Judul: Penerapan Structural Equation Modeling – Partial Least Square dan Analisis Mediasi dalam Menentukan Faktor yang Mempengaruhi Indeks Pembangunan Manusia di Indonesia
Abstrak: Structural Equation Modeling (SEM) adalah analisis multivariat yang menggabungkan analisis faktor dan regresi, sehingga memungkinkan peneliti untuk melihat hubungan antara variabel laten dan indikatornya serta hubungan antara variabel laten. Partial Least Square adalah pendekatan soft modeling pada SEM yang tidak memiliki asumsi sebaran data dan jumlah minimal amatan yang sering disebut dengan PLS SEM. Data yang digunakan pada penelitian ini adalah data provinsi di Indonesia sehingga jumlah amatan penelitian ini adalah 34 amatan. Jumlah amatan ini terlalu kecil dan tidak memenuhi asumsi kenormalan data sehingga metode analisis yang digunakan adalah PLS SEM. Penelitian ini menerapkan PLS SEM untuk mengidentifikasi faktor-faktor yang mempengaruhi Indeks Pembangunan Manusia berdasarkan data provinsi di Indonesia. Indeks Pembangunan Manusia terdiri dari tiga dimensi, yaitu Ekonomi, Pendidikan, dan Kesehatan yang akan digunakan sebagai variabel laten yang mempengaruhi Indeks Pembangunan Manusia secara langsung dan secara tidak langsung. Hasil dari penelitian ini menunjukkan bahwa Ekonomi dan Kesehatan mempunyai pengaruh langsung yang signifikan sedangkan Pendidikan memiliki pengaruh tidak langsung yang signifikan terhadap Indeks Pembangunan Manusia yang dimediasi oleh variabel laten Ekonomi. Model yang diuji dalam penelitian ini dievaluasi mengunakan nilai Q2 sebesar 67% yang mengindikasikan bahwa model yang dibangun cukup baik dalam menjelaskan keragaman dari Indeks Pembangunan Manusia.
Keyword: partial least square, human development index, latent variable

Judul: Application of Structural Equation Modeling – Partial Least Square and Mediation Analysis in Determining Factors of Human Development Index in Indonesia.
Abstrak: Structural Equation Modeling (SEM) is a class of multivariate techniques that combine aspects of factor analysis and regression, enabling the researcher to simultaneously examine relationships among measured variables and latent variables as well as between latent variables. Meanwhile, partial least square is soft modeling approach to SEM without any assumptions about data distribution and minimal number of observation that often called as PLS SEM. Data that used in this research are the province’s data in Indonesia that has 34 provinces. The number of observation that equals to 34 observations is too small and could not fulfill the maximum likelihood estimation of SEM. In this research, the estimation method used was PLS, so the analysis called PLS SEM. This research used the PLS SEM to identify the factors that influence the human development index based on the province’s data in Indonesia. Human Development Index consists of three dimensions, which are Economy, Education, and Health that used as latent variables that influence the human development index direct and indirectly. The result of this research show that Economy and Health influence the Human Development Index directly significant. Education influences Human Development Index indirectly with partial mediation that mediated by Economy. The model in this research is evaluated by Q2 value that equals to 67% so the model obtained from this research was good enough In explaining the variance of Human Development Index.
Keyword: partial least square, human development index, latent variable

Judul: Detoxification of Cassava’s Acid Hydrolyzate by Activated Carbon Method for Bioethanol Production
Abstrak: Cassava is one of natural resources for carbohydrate that also available for bioethanol production. Starch and fibers hydrolysis maybe conducted on acid condition. The restriction in acid hydrolysis is 5-hydroxymethyl furfural (HMF) and furfural formation, which inhibit yeast fermentation. This study applied two stages of detoxification, which are overliming and activated carbon adsorption methods for lowering HMF and furfural concentrations. In order to obtain tolerable amount in sugar solution, detoxification by activated carbon adsorption was done by concentration of 1%, 2.5%, 5% and 10% and duration of contact are 30 45 and 60 minutes. The results showed that overliming method decreased HMF and furfural concentrations 34.38% and 60.81%, respectively. Overliming followed by 5% activated carbon adsorption for 30 minutes produced the best sugar solution which has a lower HMF and furfural concentrations by 72.03% and 89.11%, respectively. Adsorption constants of HMF and furfural by 5% activated carbon were 0.044 g/min and 3,7 x 10-5 g/min, respectively. The concentration of ethanol produced was 5.00% (b/v) or 63.22% higher than obtained from detoxification by neutralization (NH4OH) which produced ethanol only 3.06%.
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