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INDONESIA
INFOKUM
Published by SEAN INSTITUTE
ISSN : 23029706     EISSN : 27224635     DOI : -
Core Subject : Science,
Computer Science & IT
The INFOKUM a scientific journal of Decision support sistem , expert system and artificial inteligens which includes scholarly writings on pure research and applied research in the field of information systems and information technology as well as a review-general review of the development of the theory, methods, and related applied sciences. Software Engineering. Image Processing Datamining Artificial Neural Networks
Arjuna Subject : Ilmu Komputer (semua kategori) - Kecerdasan Buatan
Articles 842 Documents
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APPLICATION OF DATA MINING TO DETERMINE THE LEVEL OF FISH SALES IN PT. TRANS RETAIL WITH FP-GROWTH METHOD Tamba, Saut Parsaoran; Sitanggang, Mario; Situmorang, Bimo Christhoper; Panjaitan, Gracia Laura; Marlince Nababan
INFOKUM Vol. 10 No. 02 (2022): Juni, Data Mining, Image Processing, and artificial intelligence
Publisher : Sean Institute

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Abstract

Trans Retail Indonesia is one of the shopping places in the city of Medan. Trans Retail Indonesia is engaged in providing raw materials such as selling fish. However, at Trans Retail Indonesia, sales data collection still uses a manual system, so this store has not been able to determine which type of fish has the highest level of sales. So this affects the availability of goods and results in a lack of stock in this store. So we need a data mining system with the FP-Grwoth method to analyze fish sales data so that the results of the analysis become a reference for stores in determining the supply of fish stocks. The results of the analysis carried out by researchers from the data obtained are the fish that is most in demand is the Jengka Split with a value of 90%, and if you take a split Jengka fish, you will take anchovy buntiaw with a value of 54%. If you take an anchovy, it will take a large anchovy and will take a white Peda fish with a value of 100%.
DATA MINING SYSTEM IMPLEMENTATION BY GROUPING SALES AT PT. GANDATAMA CROWN manullang, sehat saorasi; Palma Juanta
INFOKUM Vol. 10 No. 02 (2022): Juni, Data Mining, Image Processing, and artificial intelligence
Publisher : Sean Institute

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Abstract

This research discusses how to classify the data from period to period by implementing the Apriori method. The data used in this research is sales in 2021-2022. Researchers have carried out stem analysis using the a priori data method used in February 2021. This system can classify sales according to the type of goods that consumers are more interested in. So the types of sales items that are included in the best-selling sales pattern are, 40%, 60%, 70%.
ANALYSIS OF THE K-NEAREST NIGBOAR METHOD TO DETERMINE THE ELIGIBILITY OF INTERNSHIP STUDENTS AT PRIMA INDONESIA UNIVERSITY Shriram ram; Medalsan C; Yanmil V. H. Purba; Jepri Banjarnahor
INFOKUM Vol. 10 No. 02 (2022): Juni, Data Mining, Image Processing, and artificial intelligence
Publisher : Sean Institute

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Abstract

This study discusses how to determine the feasibility of interns who deserve to be awarded, by applying the K-NN method. Based on the problem in this study, it is difficult to determine prospective interns who will be rewarded for those who have special abilities, so this system aims to solve these problems using the K-NN method.. In this study, we have tested data with 5 types of criteria, where in this test we will try to collect the values that will be processed individually by inputting the values 1, 3, 4 and 2. Based on calculations, with discipline: 1, Have Expertise: 2, Able to Work in Team: 3, Able to communicate well: 1, then the result: Decent.
Data Mining Analysis To Determine The Inventory Of Food Sales During The Pandemic With The K-Means Clustering Method David C. Hutajulu; Yulianus Zega; Unggul Siregar; Jepri Banjarnahor
INFOKUM Vol. 10 No. 02 (2022): Juni, Data Mining, Image Processing, and artificial intelligence
Publisher : Sean Institute

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Abstract

Currently, many businesses are no longer operating because people no longer shop directly for direct sales, but now many people shop online. This is one of the problems faced by sales that do not market their goods online, so there has been a buildup of inventory for the last 2 years during this pandemic. It is difficult for the company to know which types of goods will be sold a lot and a little every day because the system is still in use only for input. So with that there needs to be a system that solves the problem. In this study, the K-Means method will be used to determine the most sales. This system has carried out the clustering process with the K-Means method by utilizing the data of past items. The results of this research in cluster 1 with a value of Cluster 1 -> 358.64 245.9775 while in Cluster 2, Cluster 2 -> 45.39 22.824285714286.
ANALYSIS OF SUGENO'S FUZZY INFERENCE SYSTEM IMPLEMENTATION TO DETERMINE THE NUMBER OF GOODS ORDERS AT SUZUYA SUPERMARKET Hendrik K. Laoli; Annisa Maulida; Jegedis Pri; Yonata Laia
INFOKUM Vol. 10 No. 02 (2022): Juni, Data Mining, Image Processing, and artificial intelligence
Publisher : Sean Institute

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Abstract

Currently, supermarkets in Indonesia had become a shopping place in great demand by the public, in terms of strategic location, also with the types of goods available such as food that people need every day. With so many shopping enthusiasts to supermarkets such as Alfamart, Suzuya then every types of goods there were a lot that must be done to increase the stock of goods to remain available, but because the number of types of goods would be provided, employees for the stock of goods were overwhelmed in checking the stock of goods would be carried out additional stock. Therefore, there needs to be a system that would help every employees work in the supermarket, especially those who did the stock recording of goods in warehouse employees. In this study, analyzed Sugeno's Fuzzy Inference System in order to provide effective and efficient work in the ordering section of goods supplied at supermarkets. The results of this study concluded that using Sugeno's Fuzzy Inference System system was faster in determining the stock to be provided to supermarkets
Analysis of Satisfaction the fast Food Restaurants using the C.45 Method in Medan Fahri Chairullah; Muhardi saputra; Nahla Naisylla Lubis; Dedi Andika Sihombing; Palma Juanta
INFOKUM Vol. 10 No. 02 (2022): Juni, Data Mining, Image Processing, and artificial intelligence
Publisher : Sean Institute

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Abstract

Analysis of customer satisfaction with fast food restaurants at one of the fast food restaurants, namely KFC in the city of Medan, is an interesting thing that the author wants to do. This restaurant has many branches. The city of Medan which consists of 21 sub-districts has at least 1 (one) KFC. With so many restaurants, there are various ratings expressed by the customer. Because there are slight differences between one another. when it comes to taste, there will be one voice for the consumers, but not on the price, facilities and services. However, there are also consumers who state that the taste is not good at one of the branches. Research data taken as many as 100 random consumers from different locations. The method used to analyze customer satisfaction is the c4.5 algorithm. The results obtained are the analysis of customer satisfaction which is the highest in taste at 64%. If it tastes good then the customer will feel very satisfied. If there is a bad taste, then the customer considers other things to make them feel satisfied with the fast food restaurant
CREDIT CONGESTION ANALYSIS AT PT. SINARGA GALANG USING THE C4.5. ALGORITHM METHOD Muhardi Saputra; Jenifer, Jenifer; Denisyah Sitorus; Situmorang, Devi Br
INFOKUM Vol. 10 No. 02 (2022): Juni, Data Mining, Image Processing, and artificial intelligence
Publisher : Sean Institute

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Abstract

Credit congestion is a serious problem that is often faced by companies engaged in credit services. PT. Sinarga Galang is a company engaged in selling cars with cash or credit payment systems. The author takes data on the company's credit system in the bad category. Because the company can't analyze the credit jams that occur so it doesn't produce the right decisions in terms of filtering consumers who want to do credit. The number of bad loans, the company will go bankrupt but do not use the credit system, it will reduce sales as well and eventually can go bankrupt as well. For this reason, proper analysis is needed in classifying corporate credit bottlenecks. The method that the author uses is the C4.5 algorithm. This method is often used in research in the case of data classification because the results are precise. The results obtained in the study are a decision tree in the form of (1) if the dependents are: stuck (2) the dependents are few: stuck (3) the dependents are large: the salary is high: smooth (4) the dependents are the: moderate salary: stuck (5) the dependents are many : meager salary : smooth. These results are seen from the influence of the criteria that occur in the data, namely the number of dependents, salary / business income, monthly tenor or home ownership status. The data processing used is 100 data
Analysis of Academic Service Satisfaction Levels From the Perspective FTIK UNPRI Students Use the Method Importance Performance Analysis(IPA) Angga Snidres Girsang; Elida Mardiana Manik; Egi Suranta Bangun; Saut Parsaoran Tamba
INFOKUM Vol. 10 No. 02 (2022): Juni, Data Mining, Image Processing, and artificial intelligence
Publisher : Sean Institute

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Abstract

In the field of education, the level of comfort is an important service in activities. Especially students who are studying, lectures will be very enjoyable if the services provided are in line with expectations. In the academic section of the Prima Indonesia University campus, there are still many things that are beyond expectations. Especially in the academic service section, the level of student satisfaction has not been taken into account. Because there are still many students who do not feel that they have good facilities. So this study will test the academic services of the Prima Indonesia University campus. Student realities and expectations can be collected with questionnaire data. Students who are respondents will provide results in the form of a dataset that will be processed using the SPSS version 23 data processing application. The results of data testing will be carried out in the Importance Performance Analysis (IPA) method to get better and detailed results. The use of the IPA method will produce a catesian diagram as a result of the test. So that the results of the dataset are obtained to be used as conclusions in this study. From the results of the average level of conformity contained in the table for calculating the level of conformity. Got an average of 97%. Based on this, the level of service provided is close to the respondent's expectations. From the results of the average level of conformity contained in the table for calculating the level of conformity. Got an average of 97%. Based on this, the level of service provided is close to the respondent's expectations. From the results of the average level of conformity contained in the table for calculating the level of conformity. Got an average of 97%. Based on this, the level of service provided is close to the respondent's expectations.
Triple Exponential Smoothing Analysis in Predicting Numbers Request for Delivery of Logistics CV. Lotus Mas Express Elvis Sastra Ompusunggu; Andrean Wirjana; Silemberesen Silemberesen; Dea Junia Dea Junia
INFOKUM Vol. 10 No. 02 (2022): Juni, Data Mining, Image Processing, and artificial intelligence
Publisher : Sean Institute

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Abstract

CV. Teratai Mas Express is a company engaged in services, namely transportation services or commonly called expeditions. But this company specializes in transportation logistics. The problem that is often faced by this company is that it often suffers losses due to being unstructured in terms of stock transportation inventory to the number of delivery requests. Especially in certain seasons and usually the corn harvest season. Demand rose, but companies often made mistakes in providing their freight. Sometimes advantages and sometimes disadvantages. Excess or shortage of these supplies in a high level. Suppose the company provides 14 transportations but only 8 is used or vice versa, resulting in a large loss. For this reason, a precise prediction calculation is needed so that the number of logistics delivery requests can be predicted efficiently in order to reduce large losses. The prediction method that I use is Triple Exponential Smoothing. This method is suitable for use in this case because the number of logistics delivery requests increases in certain seasons and this method can analyze it.
Recommendations for Placement of Internships in Industry with the Distance from Average Solution (EDAS) method based on student scores Tomy Satria Alasi; murdani murdani
INFOKUM Vol. 10 No. 02 (2022): Juni, Data Mining, Image Processing, and artificial intelligence
Publisher : Sean Institute

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Abstract

Currently, the Indonesian Ministry of Education has implemented a new rule with every student expected to have an internship in the industry. With the aim of each student being able to understand the situation of the world of work so that preparation before completing a bachelor's degree is stronger. However, one of the problems found is that students cannot determine the placement of internships. This study tries to provide a solution to these problems by applying the rules from the head of the study program to provide recommendations to students. These rules are built based on student academic scores stored in the campus database which is controlled by the head of the study program. The method used is Distance from Average Solution (EDAS). The EDAS method is to determine the highest ranking using PDA is the positive distance from the average and (NDA) is the negative distance from the average. The results of this study provide recommendations automatically in the hope of supporting the current campus academic system.

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