Spatial Statistic Analysis of Earthquakes in Aceh Province Year 1921-2014: Cluster Seismicity

The purpose of this study is to apply the analysis of spatial patterns of earthquakes in the province of Aceh by detecting clusters and looking for spatial patterns locally and globally during the period 1921-2014 using GIS (Geographic Information System). The selected techniques are Average Nearest Neighbor, Moran Global Index, the Getis-Ord General G, Anselin Local Moran Index, the Getis-Ord Gi*, and Kernel Density Estimation. Each technique is implemented using GIS so that calculations can be done efficiently and quickly. The results of this study indicate that (1) The techniques can detect clusters of dots on the spatial pattern of earthquakes; (2) Both globally and locally, it shows that earthquakes clustered in the southwestern heading to the northern part of the province; (3) An earthquake with a greater magnitude generally concentrated in the district of Simeulue, the western part of Aceh Besar and northwest of Saban

Prevalence of depression and anxiety among college students living in a disaster-prone region

The present study examined the prevalence rate of depression and anxiety among college students living in a disaster-prone area of Aceh, Indonesia. College students enrolled in two public Universities in Banda Aceh were randomly selected to participate in the self-administered standardized questionnaires for depression and anxiety. The prevalence rates of depression and anxiety were 18.8% and 27.4%, respectively. Depression was associated with gender and BMI while anxiety was only associated with gender. Depression is also positively correlated to anxiety. Depression and anxiety are prevalent among college students living in a disaster prone area. Early detection and timely treatment of mental disorders should be beneficial to the students living in this circumference.Keywords: Depression, Anxiety, College students, Disaste

The Efficiency of Manufacturing Sector: Empirical Evidence From Aceh Province Indonesia

This paper was aimed to analyze the efficiency of Manufacturing Sector in Province of Aceh – Indonesia. The analysis was conducted using the secondary data on manufacturing sector of Province of Aceh together with the Data Envelopment Analysis (DEA analysis). Based on the research, it was found that the manufacturers that had highest output included those producing Fertilizer, Chemical, and Rubber whereas the manufacturers that had the lowest output included Foods and Tobaccos. This condition was caused by the lower interest of the producers involving in foods and tobaccos products. By using DEA analysis, the efficiency value of each product is varied. Using constant return to scale (CRS) assumption, there are four manufactures that are not efficient, including Foods and Tobaccos, Textile, Animal skin products and shoes, and Fertilizer, Chemical, and Rubber products.Keywords: efficiency, manufacturing sector, data envelopment analysi

Dynamic interdependence of the Indonesian Rupiah with the ASEAN and the world largest Forex markets

This study empirically investigates the dynamic interdependencies of the Indonesian Rupiah (IDR) with the ASEAN, European, and Japanese forex markets. Using daily nominal exchange rates of Indonesia, Thailand, Malaysia, Singapore, the Philippines, Europe, and Japan spanning from January 1, 2008 to December 31, 2015, the study employs the impulse response functions and variance decomposition analysis based on the vector autoregression method. The study documented that the IDR more responded to innovations in the forex market of Singapore as compared to other ASEAN forex markets. Additionally, the ASEAN forex markets were more interdependence with the forex markets of Japan rather than Europe. Since the forex markets become more interdependent both regionally and internationally, thus it needs for policy coordination among the countries to mitigate the impact of forex fluctuations if these countries are to grasp the benefits of greater forex markets’ interdependence

Using peer education to improve diabetes management and outcomes in a low-income setting: A randomized controlled trial

Background: Diabetes is an important health burden in Indonesia. However, diabetes management and treatment remain poor, with most people with diabetes in Indonesia not achieving the recommended blood glucose levels. Peer education may have particular potential in low-income settings in complementing diabetes care without being a large additional strain on the health system. Methods/design: This cluster randomized controlled trial aims to identify the effect of the implementation of peer education for patients with type 2 diabetes on diabetes-related outcomes in Aceh, Indonesia, which will complement the diabetes treatment provided at primary-care health posts (puskesmas). Altogether, 29 puskesmas were recruited in Banda Aceh and Aceh Besar, each of which was randomly assigned to either the control or the intervention group. Then, 534 people with diabetes were identified and recruited through their respective puskesmas. The intervention consists of up to two peer education groups per puskesmas, which are led by previously trained people with diabetes. Peer education sessions are held every month for 18 months, with follow-up data being collected 9 and 18 months after the first peer education session. The main objective is to improve diabetes management and the health behavior of participants receiving peer education to reduce their average blood glucose levels as measured by glycated hemoglobin (HbA1c) levels. Secondary outcomes are the effects of peer education on lipid levels, waist circumference, blood pressure, quality of life, treatment adherence, diabetes knowledge, physical activity, and dietary diversity. Data sources for the measurement of outcomes include patient and health facility surveys and biomarker measurements. An economic evaluation will be conducted to assess the cost-effectiveness of the intervention. Discussion: This trial will contribute to the evidence on the effectiveness and cost-effectiveness of peer education in improving diabetes management in a low-income setting in Indonesia and in other comparable contexts

Healthcare providers' perception of the referral system in maternal care facilities in Aceh, Indonesia: A cross-sectional study

Objectives Our study investigates the barriers perceived by staff in the referral systems in maternal healthcare facilities across Aceh province in Indonesia. Design With a cross-sectional approach, two sets of surveys were administered during September to October 2016 in 32 sampling units of our study. We also collected referral data in the form of the frequency of ingoing and outgoing referral cases per facility. Setting In three districts, Aceh Besar, Banda Aceh and Bireuen, a total of 32 facilities including hospitals, community health centres, and private midwife clinics that met the criteria of providing at least basic emergency obstetric and neonatal care (BEonC) were covered. Participants Across the 32 healthcare centres, 149 members of staff (mainly midwives) agreed to participate in our surveys. Primary and secondary outcome measures The first survey consisted of 65 items focusing on organisational measures as well as case numbers for example, patient counts, mortality rate and complications. The second survey with 68 items asked healthcare providers about a range of factors including attitudes towards the referral process in their facility and potential barriers to a well-functioning system in their district. Results Overall, mothers'/families' consent as well as the complex administration process were found to be the main barriers (36% and 12%, respectively). Healthcare providers noted that information about other facilities has the biggest room for improvement (37%) rather than transport, timely referral of mothers and babies, or the availability of referral facilities. Conclusions The largest barrier perceived by healthcare providers in our study was noted to be family consent and administrative burden. Moreover, lack of information about the referral system itself and other facilities seemed to be affecting healthcare providers and mothers/families alike and improvements perhaps through a shared information system is needed

Willingness-to-pay for a COVID-19 vaccine and its associated determinants in Indonesia

How countries, particularly low- and middle-income economies, should pay the coronavirus disease 2019 (COVID-19) vaccine is an important and understudied issue. We undertook an online survey to measure the willingness-to-pay (WTP) for a COVID-19 vaccine and its determinants in Indonesia. The WTP was assessed using a simple dichotomous contingent valuation approach and a linear regression model was used to assess its associated determinants. There were 1,359 respondents who completed the survey. In total, 78.3% (1,065) were willing to pay for the COVID-19 vaccine with a mean and median WTP of US$57.20 (95$ 54.56, US$59.85) and US$ 30.94 (95%CI: US$30.94, US$ 30.94), respectively. Being a health-care worker, having a high income, and having high perceived risk were associated with higher WTP. These findings suggest that the WTP for a COVID-19 vaccine is relatively high in Indonesia. This WTP information can be used to construct a payment model for a COVID-19 vaccine in the country. Nevertheless, to attain higher vaccine coverage, it may be necessary to partially subsidize the vaccine for those who are less wealthy and to design health promotion materials to increase the perceived risk for COVID-19 in the country

Analyzing XploRe Download Profiles with Intelligent Miner

This paper is an example of data mining in action. The database we are mining contains 1085 profiles of individuals who have downloaded the statistical software XploRe. Each profile contains the responses to an online questionnaire comprised of questions about such things as an individuals' computing preferences (operating system, favourite statistics software) or professional affiliation. After formatting and cleaning the raw data using MS Excel, we use IBM's Intelligent Miner to perform a cluster analysis of the download profiles. We try to identify a small number of "types" of users by employing a clustering algorithm based on the New Condorcet Criterion, which is particularly well-suited for our all-categorical data. We identify three clusters in the mining run: Academia, Unix/Linux users and Researchers. The three variabels that are most important in identifying the clusters are an individual's kind of work, the way he or she got to know XploRe and the operating system of his or her computer

Pengembangan aplikasi teknologi informasi berbasis WEB SIG (sistem informasi geografis) untuk pengintegrasian informasi potensi bahan tambang dan energi terbarukan di Provinsi Aceh

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