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Irjii Matdoan, Moh. Rahmat
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Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation

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Application of Hashing Method in Medical Term Dictionary Application Irjii Matdoan, Moh. Rahmat; Rasna, Rasna; M Saleh, Sahlan; Sah, Andrian; Lamsir, Seno
International Journal of Engineering, Science and Information Technology Vol 4, No 4 (2024)
Publisher : Department of Information Technology, Universitas Malikussaleh, Aceh Utara, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v4i4.662

Abstract

The number of words or terms that appear and are used in human life makes it difficult for a person to master all of these words. To overcome this, these words or/terms are compiled in a dictionary, one of which is a dictionary of medical terms. This research aims to create software that can perform its function as a medical terminology dictionary program and implement the Hash method into software that can be used for data search. This research applies the hash method to find the hash value using a rolling hash. The hash method uses input text to be transformed into numbers, thus speeding up the computational process. The application of the hash method in the addressing/storage process in the Database is very efficient in terms of time and place. The output appears in the form of word meaning and hash value. The hash value is raised to know the value of the searched term using the rolling hash formula. With this research, it is hoped that searching for the meaning of medical terms in a computerized manner can be consistent with manual searches.
Implementation of Dijkstra and Ant Colony Algorithms for Web-based Shortest Route Search for LPG Gas Distribution Rasna, Rasna; Irjii Matdoan, Moh. Rahmat; Kumala Dewi, Nurlaela; Ariffien, Afferdhy; Lamsir, Seno
International Journal of Engineering, Science and Information Technology Vol 5, No 2 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i2.805

Abstract

National energy needs and efforts to fulfill them are currently vital issues to be discussed and resolved. One type of energy that still has various problems is fuel gas, especially LPG (Liquid Petroleum Gas). The gas scarcity in each region differs; not all regions experience gas shortages, and some areas have excess LPG gas stocks. The problem of the scarcity of 3 kilogram (Kg) LPG gas is not the first time this has happened. In recent months, people in some regions have complained about the scarcity of subsidized 3-kilogram (kg) LPG gas. This situation certainly makes it difficult for the community. Not only does the scarcity hamper community activities, but it also makes the price of gas refills more expensive than usual. With the increasing demand for LPG gas every year, the government must provide large stocks of LPG gas. But what power if the LPG gas stock is less or runs out at specific locations. Therefore, applying gas base route search is needed to overcome the shortage of gas stock at a location. This application applies two search methods, namely the Dijkstra algorithm and the ant colony algorithm, to find the fastest route to the location of the gas base in the XYZ area. In the algorithm process, Dijkstra requires distance data for each city before starting the algorithm process. The Ant Colony Algorithm does not require the distance of each city because, in an Ant Colony, the distance between towns is calculated after the ants complete their journey. From the results of the process of the two algorithms, it is known that the path produced by Dijkstra's algorithm is more consistent and precise than the Ant Colony algorithm, which gives results that are not necessarily the same for each process.
Weather Classification and Prediction on Imagery Using Boltzmann Machine Rasna, Rasna; Irjii Matdoan, Moh. Rahmat; Salat, Junaidi; J, Fitria; Lamsir, Seno
International Journal of Engineering, Science and Information Technology Vol 5, No 2 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i2.806

Abstract

Weather is a physical process or event that occurs in the atmosphere at a specific time and place, as well as its changes over a short period in a particular location on Earth. To produce weather forecast information, there is a series of processes that must be carried out until the weather information is conveyed accurately. The stages involved in the feature extraction process are carried out first. This process is carried out to obtain specific characteristics or features from a dataset. After the feature extraction process has been completed, the next step is to predict the weather based on the input images. To classify the weather on Earth using various algorithms, one of which is the Machine Boltzmann. The pattern recognition method used is Machine Boltzmann as an application of a simpler and more complex method. Generally, the weather prediction system using Machine Boltzmann consists of several stages, namely image acquisition, greyscale processing, segmentation/location using Sobel edge detection, classification using the Machine Boltzmann method, and finally producing output in the form of weather class results. The classification process in this research involves images of clear, cloudy, and rainy weather as inputs. The output of the system is the determination of whether the input weather image falls into the category of clear, cloudy, or rainy weather. The results of the study show that the classification of weather based on captured images has the highest accuracy for clear weather, with a percentage of 73.33%. For cloudy weather, the success rate is equal to the error rate, which is 50%, while rainy weather was not recognized at all.
Forecasting the Inventory of Milled Dry Grain Using the Lot Sizing Method at Markom Rice Mill Ariffien, Afferdhy; Lamsir, Seno; Rasna, Rasna; Aini, Qurrotul; Irjii Matdoan, Moh. Rahmat
International Journal of Engineering, Science and Information Technology Vol 5, No 2 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i2.817

Abstract

Today's industrial activities are increasing with sophisticated technology, all applied to satisfy consumers in various services. One of the important parts of an industry is the inventory of goods. This is related to the continuity of the resulting production. In meeting the needs of consumers, a plan is needed in production so that there is no shortage of raw materials and the production process does not stop. Grain is an agricultural commodity whose demand and production levels occasionally increase. We can see that until now, our country, Indonesia, still imports rice from other countries, where rice is the main production product produced from grain. The problem can be solved with the Lot sizing method used in this study, which is used to determine the size of the order quantity. In the rice mill itself, grain storage has a limited capacity, so it cannot be directly stored with a large capacity when the price of grain is down. Applying this method as an application will make it easier to manage grain inventory at the rice mill and estimate inventory costs for the next 1 () year. The results of the lot sizing calculation (silver meal) show that for the next year, the smallest cost of procurement of dry milled grain (MDG) demand is obtained from the procurement of demand every month. In other words, procurement is more appropriate every month or period so that the costs incurred for grain inventory are smaller. The following data are the results of the silver meal lot sizing calculation: (1) 39015.4 kg, (2) 35871.2 kg, (3) 39536 kg, (4) 33894.8 kg, (5) 31402 kg, (6) 27982.5 kg, (7) 41461.9 kg, (8) 35336.7 kg, (9) 41305.6 kg, (10) 45717.5 kg, (11) 42007.9 kg, (12) 50828 kg. The cost incurred per order is Rp. 6,000,000
Co-Authors Ariffien, Afferdhy J, Fitria Kumala Dewi, Nurlaela Lamsir, Seno Qurrotul Aini Rasna, Rasna Sah, Andrian Sahlan M Saleh Salat, Junaidi