コミュニティ主導型開発と貧困削減：インドネシアにおけるコミュニティ能力強化のための国家プロジェクトの経済評価

この博士論文は、全文公表に適さないやむを得ない事由があり要約のみを公表していましたが、解消したため、令和２（2020）年6月３日に全文を公表しました。筑波大学 (University of Tsukuba)201

コミュニティ主導型開発と貧困削減：インドネシアにおけるコミュニティ能力強化のための国家プロジェクトの経済評価

筑波大学 (University of Tsukuba)201

Regional Tourism Development in Nusa Tenggara Barat: Maximizing Local Economic Development

The diversity of each region causes different potentials in each region. The potential of the village can map how rich the area is, the advantages of the area, and the population and welfare. Tourism is one of them; this sector is potential for the area because it can lift its economy if it is adequately managed. Good management is born from the policies/regulations of the local government. Nusa Tenggara Barat is a province with many tourist attractions. However, from an economic and socio-cultural perspective, Nusa Tenggara Barat has yet to be able to compete with other major provinces in Indonesia, such as the Special Region of Yogyakarta (DIY). The 2018 Village Potential Data by BPS can assist the government in compiling efforts for the village's progress. In the process of data processing, especially big data, in-depth exploration is needed to produce meaningful insight. Clustering is one of the exploration techniques that can map areas in Nusa Tenggara Barat based on the tourism potential in each village. K-Prototypes are used in cases with mixed variables (numeric and categorical). Determination of the best number of clusters is using the silhouette index. It produced 5 clusters with their respective diversity. There are five clusters in Nusa Tenggara Barat by the villages based on tourism aspects and factors that support tourism. Cluster 3 is an ideal cluster, meaning tourism development in that cluster is complete. Cluster 5 has considerable potential in tourism because the supporting factors are analytically good. There are villages dispersed across Sumbawa Barat, Sumbawa, Lombok Tengah, Lombok Barat, Dompu, and Bima that are part of cluster 1. In Sumbawa Barat and Lombok Tengah, cluster 1 predominates numbers. The settlements in cluster 2 are then more prevalent in Sumbawa and Bima. Furthermore, Sumbawa, Dompu, and Bima have the highest concentrations of cluster 4. Unlike clusters 3 and 5, special attention should be paid to clusters 1, 2, and 4 in tourism development. Implications of this research are the government could take toward each cluster to increase the GDP-oriented service product, namely tourism; whether it is an improvement or reconstruction, clustering analysis works its role in learning the data to make the policy more focused.Keberagaman setiap daerah menyebabkan potensi yang berbeda di setiap daerah. Potensi desa dapat memetakan seberapa kaya wilayahnya, keunggulan wilayahnya, serta jumlah penduduk dan kesejahteraannya. Pariwisata adalah salah satunya; Sektor ini merupakan potensi daerah karena pariwisata dapat mengangkat perekonomian daerah jika dikelola dengan baik. Manajemen yang baik lahir dari kebijakan/peraturan pemerintah daerah. Nusa Tenggara Tenggara (NTB) merupakan provinsi yang memiliki banyak tempat wisata. Namun, dari segi ekonomi dan sosial budaya, NTB belum mampu bersaing dengan provinsi besar lainnya di Indonesia, seperti Daerah Istimewa Yogyakarta (DIY). Data Potensi Desa 2018 oleh BPS dapat membantu pemerintah dalam menyusun upaya kemajuan desa. Dalam proses pengolahan data khususnya big data diperlukan eksplorasi yang mendalam untuk menghasilkan insight yang bermakna. Clustering merupakan salah satu teknik eksplorasi yang dapat memetakan wilayah di NTB berdasarkan potensi wisata di masing-masing desa. K-Prototipe digunakan dalam kasus dengan variabel campuran (numerik dan kategorikal). Penentuan jumlah cluster terbaik menggunakan indeks siluet. Dihasilkan 5 cluster dengan keanekaragamannya masing-masing

Comparative Analysis of Social Economic and Ecological Progress of “Oil Palm Village” and “Non-Oil Palm Village” Communities

This study aimed to analyze the level of social, economic, and ecological progress of the Oil Palm Village communities and compare the level of social, economic, and ecological progress between the Oil Palm Village and Non-Oil Palm Village communities. Indonesia is one of the major palm oil-producing countries in the world. Palm oil has brought economic benefits nationally and also to local communities. However, in its development, there has been a controversy surrounding the palm oil commodity, namely in the case of Indonesian palm oil which is related to the issues of deforestation and territorialization due to the economic interests of palm oil versus the existence of forest areas. This study used a Quantitative Approach with Secondary Data Methods from primary sources (Ministry of Village, Development of Disadvantage Region, and Transmigration, BPS, and Directorate General of Plantation) with the village communities as the unit of analysis. As many as 524 village communities were selected from the population of Oil Palm Villages and Non-Oil Palm Villages in eight provinces of Indonesia’s oil palm centers with a combination of Purposive Multistage Sampling and Propensity Score Matching methods. Descriptive analysis, comparative analysis, analysis of the difference in progress using the Difference in Difference (DID) model, and the binary logistic regression method were carried out in this study. The results of the study revealed the facts that there has been an increase in social, economic, and ecological progress in various Oil Palm Village communities. The level of social, economic, and ecological progress of Oil Palm Village communities is higher than that of Non-Oil Palm Village communities. These facts indicate that the community sustainability level of the Oil Palm Village communities is superior to that of the Non-Oil Palm Village communities

Analysis of the Effectiveness of Flash Floods Disaster Mitigation in Java Island

Flash flood is one of the natural disasters that currently happens a lot in Indonesia. Java Island is one of the largest archipelagoes in Indonesia and has the highest incidence of flash floods. Several efforts were conducted to anticipate and mitigate flash floods in Java Island, including an early warning system, preparing safety equipment, building evacuation route signs, and monitoring watersheds. Through the dataset of Village Potential 2018, this study aims to explore the effectiveness of flash flood mitigation in Java Island using the R programming language. The stages of research carried out in this study are data preprocessing, including selecting, recoding the variables, exploratory univariate, bivariate, and multivariate data analysis. The results showed that the fatalities of flash floods often occurred in areas with plains surface, especially in West Java and East Java, followed by the topography of Central Java on the hills and the valleys in Banten. In addition, the most effective disaster mitigation established in Java Island is safety equipment and the construction of evacuation route signs compared to other disaster anticipation efforts

Seroprevalence, Accuracy and Precision Value of Brucellosis Surveillence at The Region Area of Balai Karantina Pertanian Kelas I Balikpapan

The Technical Implementation Unit alai Karantina Pertanian Kelas I Balikpapan plays a role in efforts to prevent the entry, spread, and release of HPHK. Direct observation was performed by surveying the target brucellosis in the region of Balai Karantina Pertanian Kelas I Balikpapan. This surveillance aimed to determine the seroprevalence of brucellosis and to support the maintenance of brucellosis status in East Kalimantan. Sampling in areas with reported clinical symptoms and brucellosis reactors. The sampling areas were based on the region of Balai Karantina Pertanian Kelas I Balikpapan in Balikpapan City, North Penajam Paser Regency, Paser Regency, and Kutai Kartanegara Regency. The method for calculating the number of samples to detect the disease uses the Rose Bengal Test (RBT) and Complement Fixation Test (CFT). The test results showed a seroprevalence of 0.29%, positive and negative predictive values of 50% and 99,7%, respectively, an accuracy value of 99.11%, and a precision of 50%. The test performance based on the accuracy value was excellent because it had a value of 99.11%, which means that the ability of the CFT to detect all samples tested correctly was 99.11%. The test carried out using the CFT test on this surveillance had a precision or test consistency of 50%, and the sensitivity and specificity were 50% and 99.7%, respectively

Economic Evaluation of Poverty Alleviation by the National Program for Community Empowerment in Western Part of Rural Indonesia

This study is aimed to evaluate community empowerment program known as PNPM Mandiri in terms of block grant allocations whether they are proven to impact poverty reduction in Indonesia. It is documented that economic and agriculture allocation play significant role in alleviating poverty as they are deemed as economical investment for rural entities. Another result suggested that transportation, economic, together with agricultural sector have particular relationship as grouped as economic capital that they could not be separated each other which, one treated to be increase, subsequently other sector will tend to increase as well. However, the notion of human capital personified into social, health, and education budget do not show significantly different due to particular reasons comprising elite dominance, poor healthcare delivery, and unequal expenditure of education distribution within family, respectively. The findings is fruitful in order to project more efficient budget allocation either to diversify variety of PNPM program to fasten and optimize poverty eradication

Low Birth Weight Classification With Synthetic Minority Over Sampling Technique Random Forest

Low birth weight (LBW) is defined as a condition where the birth weight is less than 2500 grams. Infants born with LBW conditions are more susceptible to disease and have a higher risk of dying at an early age. LBW conditions that are prone to unbalanced data can be classified using the Synthetic Minority Oversampling Technique (SMOTE) random forest method. The analysis was processed on the 2017 Indonesian Demographic and Health Survey (IDHS) data to identify important variables in predicting the incidence of LBW. The results showed that the SMOTE random forest model provided an accuracy value of 79.84%, sensitivity of 30.99%, specificity of 83.6%, and AUC of 62%. Important variables in predicting the incidence of LBW were the number of antenatal care visits, wealth quantile, maternal age at delivery, iron supplementation, marital status, and twins’ birth

Province clustering based on the percentage of communicable disease using the BCBimax biclustering algorithm

Indonesia needs to lower its high infectious disease rate. This requires reliable data and following their temporal changes across provinces. We investigated the benefits of surveying the epidemiological situation with the imax biclustering algorithm using secondary data from a recent national scale survey of main infectious diseases from the National Basic Health Research (Riskesdas) covering 34 provinces in Indonesia. Hierarchical and k-means clustering can only handle one data source, but BCBimax biclustering can cluster rows and columns in a data matrix. Several experiments determined the best row and column threshold values, which is crucial for a useful result. The percentages of Indonesia’s seven most common infectious diseases (ARI, pneumonia, diarrhoea, tuberculosis (TB), hepatitis, malaria, and filariasis) were ordered by province to form groups without considering proximity because clusters are usually far apart. ARI, pneumonia, and diarrhoea were divided into toddler and adult infections, making 10 target diseases instead of seven. The set of biclusters formed based on the presence and level of these diseases included 7 diseases with moderate to high disease levels, 5 diseases (formed by 2 clusters), 3 diseases, 2 diseases, and a final order that only included adult diarrhoea. In 6 of 8 clusters, diarrhea was the most prevalent infectious disease in Indonesia, making its eradication a priority. Direct person-to-person infections like ARI, pneumonia, TB, and diarrhoea were found in 4-6 of 8 clusters. These diseases are more common and spread faster than vector-borne diseases like malaria and filariasis, making them more important