JOURNAL_SUBMISSIONOpen AccessMetadata saja
2019•
Seasonal vegetable plants are one of food commodity in Indonesia which contributed significantly in supporting the growth of national economy. Fuzzy Logic using Tahani Model is appropriate to analyze the harvested area, production, and yields of food commodity. It is based on query in fuzzy database. It is also can be proposed as recommendation for both government and entrepreneur in achieving in the target based on query. Target is main priority of food commodity. Fuzzy query is harvested area (medium), production (sufficient), and yield (normal). Non fuzzy query is commodity (export commodities), harvest (plants harvested several times), and form of product (fresh fruit). Result showed that eggplant (0.6587), tomato (0.6023), cucumber (0.5865), capsicum frutescens (0.2901), and capsicum annum (0.1581) as recommendation for priority of national food policy.
JOURNAL_SUBMISSIONOpen AccessMetadata saja
2019•
<p>Price, consumption, and production influence global food estimation. Food consumption and food production needs improving affordability, government policy and expert proposition in decision making. Expert have developed a scenario combining direct weather impact on key grain producing regions, indirect impact through crop pathogens, consequences for markets, and stock of global food. Global food production tended to increase, meanwhile consumption under production. In Indonesia, production is under consumption. It is anomaly by global situation and world condition. Government policy is tariff, export, and import. Export food influenced by price food commodity is not stable, meanwhile food import tended to increase because by national food consumption increasing demand. Government policy and expert proposition to modern society, need Expert System is increasing rapidly. In Artificial Intelligence, Expert System is a computer system that emulates the decision making ability of a human expert. There are two reasoning strategies in Expert System: Forward Chaining and Backward Chaining. The aim of this paper is to identify which reasoning strategy system (Forward Chaining). This paper focus on the concept of knowledge representation in Artificial Intelligence and implementing of Forward Chaining on Food Affordability. Food Affordability used to planning of food in the future. Finally, Inference using Forward Chaining on Food Affordability, the result it is good and can be used to planning and policy on national food.</p>
JOURNAL_SUBMISSIONOpen AccessMetadata saja
2018•
This paper aims to implement Fuzzy Logic for cost prediction. Fuzzy Logic using Tsukamoto Model and Sugeno Model. Predicted costs consist of communication cost, transportation cost, and social cost as the external cost. The external cost is one component of living cost. High external cost becomes one of the causes of the high cost of living. The high cost of living is one of the factors causing high-cost economy. In this case, the cost prediction using Fuzzy Logic. Experimental results show that Fuzzy Logic using Tsukamoto Model with value is 1891. Fuzzy Logic using Sugeno Model with value 1621. Both models produce a feasible cost prediction. Feasible is meaning accurate and proper (value cost between low cost and high cost from all of cost). There are 46.56 % of the population of middle class in Indonesia. This means that 46.56% of the population of Indonesia has the potential to reduce the high cost economy. High cost economy (living cost) can be reduced, it can drive economic growth (social cost) and be able to improve social welfare (social cost).
JOURNAL_SUBMISSIONOpen AccessMetadata saja
2016•
<p class="Abstract">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.<em></em></p><em>Key words: clustering, calculation, classification, fruit and vegetable consumption</em>
JOURNAL_SUBMISSIONOpen AccessMetadata saja
2016•
<p>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. </p><p>Key words: filter, information, website, teaching material, find and get</p>
JOURNAL_SUBMISSIONOpen AccessMetadata saja
2016•
<p style="margin: 1em 0px; color: #111111; font-family: Arial, Verdana, Helvetica, sans-serif; font-size: 11.2px; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-weight: normal; letter-spacing: normal; orphans: 2; text-align: left; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px; -webkit-text-stroke-width: 0px; background-color: #fafafa;">This research is conducted to apply the Analytical Hierarchy Process (AHP) method applied as model of Decision Support System (DSS) in choosing lecturer at STIKOM Pelita Indonesia Pekanbaru. Data collected by through observation and interview done in shares of administration academic at college. Here in after data analyzed to learn the pattern from method used and added with the reference from literature. Experiment done use the Expert Choice software known that method can yield the optimal decision in election instructor staff. There by the method recommended to be applied to getting optimal result.</p><p style="margin: 1em 0px; color: #111111; font-family: Arial, Verdana, Helvetica, sans-serif; font-size: 11.2px; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-weight: normal; letter-spacing: normal; orphans: 2; text-align: left; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px; -webkit-text-stroke-width: 0px; background-color: #fafafa;"> </p><p style="margin: 1em 0px; color: #111111; font-family: Arial, Verdana, Helvetica, sans-serif; font-size: 11.2px; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-weight: normal; letter-spacing: normal; orphans: 2; text-align: left; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px; -webkit-text-stroke-width: 0px; background-color: #fafafa;">Keywords: Decision Support System, Analytical Hierarchy Process, Expert Choice Software</p>
