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  1. Hidayat Y, Machmud A, Zulhuda S, Suartini S
    F1000Res, 2024;13:722.
    PMID: 40083803 DOI: 10.12688/f1000research.148322.3
    BACKGROUND: Indonesia currently could not make it to the top ten global halal due to some external and internal factors, although it is the largest Muslim country. In the external sector, the competition map is getting tougher, while internally, there are handicaps in the form of weak public awareness of competition. As a country with the largest Muslim population in the world, Indonesia can become one of the largest markets in the world. As indicated in the Global Islamic Economic Report (GIER), Indonesia is one of the top ten countries that control the Islamic economic market, yet it fails to dominate its Islamic market. Accordingly, the government needs to play a stronger role through regulatory policies to encourage the development of the Islamic economic ecosystem in Indonesia (halal value chain). The purpose of this study is to find out and analyse the existence of Micro, small, and medium enterprises (MSMEs) in Indonesia in the world's market for Halal products and Services.

    METHODS: The researchers have conducted a form of normative juridical research with the analytical descriptive method, namely by collecting, describing, analysing, and presenting what is ( das sein) and what ought to be ( das sollen).

    RESULTS: Support from the government and stakeholders has not been optimal in improving welfare - capital access, management, and halal certification, so the existence of the global halal ecosystem has not yet impacted MSMEs' ability to compete competitively.

    CONCLUSIONS: The conclusion of this study shows that the quadruple helix innovation system is capable of guaranteeing the development of MSMEs in a manner to achieves a high level of competitiveness - efficiency, and effectiveness of the products and services produced.

  2. Syukriani Y, Wulandari AS, Wanranto B, Hidayat Y
    Sci Justice, 2023 Mar;63(2):229-237.
    PMID: 36870702 DOI: 10.1016/j.scijus.2023.01.003
    The existence of the Chinese population in the predominantly Malay population in Indonesia can be traced back thousands of years, and it has been suspected that it played an essential role in the history of the Malay population origin in Maritime South East Asia. With the fact that the Malay-Indonesian population is currently predominant compared to the Chinese population in Indonesia (Chinese-Indonesian), the selection of the origin of the STRs allele frequency panel population becomes an issue in DNA profiling, including in paternity testing. This study analyses the genetic relationship between the Chinese-Indonesian and Malay-Indonesian populations and how this affects the Paternity Index (PI) ​​calculation in paternity test cases. The study of the relationship between populations was carried out using neighbour-joining (NJ) tree analysis and multidimensional scaling (MDS) on the allele frequency panel of 19 autosomal STRs loci of Malay-Indonesian (n = 210) and Chinese-Indonesian (n = 78) populations. Four population groups were used as references: Malay-Malaysian, Filipino, Chinese, and Caucasian. An MDS analysis was also performed based on the pairwise FST calculation. The combined Paternity Index (CPI) calculation was carried out on 132 paternity cases from the Malay-Indonesian population with inclusive results using a panel of allele frequencies from the six populations. The pairwise FST MDS indicates a closer relationship between the Chinese-Indonesian and Malay-Indonesian compared to the Chinese population, which is in line with the CPIs comparison test. The outcome suggests that the alternative use of allele frequency database between Malay-Indonesian and Chinese-Indonesian for CPI calculations is not very influential. These results can also be considered in studying the extent of genetic assimilation between the two populations. In addition, these results support the robustness claim of multivariate analysis to represent phenomena that phylogenetic analyses may not be able to demonstrate, especially for massive panel data.
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