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Building of Informatics, Technology and Science
Published by Forum Kerjasama Pendidikan TInggi
ISSN : 26848910     EISSN : 26853310     DOI : -
Core Subject : Science,
Computer Science & IT
Building of Informatics, Technology and Science (BITS) is an open access media in publishing scientific articles that contain the results of research in information technology and computers. Paper that enters this journal will be checked for plagiarism and peer-rewiew first to maintain its quality. This journal is managed by Forum Kerjasama Pendidikan Tinggi (FKPT) published 2 times a year in Juni and Desember. The existence of this journal is expected to develop research and make a real contribution in improving research resources in the field of information technology and computers.
Arjuna Subject : -
Articles 889 Documents
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Penerapan Metode Case Based Reasoning Untuk Diagnosa Penyakit Kulit Akibat Virus Eksantema Berbasis Web Parwan Harahap; Jeperson Hutahaean; Muthia Dewi
Building of Informatics, Technology and Science (BITS) Vol 4 No 2 (2022): September 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i2.2092

Abstract

In the current condition of the patient, if he has experienced early symptoms of skin disease due to the exanthema virus, it is felt that he cannot directly consult with a dermatologist because of the high cost and limited time for specialists to carry out activities in the hospital. So the author needs to make an expert system application that can overcome this. Through this application, users can consult with the system like consulting an expert to diagnose symptoms that occur to users and find solutions to problems encountered. This expert system is made by providing appropriate or not or with several choices of answers that are recommended from the symptoms that occur. System. Diagnosing skin diseases due to exanthema virus, the author uses the Case Based Reasoning method. The CBR method is a weighting technique by comparing new cases with old cases. With the diagnosis based on the data provided by the patients and experts then analyzed by case based reasoning method and stored as a knowledge database in the expert system. So that this expert system can help to take solutions for handling problems when patients suffer from skin diseases due to the Exanthema Virus.
Implementasi Robot Orang-Orangan Sawah Supply Energi Matahari Memakai Microcontroller Ahmad Dahlan Simanjuntak; Jhonson Efendi Hutagalung; Abdul Karim Syahputra
Building of Informatics, Technology and Science (BITS) Vol 4 No 2 (2022): September 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i2.2101

Abstract

Sparrows are a type of pest that is very detrimental to rice farmers, even though these bird pests are small in size but in very large numbers, causing rice farmers to be overwhelmed in protecting rice from pests. Efforts made by farmers in protecting rice from bird pests by using scarecrows that work less effectively, it is necessary to have a scarecrow robot that can work effectively by utilizing solar heat as an energy supply. The rice field robot will be placed in the middle of the rice field that has issued a grain with a size of 20mx20m by utilizing the LDR sensor as a switch to turn on and off automatically, where the robot is equipped with 4 sound sensors placed in each corner of the rice field to detect the sound of birds on the ground. when the robot's sound sensor detects the sound of bird pests, the DC motor mounted on the robot body will move to rotate the robot body left and right along with the servo installed on the two robot arms will move in opposite directions from 00-1800 or 1800-00 and the DFPlayer will make a sound to scare away bird pests that will attack rice. Finally, the author hopes that this research can be further developed so that it can increase the use of the robot in bird repellent
Mesin Pendeteksi Uang Palsu Dengan Sensor LDR Berbasis Kecerdasan Buatan Sri Maharani; Jhonson Efendi Hutagalung; Abdul Karim Syahputra
Building of Informatics, Technology and Science (BITS) Vol 4 No 2 (2022): September 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i2.2102

Abstract

Money is a very important thing for human life in meeting the needs of life, as a medium of exchange in payment for the buying and selling process. The importance of money causes some people to try to have as much money as possible, even in a way that is against the law like make and circulate counterfeit money. Counterfeit money is counterfeit currency that is produced without legal authorization and permission from the state or government. The circulation and manufacture of counterfeit money is very detrimental to the economy of the country and the small community because it is difficult to distinguish counterfeit money by naked eye and tools to detect counterfeit money are not commonly used and existing tools do not detect paper money through the holographic bars contained in banknotes. The purpose of this study was to determine whether banknotes were included in the original or counterfeit category using LDR sensors, ultrasonic sensors, UV lamps, lasers, and UV sensors. Ultrasonic function to read the distance, if appropriate, it will automatically turn on the UV lamp which will be captured by the UV sensor, so that the holograms on the banknotes can be clearly seen and the laser is used to illuminate the bars on the money if the laser does not penetrate and the light will be received by the banknote. LDR sensor that adjusts to a predetermined value range, the results can be seen on the LCD screen and hear the sound from the speakers. It is hoped that the existence of this money detector can be used to help people avoid the circulation of counterfeit money and develop it further
Sistem Pakar Untuk Mendeteksi Penyakit Mata Menerapkan Metode Case Based Reasoning Norma Jaya Telambanua; Nofriadi Nofriadi; Ari Dermawan
Building of Informatics, Technology and Science (BITS) Vol 4 No 2 (2022): September 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i2.2116

Abstract

The problem that is often faced by the general public is the difficulty of knowing the occurrence of eye disease in humans because it is caused by different symptoms, so if the eye is disturbed and we ignore it, it could be an early symptom of eye disease that can be fatal. Given that experts and practice hours are limited, so that patients cannot consult experts anytime and anywhere, an expert system is needed. The existence of an expert system can solve problems that occur because the expert system uses an appropriate method. In the expert system, the method used to diagnose an eye disease is the Case Based Reasoning (CBR) method, which is a reasoning process for a previous similar case. In the experiment, it is proven by looking for the level or value of the new case data approach with the old case data data for reference in making decisions on new cases. Therefore, the authors build an expert system application to diagnose disease. In this system the inference used is Case Based Reasoning because the process is carried out to recognize the disease and its symptoms and early characteristics of the disease. The development of this web-based system uses the PHP and Mysql programming languages ​​as the database. This expert system can represent an expert in the field of eye disease to find out eye diseases based on existing characteristics and symptoms and can provide solutions if there are diseases suffered by patients
Sistem Pendukung Keputusan Pemilihan Biji Kopi Arabika Terbaik Menggunakan Metode SMART Supiyandi Supiyandi; Chairul Rizal; Muhammad Noor Hasan Siregar; Eka Putra; Rusmin Saragih
Building of Informatics, Technology and Science (BITS) Vol 4 No 2 (2022): September 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i2.2118

Abstract

Arabica coffee beans are one of the main varieties of coffee beans developed in Indonesia. In making decisions to determine quality Arabica coffee beans, an appropriate system is needed to analyze problems in solving and efficient and accurate data presentation. Therefore, a computer-based system or method is needed to facilitate the selection of the best Arabica coffee beans. This study uses the Simple Multi Attribute Rating Technique (SMART) method. The SMART method is a decision-making method to solve the problem of choosing a multi-objective choice among several criteria, so that later it will be able to produce an effective and efficient analysis. The input criteria that are the priority in selecting the best Arabica coffee beans are aroma with a weight of 25, color with a weight of 25, taste with a weight of 25, dirt content with a weight of 15, and price with a weight of 10. Of the 25 alternatives tested in this system, Gayo Avatara Natural Arabica coffee beans were the best first alternative, followed by Aceh Gayo Wet Hull, Java Ijen Natural, Java Ijen Honey, and Kintamani Natural. This decision support system for selecting the best Arabica coffee beans provides speed, accuracy, and data accuracy in selecting the best Arabica coffee beans which will be used by coffee lovers to provide coffee with a delicious taste. So the results of the decision from 25 types of Arabica coffee, there are 11 types of Arabica coffee with a rating of "Very Good", 10 types of Arabica coffee with a rating of "Good", and 4 types of Arabica coffee with a rating of "Quite Good".
Sistem Pakar Untuk Mendiagnosa Penyakit Lupus dengan Metode Forward Chaining Menggunakan Web Indah Wahyuni Bugis; Jhonson Efendi Hutagalung; Indra Ramadona Harahap
Building of Informatics, Technology and Science (BITS) Vol 4 No 2 (2022): September 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i2.2121

Abstract

Lupus disease can attack humans quickly. The initial symptoms that will arise are the same as common diseases such as high fever, prolonged thrush, and also hair will fall out and start to run out one by one until it will go bald, the form of red rashes that appear on the skin, excessive joint pain in the body, easily tired, weight loss, causing paralysis, there are many other symptoms. The lack of availability of a doctor and the limited knowledge of people in remote areas often make the initial diagnosis of the disease late, therefore the application of an expert system is considered very useful to help diagnose lupus early in view of the time and energy of an expert doctor. In the health sector there is an artificial intelligence called an expert system, which is a computer system that uses knowledge, facts and reasoning techniques in solving problems that can usually only be solved by an expert in their field. This study uses an expert system application method in making decisions using a forward chaining inference engine where the goal driven data will start a search on the initial node to the goal node until it gets results. From the diagnostic process, the system provides a selection of the symptoms experienced by the patient, resulting in CLE type lupus (Cutaneus Lupus Erythematosus)
Sistem Pakar Diagnosa Penyakit Diabetes dengan Menggunakan Metode Bayes Berbasis Web Shella Dwi Pratiwi; Jhonson Efendi Hutagalung; Suparmadi Suparmadi
Building of Informatics, Technology and Science (BITS) Vol 4 No 2 (2022): September 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i2.2124

Abstract

Diabetes Mellitus is one of the non-communicable diseases with the highest proportion in Indonesia and is the sixth highest cause of death in this country. Especially in Asahan District, the number of people with diabetes who died is increasing over time, so there needs to be effective treatment so that diabetes is no longer feared by the public because it is easy to treat. Many patients who experience diabetes are getting worse because they cannot detect the early symptoms of diabetes, which is still considered trivial. There is no information about diabetes and its symptoms, making it difficult to diagnose the disease. In the diagnosis of DM disease is limited to conventional diagnoses with doctors. it is necessary to build a system on a computer application to help diagnose DM. To determine the level of DM disease, an expert diagnostic system was made with the method used in this case is the Bayes method. This method is an approximation to an uncertainty that is measured by probability. Bayes' approach at the time of classification is to find the highest probability by inputting the required attributes and the probability of the disease and related symptoms. The results of the implementation of the system are the selection of symptoms according to the case of experiencing type 1 diabetes because it has a weight = 2 higher than the weight results of other diseases, the system provides the results of the process the system will provide information on what type of DM he is experiencing in order to get a solution with treatment
Sistem Pendukung Keputusan Penentuan Penerimaan Bantuan Pangan Non Tunai Menerapkan Metode Simple Additive Weighting (SAW) Muhammad Fikri; Fauriatun Helmiah; Pristiyanilicia Putri
Building of Informatics, Technology and Science (BITS) Vol 4 No 2 (2022): September 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i2.2127

Abstract

One of the programs established by the government to reduce the burden on the community in meeting basic needs is the Non-Cash Food Assistance Program (BPNT). The Social Service of Batu Bara Regency in determining the acceptance of Non-Cash food assistance has so far been using conventional methods. This makes it less than optimal in determining which people are eligible for this selection of food aid recipients, especially the priority of several people whose names have been registered with the Batu Bara Regency Social Service. In doing this election calculation does not use specific criteria so that the alternatives obtained are not as expected. Besides that, it takes time that is not fast in determining decisions and the results are slow because it must be done by holding a meeting between employees and the head of the department which causes the results of the decision to be not on target. So the Social Service of Batu Bara Regency needs a decision support system to provide alternative choices and make it easier to determine prospective Beneficiary Families (KPM) participants to determine decision assessments for Non-Cash Food Aid Reception. The method used is by collecting data on filling out forms given to village communities and using the implementation of the Simple Additive Weighted (SAW) method as a decision support system in receiving non-cash food assistance at the Batu Bara District Social Service. The results of this research are the best with the highest score with a number of criteria, the chosen one is the name Lestari, who deserves to be recommended as receiving non-cash food assistance, there are also several other names based on the ranking in the calculation of this SPK
The Effect of Initialization Weights for Multi Layer Perceptron Performance on Prediction of House Construction Costs Abdul Rozaq
Building of Informatics, Technology and Science (BITS) Vol 4 No 2 (2022): September 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i2.2130

Abstract

The house is one of the primary human needs besides food and clothing. Therefore, the community will always try their hardest to meet primary needs. For the middle and lower class people, it is going to very difficult to build a residential house because the income does not match the increase in house prices. With an artificial neural network, the middle to lower class people can estimate the costs that must be prepared if you want to build a residential house, of course this will be cheaper than using housing developer services. Based on the data that has been obtained, the researcher is then trained and tested using an artificial neural network with 13 data input, 25 hidden layers, a learning rate of 0.75, the number of iterations of 1000, the best test results are MSE value, 0.1, mean accuracy of 97.22 and computation time of 0,028 seconds
Penerapan Metode Single Exponential Smoothing (SES) dalam Peramalan Jumlah Ikan Nindi Lisnawati; Havid Syafwan; Nurkarim Nehe
Building of Informatics, Technology and Science (BITS) Vol 4 No 2 (2022): September 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i2.2132

Abstract

The fisheries sector is a sector that is one of the factors that can support activities and the Indonesian economy. Fishery resources, especially those in the sea, are natural resources that are freely used by anyone. In carrying out fishing business in Asahan Regency, there has been a cycle of ups and downs from the last ten years, so that the fish supply is not in accordance with its needs. Besides that, it takes a long time to find out the number of fish according to the origin of the catch if there is no technique used. Because this cycle occurs in fish production, it is not yet known how much fish production in the coming year will meet their needs, whether it will increase or decrease, the Government and fishermen in Asahan must be able to take policies to get solutions to these problems. So we need a method to predict the number of fish catches in order to know the predictive value in the next period by using calculations to find the error value for each value using the Single Exponetial Smoothing (SES) method. The results of the study obtained a prediction of the number of fish, namely in the July 2022 period 676836.19 (Kg) with a MAPE value of 3.38%, which value was greater in May 2022 and smaller than June 2022, the Asahan District Fisheries Service must meet the number of fish. in stock of their needs

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