This paper introduces a Markov chain model for Islamic micro-financing, especially mudarabah  and murababah contract. Mudarabah and murabahah  are two Islamic micro-financing contracts that have enormous potential in creating a balance between the monetary and sharia sector because these two products are moving to manage the business sector which undoubtedly adds value to the economic movement directly.  On the other hand, these two contracts have the potential to cause problems in their implementation. The most common problem of the two contracts is asymmetric information, which consists of adverse selection and moral hazard. We propose the Markov chain model as a solution for the Islamic banks to reduce the risk because of adverse selection and moral hazard in mudarabah  and murabahah  contract. In our model, we also propose a mechanism to avoid strategic default in mudarabah contract. We observed two different probabilities of an applicant to become a beneficiary to find the solution to the problems. The results of this study, the bank can decrease the probability of an applicant to become a beneficiary to reduce the adverse selection and moral hazard in mudarabah  and murabahah contract.

Tujuan dari kegiatan peningkatan kemampuan numerasi bagi guru Madrasah Ibtidaiyah adalah untuk perbaikan proses pembelajaran literasi numerasi untuk meningkatkan keterampilan guru Madrasah Ibtidaiyah (MI) dalam merencanakan, melaksanakan, dan mengevaluasi pembelajaran literasi numerasi menggunakan matematika sebagai wahananya. Kegiatan ini merupakan rangkaian kegiatan dalam bimbingan teknis (BIMTEK) tindak lanjut hasil asesmen kompetensi madrasah Indonesia (AKMI) yang diselenggarakan oleh Kementerian Agama RI. Kegiatan ini melibatkan  60 guru sebagai peserta dan 1 orang instruktur. Peserta adalah guu Madrasah Ibtidaiyah  dari 5 provinsi, yaitu Jawa Timur, Kalimantan Barat, Kalimantan Selatan, Kalimantan Tengah, dan Kalimantan Selatan. Dalam kegiatan ini, peserta dibagi menjadi 2 kelas, yaitu kelas 033 dan kelas 034 yang masing-masing kelas terdiri dari 30 peserta. Kegiatan ini dapat meningkatkan kompetensi numerasi peserta yang dapat diterapkan dalam pembelajaran numerasi di kelas. Peserta dapat meningkatkan keterampilan mereka dalam merencanakan, melaksanakan, dan mengevaluasi pembelajaran  literasi numerasi di kelas. Perlu adanya tindak lanjut dari kegiatan ini, yaitu berupa evaluasi terhadap apa yang akan/telah diterapkan oleh pada peserta di MI masing-masing.

We consider a Markov-Chain model for a Microfinance Institution (MFI) borrower who can be in one of four states: Applicant (A), Beneficiary (B − or B + ) of a small or a large loan, or included (I) in the regular banking system. Given the transition matrix we compute the equilibrium and deduce the influence of probability parameters on what is profitable to the borrower within breaking-even constraints of the MFI. We give a general theorem on the total expected actualized income of a Markov Chain with Income (MCI), that we then apply to our model to determine the constrains emerging from Absence of Strategic Default (ASD) requirements. These do not only bound the probabilities from above but sometimes also from below.

This paper presents a Bayesian Game model for a profit-and-loss sharing (PLS) contract. We develop our model into two parts, namely the model for non-social bank and the model for social bank. We propose the model to reduce adverse selection problem in offering a PLS contract. The Bayesian game starts with an incomplete information. Islamic banks do not know exactly what type of agent is applying for a PLS contract, efficient or non-efficient, the information of the bank is incomplete. In Bayesian game, we assume that the Islamic Bank assigns the agent type with a prior probability. Determination of the profit-sharing ratio of the contract will be discussed. We look for the Bayesian Nash equilibrium of the game in our model which is considered a solution. We show that the bank offers an interesting but risky contract to the agent if the bank assigns that the agent is efficient with a high probability, otherwise the bank offers a less risky contract to the agent if the bank assigns that the agent is a non-efficient agent with high probability. The results can be considered by Islamic banks to reduce the adverse selection problem in PLS contract.