<span lang="IN">This paper was conducted to apply Analytical Hierarcy Process (AHP), applied as Decision Support System (DSS) model in selection of lecturer at STAIN Batsangkar. Data collected by through observation and interview done in shares of administration academic data center at college. Here in  data analyzed to learn the pattern from method used and added with the reference from literature. Experiment done using Microsoft Excel and Expert Choice Software, known that method can yield the optimal decision in selection of lecturer. There by the method recommended to be applied to getting optimal result in decision making.</span>

Tujuan dari penelitian ini untuk mengetahui dan menganalisis pengaruh inflasi dan nilai tukar rupiah terhadap harga saham pada perusahaan properti yang listing pada Bursa Efek Syariah diIndonesia. Sampel dalam penelitian ini berjumlah 11 perusahaan. Teknik analisis data dalam penelitian ini menggunakan regresi linier berganda uji asumsi klasik, uji-t dan uji-f, koefisien determinasi. Pengelolaan data dalam penelitian ini meggunakan program software IBM SPSS (Statistic package for the social sciences) versi 25 for windows. Hasil penelitian ini membuktikan bahwa inflasi berpengaruh terhadap harga saham perusahaan properti dengan nilai sig. 0,032 < (α) 0,05. Nilai tukar rupiah berpengaruh terhadap harga saham pada perusahaan properti, pada sig. 0,042 < (α) 0,05. Secara simultan inflasi dan nilai tukar berpengaruh terhadap harga saham pada perusahaan properti dengan sig. 0.046 < (α) 0,05. Keimpulan bahwa inflasi dan nilai tukar rupiah baik secara parsial maupun secara simultan berpengaruh terhadap harga saham pada perusahaan propoerti efek syariah periode 2010-2020.

Multi-Attribute Decision Making (MADM) is used to select the best alternative from multi-alternatives based on multi-attribute (fashion material) and multi-criteria (sustainable fashion). Multi-alternatives are cotton, linen, silk, wool, acrylic, nylon, polyester, rayon, spandex, and mixed. Multi-attributes are material, texture, color, characteristic, comfort, and wearability. Multi-criteria are material fiber, smooth texture, faded color, elastic clothing, useful long, chilly and comfortable. Hybrid approaches and optimal solutions are needed to determine the best choice in decision making for both producers and consumers. The hybrid approach in MADM used is Simple Multi-Attribute Rating (SMART), Multi-Factor Evaluation Process (MFEP), Multi-Object Optimization based on Ratio Analysis (MOORA), Simple Additive Weighting (SAW), and Weighted Product (WP). SMART and MFEP are based on the Non-Benefit Cost Model while MOORA, SAW, and WP are based on a Benefit-Cost Model. The experimental results show that the SMART model with the best alternative is the rayon with the highest value (2.8333). The selection of the MFEP Model with the best alternative is rayon with the highest value (2.8330). The choice of MOORA model with the best alternative is rayon with the highest value (0.2595). The selection of the SAW Model with the best alternative is rayon with the highest value (0.8932). The selection of the WP Model with the best alternative is rayon with the highest value (0.1285). MADM using SMART, MFEP, MOORA, SAW, and WP for sustainable fashion yields the best alternative for consumption and production for the middle-class population in Indonesia.

This paper aims to process daily food consumption based on the Guideline to Healthy Food or the principle of Healthy 4 Perfect 5 (H4P5). The Guideline to Healthy Food does not include the portion and size of daily food consumption, therefore it is perfected into the Guidelines to Balanced Nutrition (GBN). GBN is performed by consuming three servings of protein vegetables, three servings of animal protein, eight servings of carbohydrates, five servings of vegetables, five servings of fruits, and eight servings of water. Each part of the portion has a proportional size and dose based on GBN. The portions are measured by food composition using the optimization process using a Genetic Algorithm (GA). Optimization by a using Genetic Algorithm yielded three outputs, namely, first, the initial objective function (0) compared to the generative objective function (1) produces a value of 6.13: 4.72 (there is an increase in chromosomes, because, the smaller the value, the better the chromosome is). Second, probability mutation is 50% of mutation rate, crossover probability is 5%, the maximum generation is 36, the maximum fitness point is 0.240806, and the size of the population is 6. Third, optimization using the Genetic Algorithm in food composition produces one food model, one consumption model, and one composition model. Thus, the result of this research (food model, consumption model, and composition model) can be a recommendation for food consumption patterns (normal condition) and a reference for national food consumption policies.

This study aims to analyze and determine the effect of the US Dollar Exchange Rate and Inflation on Third Party Funds (TPF) at Bank Nagari Syariah Batusangkar Branch for the period 2013-2018. The type of research used in this research is field research with quantitative research methods using a descriptive approach, and using eviews analysis tools with multiple regression and using the Ordinary Least Square (OLS) estimation method. The results of this study indicate that the US Dollar exchange rate variable with a coefficient value (8.141176), the probability value (0.0332) has a positive and significant effect on Third Party Funds (TPF), the inflation variable has a negative and insignificant effect on Third Party Funds (TPF) with a coefficient value ( -0.697542) probability value (0.1019) while the variable US dollar exchange rate and inflation together have a positive and significant effect on third party funds using the Ordinary Least Square (OLS) method, the F-statistic value is 31.98483 with a probability of 0.009481.