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The purpose of this paper aims to investigate micro enterprises financing in Indonesia and examines how this financing differs, depending on the enterprise’s development stage. This research also identifies some structural problems related to micro-financing and provides workable solutions.

This research uses the entrepreneurial network model of Schutjens and Stam (2003) to examine how Indonesian micro and small enterprises (MSEs) evolve even before they become regular small businesses. Content analysis is used on 10 micro-enterprises from Jakarta, the capital city of Indonesia and its surroundings. Financing issues at each stage of enterprise development are identified and deeply examined.

This research not only confirms the significant financing problems micro-enterprises face but also clarifies that these problems are unique to each stage of the MSEs’ development. One insight is that most micro-enterprises do not use funding from formal institutions. That is, business owners rely more on funding from non-formal institutions. This is because these enterprises’ managers generally cannot prepare loans application and/or they are lack of knowledge/training on financing matters. They hesitate to borrow from formal financial institutions, as the rates are high but the processing time is longer than those of the loan sharks.

This research contributes to the field of entrepreneurial finance by identifying the structural problems inherent in micro-finance and providing workable solutions for overcoming these problems.

Digital documentation techniques of tunneling excavations at archaeological sites are becoming more common. These methods, such as photogrammetry and LiDAR (Light Detection and Ranging), are able to create precise three-dimensional models of excavations to complement traditional forms of documentation with millimeter to centimeter accuracy. However, these techniques require either expensive pieces of equipment or a long processing time that can be prohibitive during short field seasons in remote areas. This article aims to determine the effectiveness of various low-cost sensors and real-time algorithms to create digital scans of archaeological excavations.

The authors used a class of algorithms called SLAM (Simultaneous Localization and Mapping) along with depth-sensing cameras. While these algorithms have largely improved over recent years, the accuracy of the results still depends on the scanning conditions. The authors developed a prototype of a scanning device and collected 3D data at a Maya archaeological site and refined the instrument in a system of natural caves. This article presents an analysis of the resulting 3D models to determine the effectiveness of the various sensors and algorithms employed.

While not as accurate as commercial LiDAR systems, the prototype presented, employing a time-of-flight depth sensor and using a feature-based SLAM algorithm, is a rapid and effective way to document archaeological contexts at a fraction of the cost.

The proposed system is easy to deploy, provides real-time results and would be particularly useful in salvage operations as well as in high-risk areas where cultural heritage is threatened.

This article compares many different low-cost scanning solutions for underground excavations, along with presenting a prototype that can be easily replicated for documentation purposes.