0,86, koefisien determinasi (R²) sebesar 0,74, nilai RMSEC sebesar 0,0060, dan nilai RPD sebesar 2,0. Hasil ini menunjukkan bahwa model yang dibangun tergolong prediksi kuantitatif (quantitative-based prediction).

Patchouli oil is an essential oil obtained from the distillation of patchouli plants. One of the best varieties is produced in Aceh. Patchouli oil has a high demand in various industries such as cosmetics, perfume, soap, and pharmaceuticals. However, the high demand has led some producers to engage in adulteration practices, one of which involves mixing patchouli oil with turpentine oil. This mixing reduces the quality and purity of patchouli oil. Therefore, authenticity testing is important to ensure the quality of the final product. One parameter used in testing authenticity is the refractive index.The refractive index is generally measured using conventional methods. However, with technological advancements, near infrared reflectance spectroscopy (NIRS) has begun to be applied because it is fast, non-destructive, and environmentally friendly. This study aims to examine the capability of NIRS technology combined with the principal component regression (PCR) method to detect changes in the refractive index of patchouli oil adulterated with turpentine oil. It also aims to analyze the effect of applying spectral pre-treatment on the quality of the resulting prediction model. Patchouli oil and turpentine oil were used as materials in this research. The authenticity of the patchouli oil was verified using gas chromatography–mass spectrometry (GC–MS) at the Research and Standardization Center (Baristand) in Banda Aceh. The patchouli oil was then mixed with turpentine oil to produce a range of sample variations. A total of 31 samples were prepared, consisting of one patchouli oil sample, one turpentine oil sample, and 29 mixed samples. Spectral acquisition was carried out using an FT-NIR Thermo Nicolet Antaris IITM instrument. The refractive index was measured using a hand refractometer. The data obtained were modeled using the principal component regression (PCR) method. Pre-treatments such as first derivative, mean normalization, and de-trending were applied. The modeling process was performed using Unscrambler® X Version 10.4 software. The results of this study show that the near infrared reflectance spectroscopy (NIRS) technology combined with the principal component regression (PCR) method has potential to detect changes in the refractive index of patchouli oil mixed with turpentine oil. The use of the first derivative pre-treatment improved the quality of the prediction model. The best model was obtained at the 18th principal component (PC-18) with a correlation coefficient (r) of 0.86, a coefficient of determination (R²) of 0.74, a root mean square error of calibration (RMSEC) of 0.0060, and a residual predictive deviation (RPD) of 2.0. These results indicate that the developed model provides a quantitative-based prediction.