Decision analysis of Multiple Attribute Decision Making (MADM) model is used to assess the performance, not only in a rank but also in a plan of marketing strategy as an effort to increase consumers’ satisfaction by combining DEMATEL-based Analytical Network Process (DANP) method and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method. One of the industrial services in the education nowadays is the services of the Guidance Learning (LBB). This article has 3 alternatives to 6 criteria. The questionnaire was distributed to 80 LBB’ students and 55 LBB’ mentors. The result of the dominant criteria affecting customer satisfaction of LBB in Malang by DANP method is the mentor quality. Meanwhile, the TOPSIS result showed that the LBB of Avicenna Education Malang is the best alternative to the marketing strategy..

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The Hybrid Entropy-TOPSIS method is a combination of two methods, Entropy and TOPSIS. The combination of the two methods is used in the decision-making model to improve the quality of a decision. In this research, the Hybrid Entropy-TOPSIS method was applied to determine the ideal contraceptive tool based on the acceptor criteria. Entropy is a method of weighted criteria, while TOPSIS is a method of decision making through the alternative ranking process based on weighted criteria. The criteria are factors which influence to Keluarga Berencana acceptors for selecting contraceptives. The used criteria in this research were the age, blood pressure, menstrual cycle, the use of contraceptives, and the cost. While the Alternative is contraceptive tool itself. The selected alternatives here were Pill, Injection, Condoms, Implant, IUD and MOP / MOW. Based on the results of the questionnaire data and the simulation, it was obtained that pill and implants has the highest ranking and they indicated that pill and implants as an alternative selection of the ideal contraceptives.

Determination of methods or contraception tool used by acceptors to support the Family Planning (“Keluarga Berencana”) is a problematic. In choosing methods or contraception tool, the acceptor must consider several factors, namely health factor, partner factor, and contraceptive method. Each method or contraception tool which is used has its advantages or disadvantages. Although it has been considering the advantages and disadvantages, it is still difficult to control fertility safely and effectively. Consequently acceptor change the method or a contraception tool that is used more than once. In order acceptors get the appropriate contraception tool then the patterns of changing in the usage of effective methods or contraception tool is determined. One of the methods that can be used to look for the patterns of changing in the usage of contraception tool is data mining. Data mining is an interesting pattern extraction of large amounts of data. A pattern is said to be interesting if the pattern is not trivial, implicit, previously unknown, and useful. The patterns presented should be easy to understand, can be applied to data that will be predicted with a certain degree, useful, and new. The early stage before applying data mining is using k nearest neighbors algorithm to determine the factors shortest distance selecting the contraception tool. The next step is applying data mining to usage changing data of method or contraception tool of family planning acceptors which is expected to dig up information related to acceptor behavior pattern in using the method or contraception tool. Furthermore, from the formed pattern, it can be used in decision making regarding the usage of effective contraception tool. The results obtained from this research is the k nearest neighbors by using the Euclidean distance can be used to determine the similarity of attributes owned by the acceptors of Family Planning to the training data is already available. Based on available training data, it can be determined the usage pattern of contraceptiion tool with the concept of data mining, where the acceptors of Family Planning are given a recommendation if the pattern is on the training data pattern. Conversely, if the pattern is none match, then the system does not provide recommendations of contraception tool which should be used.

Pada tahun 2015, PBB merancang 17 Tujuan Pembangunan Berkelanjutan (SDGs) untuk mencapai kesejahteraan manusia pada tahun 2030 dengan mengintegrasikan tiga dimensi pembangunan berkelanjutan: ekonomi, sosial, dan lingkungan. Salah satu faktor yang digunakan untuk menilai keberhasilan sebuah wilayah atau pemerintahan dalam mengelola kesejahteraan dan kemakmuran masyarakat adalah tingkat perekonomian. Untuk mewujudkan kondisi tersebut diperlukan strategi dalam pembangunan pada sektor ekonomi. Penelitian ini bertujuan untuk mengelompokkan Provinsi di Indonesia menjadi 3 klaster berdasarkan Indikator Pembangunan Ekonomi menggunakan algoritma Fuzzy c-Means. Penentuan 3 klaster dimaksudkan untuk klaster provinsi dengan tingkat pembangunan ekonomi rendah, sedang dan tinggi. Dengan mengetahui karakteristik provinsi berdasarkan Indikator Pembangunan Ekonomi, maka pengambil keputusan dapat menyusun strategi perencanaan program pembangunan ekonomi berdasarkan skala prioritas pada masing-masing provinsi. Hasil pengelompokan menunjukkan bahwa Provinsi Papua sangat membutuhkan prioritas pembangunan khususnya pembangunan ekonomi dalam rangka peningkatan Indek pembangunan manusia, Angka partisipasi sekolah berusia 7 sampai 12 tahun, Angka partisipasi sekolah berusia 13 sampai 15 tahun, Angka partisipasi sekolah berusia 16 sampai 18 tahun, Sumber Air Minum Layak, Sumber penerangan listrik, dan Sanitasi Layak, karena indikator-indikatir tersebut bernilai rendah.