Keunggulan Sistem Keuangan Berbasis Bagi Hasil Dan Implikasinya Pada Distribusi Pendapatan

In this paper we attempted to answer a fundamental question whether banking systembased on a profi t-loss sharing (PLS) could improve welfare than an interest based banking system bydeveloping a rigorous theoretical modeling. In the framework of production technology we fi rstlyshowed that under production certainty and competitive market both PLS and interest based systemswere effi cient and right. However, under an uncertain situation due to a productivity shock,we proved that only the PLS system was right. We verifi ed our result by quantifying the effects onincome distribution for both lender and borrower. Two indicators, namely the standard error of distributionand Gini ratio were considered. We showed that the conventional credit market led to aserious income distribution problem where lenders did not enjoy the variability in income and didnot bear any risk, but in contrast, borrowers bore all the risk. On the other side, PLS system sharedthe risk between lenders and borrowers. In the end of the analysis, we proposed an instrument thatwould improve the performance of a PLS system from lenders perspective by introducing a so-calledrisk pooling mechanism

Fleksibilitas Nilai Tukar dan Penyesuaian Transaksi Berjalan di Indonesia: Analisis Threshold Var

Estimation study about the relationship between exchange rate flexibility and current account adjustment has been through three stages, the first stage was analysis of correlation among exchange rates variability (proxied by REER and NEER) and exchange rate regimes classification. The second step was estimating the relationship that the former was mentioned with VAR as benchmark model. The third step was applying the nonlinear estimation with Threshold VAR. The results of analysis showed that exchange rate regime classification may not capture actual exchange rate variability and flexibility exchange rate can accelerate current account adjustment in Indonesia if the changes of Indonesia exchange rate less than 27.7059 (low regime) whereas in high regime exchange rate is persistent increasing so that the system between exchange rate and current account become unstable. Bank Indonesia as monetary authorities must keep the changes of exchange rate less than 27.7059, due to exchange rate can affect current account adjustment, so can anticipate if there is current account deficit in Indonesia economy

Constructing a Predicting Model for JCI Return Using Adaptive Network-based Fuzzy Inference System

The high price fluctuations in the stock market make an investment in this area relatively risky. However, higher risk levels are associated with the possibility of higher returns. Predicting models allows investors to avoid loss rate due to price fluctuations. This study uses the ANFIS (Adaptive Network-based Fuzzy Inference System) to predict the Jakarta Composite Index (JCI) return. Forecasting JCI movement is considered to be the most influential predictor, consisting of Indonesia real interest rate, real exchange rate, US real interest rate, and WTI crude oil price. The results of this study point out that the best model to predict JCI return is the ANFIS model with pi membership function. The predicting model shows that real exchange rate is the most influential factor to the JCI movement. This model is able to predict the trend direction of the JCI movement with an accuracy of 83.33 percent. This model also has better performance than the Vector Error Correction Model (VECM) based on RMSE value. The ANFIS performance is relatively satisfactory to allow investors to forecast the market direction. Thus, investors can immediately take preventive action towards any potential for turmoil in the stock market.JEL Classification: D13, I31, J22DOI: https://doi.org/10.26905/jkdp.v23i1.252

Optimasi Biaya Operasional pada Krl Commuter Line dengan Pemberangkatan Kereta

Optimal trainset dispatching can reduce passenger build-up and optimize operational costs. This research aimed to create a model of trainset dispatching for each time slot with minimum operational costs so that passenger demand can be met. The parameters in this research are the number of passengers getting-on and getting-off, the availability of each type of train series, train capacity, operational costs, and time limits for using the training series during operational hours. The model was formed into integer linear programming and resolved with Lingo 11.0 software. This model is applied in one direction from  Bogor station to the Jakarta Kota commuter line. Trainset dispatching is done by selecting the 8 SF, 10 SF, and 12 SF trainset types with minimum operational costs at each time slot. The optimum results obtained during operational hours need to dispatch 56 trainset trips. Due to the limitations of the study the optimum operational cost of trainset dispatched is obtained  302C