This paper aims to assess the performance of Village Credit Institutions (Lembaga Perkreditan Desa or LPD) in Gianyar district, Bali province, Indonesia and its affecting factors –particularly its institutional environment. The performance indicators assessed include financial indicators (such as portfolio quality, leverage, capital adequacy ratio, productivity, efficiency, profitability, and financial viability) and outreach of the LPDs. Institutions here refer to the rules or procedures that shape how agents (people) interact and the organizations that implement the rules and codes of conduct to achieve desired outcomes. Based on data from financial reports of 174 LPDs of Gianyar district in 1999 and 2001, interviews with some stakeholders (clients, chairmen, and member of commissioner board) of the LPDs, and using descriptive analysis approach, this paper reveals that the LPDs have achieved a good performance indicators and been sustainable, and the good performance and sustainability have been very much influenced by institutional environment which includes both formal and informal institutions.

This paper attempts to assess the influence of several factors on the repayment rate of the Village Credit Institutions (Lembaga Perkreditan Desa or simply LPDs) in Gianyar district in Bali. Using a quantitative approach (logistic model) the findings of this study indicate that the Balinese social custom, including social values, norms, and sanctions (informal institutions) have an influence on sustaining the high repayment rate of the LPDs. This finding conforms to the some previous studies using institutional approach that reveal the high repayment rate of the LPDs in Gianyar district is influenced by their institutional arrangement that based on custom regulation which includes social norms, sanctions, and involvement of custom village leader in screening process and contractual enforcement of loan (informal institutions), by regulations set up by the Central Bank (formal institutions), and by the mechanism of collecting loan repayments applied by the LPDs management.

Food prices regularly change due to various factors such as the policy on imports. This paper analyzes the impact of changes in food prices including rice, red onions, and garlic, on farmers’ welfare. The Quadratic Almost Ideal Demand System (QUAIDS) was used to estimate the demand function for food commodities, and the Compensating Variation (CV) was used to estimate the impact of price changes both immediately and in the short-term. This study contributes an idea of how the government makes its policies on food prices and imports, and how they provide benefits for farmers in Indonesia. Data were collected from the 2014 National Socio-economic Survey (SUSENAS). The research results indicated that income improvement led to the increase in rice, red onion and garlic consumption. The dynamics of income, own-price and cross-price elasticity varied, depending on demography, the social economic condition, and the geographic location of the household. The short-term impact of imported products on welfare changes was larger than the immediate impact.

The identification of regional development gaps is an effort to see how far the development conducted in every District in a Province. By seeing the gaps occurred, it is expected that the Policymakers are able to determine which region that will be prioritized for future development. Along with the regional gaps, the identification in Gross Regional Domestic Product (GRDP) sector is also an effort to identify the achievement in the development in certain fields seen from the potential GRDP owned by a District. There are two approaches that are often used to identify the regional development gaps and potential sector, Klassen Typology and Location Quotient (LQ), respectively. In fact, the results of the identification using these methods have not been able to show the proximity of the development gaps between a District to another yet in a same cluster. These methods only cluster the regions and GRDP sectors in a firm cluster based on their own parameter values. This research develops a new approach that combines the Klassen, LQ and hierarchical agglomerative clustering (HAC) into a new method named multi view hierarchical agglomerative clustering (MVHAC). The data of GRDP sectors of 23 Districts in West Java province were tested by using Klassen, LQ, HAC and MVHAC and were then compared. The results show that MVHAC is able to accommodate the ability of the three previous methods into a unity, even to clearly visualize the proximity of the development gaps between the regions and GRDP sectors owned. MVHAC clusters 23 districts into 3 main clusters, they are; Cluster 1 (Quadrant 1) consists of 5 Districts as the members, Cluster 2 (Quadrant 2) consists of 12 Districts and Cluster 3 (Quadrant 4) consists of 6 Districts.

The development of the region cannot be separated from the concept of economic growth and the determination of the mainstay region as a regional center that is expected to have a positive impact on economic growth to the surrounding regions. In fact, the determination of the mainstay region is a difficult thing to do. Some cases of the determination of the mainstay region are mostly on the basis of the prerogative rights of the policy makers without carefully seeing the achievements of the development of a region. The objective of this study is to develop a classification model of the mainstay economic region using computational techniques. The decision tree methods of NBTree and J48 are used in this study and combined with Klassen typology. The results of this study show that J48 algorithm has better accuracy than NBTree in the formation process of decision tree. The accuracy of J48 is higher than NBTree i.e. 68.96%. The comparative result of the classification of the mainstay economic region between Klassen and J48 shows that there is a shift in the class position of the development quadrant. In Klassen classification, there are three regions that are categorized into the mainstay regions with advanced development and rapid growth (K1). Meanwhile, J48 results show that there is no region categorized into K1. However, the mainstay economic region on J48 is based on the level of development with the level below K1, i.e. K2. J48 classification results show that there are ten regencies that are categorized into the mainstay economic regions, namely Biak, Regency of Jayapura, Jayawijaya, Kerom, Merauke, Mimika, Nabire, Ndunga, Yapen, and the Municipality of Jayapura.