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Abstrak :
Perhitungan persentase lemak tubuh manusia pria dewasa telah dimanfaatkan dalam berbagai disiplin ilmu. Perhitungan persentase lemak tubuh dikatakan baik jika mudah digunakan, tidak membutuhkan banyak waktu dan berbiaya rendah sehingga bisa digunakan secara luas oleh masyarakat. Perhitungan dengan melihat hubungan antara ukuran antropometri yang diperoleh secara akurat melalui proses 3D Anthroscan dan persentase lemak tubuh mampu memberikan alternatif perhitungan persentase lemak tubuh yang mewakili karakteristik antropometri pria dewasa Indonesia. Dalam studi kasus penelitian ini Persentase Lemak Tubuh = 0.71X89 – 0.712X109 + 0.374X78 – 0.19X38 +1.19 - 29.507 adalah perhitugan estimasi persentase lemak tubuh yang mempunyai potensi menjawab karakteristik antropometri pria dewasa Indonesia. Metode yang digunakan untuk menghasilkan perhitungan persentase lemak tubuh untuk pria dewasa Indonesia adalah regresi berganda. ......Study of Body fat has been implemented in several research fields. Body Fat Estimation will be considered as a good measurement if it has some requirements such as easy, fast and cheap so that body fat formula can be significantly used by people. Estimation which is generated by correlation of antrhropometry that is resulted through 3D Anthroscan and body fat can give alternative solution to represent Indonesian male body fat. In this study, Body Fat = 0.71X89 – 0.712X109 + 0.374X78 – 0.19X38 +1.19 - 29.507 potentially fit to Indonesian male anthropometry. Multiple Regression is used to generate Body fat estimation for Indonesian Male.

Abstrak :
Southeast Asia, as the world fastest growing market, has become the destination for multinational companies to operate their businesses. The increasing number of companies in the region will result in raised levels of CO2 emissions because of their transport and logistics activity. This paper aims to develop a CO2 emissions framework by considering the actual conditions of the region, and by calculating the level of emissions with a case study of Indonesia. Several steps were involved in the design of the framework. First, research was conducted on available frameworks which estimate CO2 emissions in logistics. Second, the model for CO2 emissions calculation was built by breaking down all the factors influencing calculations. Third, the model was applied using distribution network data of companies in Indonesia. The output of the research is a framework which helps companies to calculate CO2 emissions, and which gauges the level of such emissions generated by companies operating in Indonesia. In addition, the impact of the different distribution network scenarios on the amount of CO2 emissions produced is assessed.