Suchergebnisse

Bantuan rumah tidak layak huni adalah salah satu program pemerintah untuk menekan angka kemiskinan di Indonesia, namun permasalahan yang ada bahwa proses yang selama ini dilakukan oleh pihak Kelurahan masih dilakukan secara subyektif dengan hanya mempertimbangkan hasil survey. Oleh karena itu, bagi pihak kelurahan diperlukan suatu sistem pendukung keputusan agar seleksi dapat dilakukan secara efisien secara sistemik. Adanya metode Multiple Attribute Decission Making, menjawab semua permasalahan tersebut. Dari beberapa metode Multiple Attribute Decission Making, Simple Addictive Weighting dipilih untuk diterapkan kedalam sistem pendukung keputusan. Sistem pendukung keputusan dibuat menggunakan metode air terjun. Tujuan penelitian ini agar pihak kelurahan dapat menyalurkan bantuannya kepada yang berhak menerimanya, sehingga dengan adanya sistem pendukung keputusan berbasis web untuk memilih penerima bantuan perumahan sesuai dan objektif. Penelitian ini memberikan hasil yang cukup akurat dimana proses penyaluran yang tepat sasaran dengan data yang diperoleh dari pihak kelurahan. Sistem yang dibuat cukup memnatu pihak kelurahan dengan nilai sekitar 73.6% yang diuji oleh 10 orang responden. Kata Kunci: Rumah Tidak Layak Huni, Multiple Attribute Decission Making, Simple Addictive Weighting, Sistem Pendukung Keputusan. Abstract The help of the home is not habitable is one of the government programs to suppress the poverty rate in Indonesia, but the problem exists that the process that was done by the village is still in subjectively Consider the survey results. Therefore, the town needs a decision support system so that the selection can be made by systemic efficiency. There is a method of Multiple Attribute Decision Making, answering all the problems. Of the multiple Attribute Decision-Making methods, Simple Addictive Weighting is chosen to be applied to the decision support system. The decision support system was made using a waterfall method. The purpose of this research is so that the village can distribute its help to the right to receive it, so it is expected by the Web-based decision support system to select the recipient of appropriate and objective housing assistance. This research provides entirely accurate results were the right distribution process targets with data obtained from the village. The system was made enough to inform the town with a value of about 73.6% tested by ten respondents. Keywords: Unqualified Houses, Multiple Attribute Decision Making, MADM, Simple Additive Weighting, Decision Support Systems.

Local economic environment is characterised by a range of economic, social, political and demographic parameters, based on which we can perform its analysis. Heterogeneity of relevant characteristics of the local economic environment imposes multiple criteria analysis as one of the suitable tools for the evaluation. Assessment of local economic environment often falls within the scope of group decision-making, as it is usually performed on the basis of an analysis of preferences of economic subjects or relevant experts on the issue of the economic environment at the local level. Regardless of whether it is based on economic subjects or expert group, in order to form a multi-criteria model, it is necessary to generate preferences of individuals into a single weight coefficient, which shows groups' preference on the importance of each criterion. The subject of this paper is determination of weight coefficients in the multi-criteria model for the analysis of local economic development based on the preferences from a group of experts, by applying adequate statistical tools, and then by ranking local governments according to the quality of business environment perceived by the expert group.In addition to descriptive statistics and testing the significance of differences, in the paper is applied multi-criteria method Simple Additive Weights - SAW.

The Tangerang Regency Housing, Settlement and Cemetery Service has house renovation assistance for Low-Income Communities (MBR). Data input still uses manual data in the form of data such as resident documents in determining the assistance in the form of house renovation. In determining the recipient of assistance still uses subjective assessment. Analysis of Manual Calculations with the Simple Additive Weighting (SAW) method after that analysis and design were made using object-oriented methods by making use cases, activities, sequences, class diagrams and user interfaces. The results of the design can be developed to help government agencies in Tangerang Regency. Keywords: Home Rehabilitation, Simple Additive Weighting, User Interface

Construction of Non-Habitable Homes (RTLH) is a government program managed by thesupervision of the Social Service (Dinas Sosial) in the form of housing construction assistancefunds for the poor. In its realization, assistance is still often found to be lacking on target. It isbecause the determination of beneficiaries is not correctly selected, and there are no standardmethods based on existing criteria. These problems require a system that can providerecommendations that conform to clear standards and use techniques that accounted. FuzzySimple Additive Weighting (SAW) method is one method used in decision making. This methodcalculates criteria to get ranking weights to support decision making. The process of selectingcriteria and determining fuzzy variables carried out as a primary process in this method. Afterthe fuzzification weight value obtained, ranking done to use as a reference in the decision makingof recipients. Based on the results of manual testing, the system made is under the effects ofmanual calculations with a level of accuracy reaching 100%, so that implemented as a basis formaking decisions. While testing, the black box system found that all the requirements tested canrun following the overall system functionality. With this recommendation system, it can help thedecision to find the recipients of the Fund for Non-Occupable Homes Construction Assistanceso that it is more targeted.

Jaminan Kesehatan Daerah (Jamkesda) is a health care program developed by the local government in Dinas Kesehatan Kabupaten Kampar, in order to serve the public health Kampar. To determine the data collection Jamkesda Participants then deliver the data to the public from the village health centers, and health centers to check, channeling data to the Department of Health and Health Department to collect data on the verification and validation of the data to the village. This causes the length of the process of determining pesetas Regional Health Insurance, as well as in the selection process participant data manually Jamkesda frequent mistakes, including inaccuracies in determining participants underprivileged or poor.Decision support system (DSS) needed to be able to provide ease in the determination of the participants Jamkesda ranking results. Simple Additive Weighting (SAW) is a method to supports the assessment criteria and weighting. The criteria used are based on income, dependents, family size and poverty letter.The ranking results of sorted from the highest total score to lowest point total. With the decision support system will be beneficial to Dinas Kesehatan Kabupaten Kampar in the determination of the participants Jamkesda based on desired criteria.Keywords: Jamkesda, Ranking and Weighting ,SAW, SPK.

Salah satu pesta demorasi masyarakat adalah pemilihan kepala Desa, pemilihan kepala desa dilakukan di tingkat desa secara langsug untuk menentukan pemimpin Desa atau kepala Desa. Sistem pendukung keputusan merupakan suatu alternatife sistem yang interaktif yang dapat membantu dalam pengambilan keputusan melalui penggunaan data dan model-model keputusan untuk memecahkan masalah yang bersifat semi terstruktur maupun yang tidak terstruktur. Sistem ini dibangun dengan menerapkan metode SAW (Simple Additive Weighting) dimana Konsep dasar metode SAW yaitu mencari penjumlahan terbobot dari rating kinerja pada setiap alternatif pada semua atribut. Pada perhitungan metode SAW ini hanya yang menghasilkan nilai terbesar yang akan terpilih sebagai alternatif yang terbaik. Perhitunganakan sesuai dengan metode ini apabila alternatif yang terpilih memenuhi kriteria yang telah ditentukan. Dengan Menggunakan sistem pendukung keputusan pemilihan calon kepala Desa yang memakai metode Simple Additive Weigtihng (SAW) ini membantu warga masyarakat untuk mengetahui perangkingan calon kepala Desa dari hasil bobot kriteria yang telah di tentukan, sehingga memberi informasi tambahan saat akan menetukan pilihan dalam pesta demokrasi warga masyarakat di desa situnggaling.

Village community especially Banyuwangi District is still many who have BWT (Bath Wash Toilet) but do not meet the standard. Such as the absence of buildings in accordance with the quality of construction that meet the needs of society. Waste water and bath rooms are disposed of in residential environments. The Government of the Public Works Department has given attention in addressing this issue through the development assistance of BWT. But in selecting the candidate beneficiaries the election process is still done conventionally. The Decision Support System (DSS) was built to help make it easier to determine the prospective beneficiaries of BWT. There are seven eligibility criteria used to assess prospective beneficiaries. Self-Connection House (CH), monthly dues per family, land contributions, population density level per hectare, individual septic tank ownership, shallow well water quality, kitchen waste water disposal and bathrooms. DSS is processed using Simple Additive Weighting (SAW) method calculation. The SAW method is capable of precise assessment. The calculation of the SAW method is based on the criteria value and the specified preference weight. On the system, there are 8 village data used to test the system process. The highest village Data became the beneficiary village of BWT. Based on the overall level of software quality can be concluded that the level of information system quality in the criteria is very good with a percentage of 94%.

The object of research that will be made is to determine the receipt of village funds in the village of Kampung Melayu, namely Direct Cash Assistance (BLT) according to system rules. The purpose of previous research regarding research on determining recipients of rice social assistance to the poor in Kampung Melayu village with the Simple Additive Weighting (SAW) method aims to determine prospective recipients of poor rice to complete practical decision making and have alternative choices for decision making in order to determine poor people who are entitled to receive rice social assistance for the poor (Raskin) in the village. Based on the criteria used to determine the decision to receive rice social assistance for the poor, namely the amount of income, marital status, number of dependents and age. The results of this study are shown for the village government to be able to determine the people who are entitled to receive social assistance for poor rice (Raskin)

Consider a voting procedure where countries, states, or districts comprising a union each elect representatives who then participate in later votes at the union level on their behalf. The countries, provinces, and states may vary in their populations and composition. If we wish to maximize the total expected utility of all agents in the union, how to weight the votes of the representatives of the different countries, states or districts at the union level? We provide a simple characterization of the efficient voting rule in terms of the weights assigned to different districts and the voting threshold (how large a qualified majority is needed to induce change versus the status quo). Next, in the context of a model of the correlation structure of agents preferences, we analyze how voting weights relate to the population size of a country. We then analyze the voting weights in Council of the European Union under the Nice Treaty and the recently proposed constitution, and contrast them under different versions of our model.

Consider a voting procedure where countries, states, or districts comprising a union each elect representatives who then participate in later votes at the union level on their behalf. The countries, provinces, and states may vary in their populations and composition. If we wish to maximize the total expected utility of all agents in the union, how to weight the votes of the representatives of the different countries, states or districts at the union level? We provide a simple characterization of the efficient voting rule in terms of the weights assigned to different districts and the voting threshold (how large a qualified majority is needed to induce change versus the status quo). Next, in the context of a model of the correlation structure of agents preferences, we analyze how voting weights relate to the population size of a country. We then analyze the voting weights in Council of the European Union under the Nice Treaty and the recently proposed constitution, and contrast them under different versions of our model, and compare them to the weights derived from poll data.

For Ruth Millikan, convention consists of patterns that are produced by reproduction which proliferate due partly to weight of precedent. The authors argue that on Millikan's account, a lot more is going to count as conventional than seems reasonable on any plausible account of convention. Moreover, at least some things that the authors think ought to be counted as conventions are going to get left out.

Abstract
In probabilistic sampling, a sampling frame comprising the target population may not be available. However, indirect sampling can be used when the units on a sampling frame can be linked to the target population, with the values observed in the target population used for estimation. If the target population can only be linked to the sampling frame through an intermediate population, then double indirect sampling is a viable option. In this case, the sampling weights can be obtained with the double generalized weight share method (GWSM). The double GWSM reduces the number of observed links compared to the simple GWSM but can detrimentally affect the precision of the estimator, as in the example of the French postal service (La Poste). In this article, we show the existence of a set of sampling weights that minimize the variance of the double GWSM in specific cases with La Poste as exemplar. These weights ensure that the implementation advantages of the double GWSM are not offset by a loss of precision. When these weights cannot be computed, as is the case in the French postal traffic survey, we propose alternative weights that can be used to improve the precision of the double GWSM estimator. Results are illustrated through Monte Carlo simulations and an application to the French postal traffic survey.

Consider a voting procedure where countries, states, or districts comprising a union each elect representatives who then participate in later votes at the union level on their behalf. The countries, provinces, and states may vary in their populations and composition. If we wish to maximize the total expected utility of all agents in the union, how to weight the votes of the representatives of the different countries, states or districts at the union level? We provide a simple characterization of the efficient voting rule in terms of the weights assigned to different districts and the voting threshold (how large a qualified majority is needed to induce change versus the status quo). Next, in the context of a model of the correlation structure of agents preferences, we analyze how voting weights relate to the population size of a country. We then analyze the voting weights in Council of the European Union under the Nice Treaty and the recently proposed constitution, and contrast them under different versions of our model.