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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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Analysis of the location of the installation of cellular towers by the method Simple Multi Attribute Rating Technique Exploiting Rank (SMARTER) Putra Edi Mujahid; Ryan Chandra; Andri Syahputra Tarigan; Maya Frida Panjaitan
INFOKUM Vol. 10 No. 02 (2022): Juni, Data Mining, Image Processing, and artificial intelligence
Publisher : Sean Institute

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Abstract

Cellular is the most important thing for today's society. For this reason, a strong signal is a priority as a means that must exist to support the cellular to work properly. Installation of cellular towers for the need for strong signal is important. PT. Solusi Tunas Pertama is a company engaged in cellular tower construction services. The problem found is that it is difficult to determine the right tower installation due to the conditions and environment as well as the impact of the cellular tower. For this reason, an analysis is needed in determining the right area for the installation of the cellular tower. In this study, the authors use the criteria of population density, distance, access, existing towers and costs. These five criteria are often used by companies for location assessment. The author uses the SMARTER method in analyzing the determination of the location of the cellular tower installation of PT. Solusi Tunas Pertama. The results obtained are that the Gunung Kiri Village area is the right location for the installation of cellular towers with a value of 60,58929 compared to other locations, namely Sisiran Forest and Balunga Rice Fields. The author conducted this research with the aim of assisting the company in determining the location of tower installation with the right confidence without the need to just guess so that the decision is not right.
IMPLEMENTATION OF THE E-VOTING SYSTEM IN THE ELECTION OF THE OSIS SMA DHARMA PANCASILA VOCATIONAL SCHOOL BASED ON WEB-BASED METHODS RAPID APPLICATION DEVELOPMENT (RAD) Eka Hayana Hasibuan; Roy Nuary Singarimbun; Baginda Harahap
INFOKUM Vol. 10 No. 02 (2022): Juni, Data Mining, Image Processing, and artificial intelligence
Publisher : Sean Institute

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Abstract

In manual voting often results in errors in vote counting, The goal to be achieved from making this e-voting application is to be able to assist committee officers in calculating the number of voters and election results quickly and accurately. For data analysis techniques using Rapid Application Development (RAD) method, which is one of the data analysis while to design this application the method used is object-oriented design using the Unified Modeling Language (UML). Based on the analysis of system requirements, a system was created web-based student council chairman election. The choice of a web-based system was due to This website is widely known by the public. So to finish The problem was proposed by a web-based e-voting system. In conclusion with With this application, general elections can run honestly and fairly and can minimize errors that can be made by humans or reduce manipulation and fraud that can occur.
COMPUTER LAB NETWORK DESIGN USING MICROTIK ON SMK DHARMA PANCASILA Dinur Syahputra; Ellanda Purwawijaya; Fithrie Soufitri; Lina Lina
INFOKUM Vol. 10 No. 02 (2022): Juni, Data Mining, Image Processing, and artificial intelligence
Publisher : Sean Institute

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Abstract

This research uses Mikrotik to design a computer lab at SMK Dharma Pancasila. After implementing the network built at SMK Dharma Pancasila, Sungai Kanan District, it will be obtained a knowledge that; Networks built with Mikrotik provide cost efficiency because the client does not require high-specification hardware and also does not require certain software. Then the distribution of the network used on the proxy is very useful so that the client's performance can be maximized. And with the network, network administration can be done more easily because it is centralized in Mikrotik.
APPLICATION OF DATA MINING TO IDENTIFY DIABETES MELLITUS USING THE SUPPORT VECTOR MACHINE (SVM) ALGORITHM AND KNN Windania Purba; Yessy Yessy; Riski Nofarianus Gulo
INFOKUM Vol. 10 No. 02 (2022): Juni, Data Mining, Image Processing, and artificial intelligence
Publisher : Sean Institute

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Abstract

Damage to the performance of human organs is very detrimental Received Revised Accepted And is the source of the most problems at this time. One of the diseases that is the number one killer in the world is diabetes mellitus. Diabetes mellitus is a metabolic disease characterized by hyperglycemia caused by and obstacle in insulin secretion from insulin action or both. Diabetes mellitus is divided into several types, type 1 diabetes mellitus generally gives rise to indications before the patient is 30 years old. Although in fact the indications of the disease can arise at any time. This study aims to apply the Support Vector Machine (SVM) and K-Nearest Neighbor (KNN) method to identify diabetes mellitus and calculate the comparison value of the accuracy of the two algorithms. From the results of this study. It can be concluded that the Support Vector Machine (SVM) algorithm produces an accuracy value of 76% while the accuracy value of the K-Nearest Neighbor (KNN) algorithm is 75%
APPLICATION OF DATA MINING TO PREDICATE STOCK PRICE USING LONG SHORT TERM MEMORY METHOD Sonia Novel Lase; Yenny Yenny; Owen Owen; Mardi Turnip; Evta Indra
INFOKUM Vol. 10 No. 02 (2022): Juni, Data Mining, Image Processing, and artificial intelligence
Publisher : Sean Institute

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Abstract

Investing some of our wealth to invest in stocks is highly recommended considering the fluctuating nature of stock prices, meaning that stock prices can go up and down at any time depending on the conditions and phenomena that occur on the stock market. Stock investment includes having a high risk of loss but also by taking that risk it is also possible to get high profits (High Risk High Return). Shares are proof of ownership of company value or proof of equity interest. Shareholders are also entitled to receive dividends (profit sharing) according to the number of shares they own. This study aims to make it easier for everyone who wants to invest in Google and Tesla stocks and implement the long short term memory method for stock price prediction. This data mining research resulted in a Root Mean Square Error (RMSE) value of 1.80%, which means the prediction results are very accurate with real data and the average difference between real stock price data and predicted data is $3 -$15.
USING THE NAIVE BAYES CLASSIFIER METHOD ON SOCIAL MEDIA SENTIMENT ANALYSIS Windania Purba; Ade Syahpitri; Grace Fitri Anggi Munthe
INFOKUM Vol. 10 No. 02 (2022): Juni, Data Mining, Image Processing, and artificial intelligence
Publisher : Sean Institute

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Abstract

Social media is one of the many technological developments that greatly affect human communication and socialization systems. Most people voice their opinions through social media, with the aim that they can be heard and seen by the general public. However, the use of social media often backfires for the owners themselves due to their excessive use. In particular, this study discusses the grouping of sentiment data from Prima Indonesia University students where to seek negative and positive opinions from students as a benchmark for online learning methods carried out in the campus environment. The data grouping process uses the nave Bayes algorithm, because this algorithm has been widely used in data processing. The tests carried out in this study resulted in an accuracy of 68% of the dataset selected as the data training process. This results in a classification of new data to find out a sentiment on students belonging to the negative or positive class.
IMPLEMENTATION OF DATA MINING WITH NAVE BAYES CLASSIFIER TO SUPPORT THE MARKETING STRATEGY OF THE MARKETING SECTION AT PT. MEGA PANCA JAYA BUMI Wahyudi, Ricki; Ramadhani, Putri Saumi; Utomo, Ardy Budi; Anita, Anita
INFOKUM Vol. 10 No. 02 (2022): Juni, Data Mining, Image Processing, and artificial intelligence
Publisher : Sean Institute

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Abstract

In the business world, competition is something that is already familiar to business actors. The bigger the business can compete, the bigger the challenges faced by business actors. One of them is a company in residential property owned by PT. Mega Panca Jaya Bumi. The newly developing company should have thought of strategies in marketing its business. In order to avoid a decrease in interest and profits, it is only natural that these new strategies can be implemented in data processing techniques or Data Mining which is expected to increase marketing and the number of markets is wider. The data processing in this study uses the Naïve Bayes Classifier Algorithm in its calculations. Data taken from the company as many as 300 records from 2019 to 2021. In this study, the process of the data experiment was carried out by applying the Python programming language version 3.8 technology. The results of testing the data got an accuracy rate of 56%
SMART HOME SYSTEM BASED ON THE INTERNET OF THINGS USING NODEMCU AND ANDROID APPLICATIONS Muhammad Syahputra Novelan; Aminuddin Indra Permana
INFOKUM Vol. 10 No. 02 (2022): Juni, Data Mining, Image Processing, and artificial intelligence
Publisher : Sean Institute

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Abstract

Smart home systems aim to maximize surveillance, monitoring, security and so on. The way this system works is that it integrates telecommunications and system controllers from a chip or NodeMCU, so it is called the Internet of Things. In this study, create or design a smart home that aims to make it easier to control existing equipment at home remotely and when traveling out of town with the Internet Of Things system. Besides, it's not just controlling remotely but by monitoring it by using an Android smartphone. The devices used in the Smart Home system design are divided into several parts, namely input, process and output. Part of the input consists of a room temperature sensor, part of the process consists of a Microcontroller or uses a NodeMCU, and part of the output is an LED as an indicator and sound or using a Buzzer module. The results of the tests carried out by the system designed that the smart home runs well overall starting from the android application and receiving data from the microcontroller and sending notifications to the sensor readings
Asistensi Implementation of Database-Based CodeIgniter PHP Framework on School Alumni Data (Case Study of Alumni Data for SMK Taman Siswa Medan) Aripin Rambe
INFOKUM Vol. 10 No. 02 (2022): Juni, Data Mining, Image Processing, and artificial intelligence
Publisher : Sean Institute

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Abstract

By using the CodeIgniter PHP framework, an information system web application software can be created to help manage data. In this study, software was developed to help manage school alumni data. By using the security layer in the CodeIgniter PHP framework, data filtering can be done to prevent the exploitation of security vulnerabilities, which include Cross-site Scripting (XSS) and SQL Injection. This can be seen from the test results that only produce low level warnings. So the quality of the software developed in terms of security is quite good.
SENTIMENT ANALYSIS OF PRODUCT REVIEWS DATA ON TOKOPEDIA BY COMPARING THE PERFORMANCE OF CLASSIFICATION ALGORITHMS Dwi Widiastuti; Isram Rasal; Dessy Wulandari Asfary Putri
INFOKUM Vol. 10 No. 02 (2022): Juni, Data Mining, Image Processing, and artificial intelligence
Publisher : Sean Institute

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Abstract

Social media is a medium where people can express their opinion on something. Opinion mining or sentiment analysis, which is studying people's sentiments towards certain entities. This can be used by companies to find out people's responses to a sales product. Sentiment analysis has received a lot of attention in recent years. Sentiment analysis is one of the main tasks of NLP (Natural Language Processing). In this paper, sentiment polarity categorization becomes the basis for sentiment analysis problems in product reviews. A general process for sentiment polarity categorization is proposed with a detailed description of the process. The data used in this study is an online product review collected from the Tokopedia application. Classification is carried out on sentence level categorization and star rating level categorization. There are three models used to compare the classification process, namely SVM, Random Forest, and Naïve Bayes models. The results of this research paper are in the form of a comparison of the performance of the three models against the polarity categorization of product review sentiment on Tokopedia

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