Prediksi Clustering, Calculation Dan Classification Fruit and Vegetable Consumption

Prediction model using combination of K-Means Clustering, Excel Function, and Naïve Bayes Classifier. Process is dataset, clustering, calculation, classification and prediction. Dataset source on BPS 2013 about consumption of fruit and vegetable. Clustering using K-Means Clustering. Clustering by output Cluster 1, Cluster 2, and Cluster 3. Calculation using Excel. Calculation by output Priority Yes and Priority No. Classification using Naïve Bayes Classifier. Classification by output Class Good and Class Bad. All data processing for clustering, calculation, and classification using Excel. Experimental results on BPS 2013 Dataset show percentage of fruit consumption 42,42% Class Good (class above average) and percentage fruit consumption of fruit consumption 57,58% Class Bad (class below average). Percentage of vegetable consumption 45,45% Clas Good (class above average) and percentage of vegetable consumption 54,55% Class Bad (class below average). Clustering, calculation and classification can be combined becamed prediction model

Aplikasi Ahp Sebagai Model Spk Pemilihan Dosen

This research is conducted to apply the Analytical Hierarchy Process (AHP) method applied as modelof Decision Support System in election instructor staff at STAIN Batusangkar. Data collected by throughobservation and interview done in shares of administration academic at college. Here in after data analyzed tolearn the pattern from method used and added with the reference from literature. Experiment done use theMicrosoft Excel/ Expert Choice software known that method can yield the optimal decision in election instructorstaff. There by the method recommended to be applied to getting optimal result

Teknik Menyaring Informasi Internet Untuk Mendapatkan Materi Belajar

A important component of teaching learning process is teaching material. A good teaching material will produce optimal and new (recent) teaching learning process. Internet is a source where we can find and get the new teaching recently. To find the teaching material, we have to know the computer identity where the teaching material is located. The Internet can be categories into 2 categories namely edu (education) for computer which located in United State and ac (academic) which is followed by country code for computer which located in the outside of United State. Filtering information with Search Engine include Power Searching Conceptual with application need technique for get information is expected

Multi-Attribute Decision Making Using Hybrid Approach Based on Benefit-Cost Model for Sustainable Fashion

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