Bulletin of Multi-Disciplinary Science and Applied Technology

Jaringan Syaraf Tiruan Untuk Memprediksi Jumlah Kebutuhan Ekspor Kopi Pada PT.Mulya Sari Mandiri Dengan Menggunakan Metode Backpropagation

Rizki Kurniawan — 2023-08-31

Coffee is one of the most popular drinks for many people. Out of every three people, one is a coffee drinker. Coffee is really delicious if you drink it either in the morning or at night when work is piling up. PT. Mulya Sari Mandiri is a coffee factory that produces coffee, both dry coffee beans and coffee powder. The coffee obtained by this company comes from various regions such as Sumatra and Java. The coffee beans that enter from the sending area are then selected to get the best coffee. Many techniques and methods are applied in the forecasting process. In solving a problem in research, of course the researcher must have a way or a method that will be applied in solving the problem so that the research carried out can be completed properly and in accordance with the expected results. The research method is carried out to look for something systematically by using the scientific method and applicable sources. In the process of this research aimed at the PT. Mulya Sari Mandiri, especially in the area of predicting the number of coffee export needs by providing more meaningful results. The result description is an illustration of what the artificial neural network system looks like in predicting a data number of export requirements using the Backpropagation method. An overview of the results is usually made in the form of user interface design or interface design, a good design is directly proportional to the quality of the program, when the interface design is good, the quality of the program will also be good. From the results of research conducted at PT. Mulya Sari Mandiri greatly adds knowledge and insight, by collecting data related to the prediction of the amount of need for export coffee, From the input learning rate and maximum epoch, the Backpropagation method can be carried out with training or training with convergent results, namely with or target error achieved with iteration 3160 the training process (time) is 0.00.25 seconds, with a permomance value of 0.0999 for Arabica coffee and for the robusta type with iteration 4957 the training process (time) is 0.00.07 seconds, with a permomance value of 0.2. From the data on the number of export coffees used as training, training targets and test data, the Backpropagtion method can be recognized and produces predictions that the number of Arabica coffee will experience a total decrease from 2021 data of 1481 with predicted results of 1410 tons.

Identifikasi Tingkat Kepuasan Pengunjung Wisata Menggunakan Metode Naive Bayes

Fisyanda Yusmalizar — 2023-08-31

One way to implement development in all these fields is through development in the tourism sector, namely by developing and utilizing existing tourism resources and potential. To support government programs in developing tourist objects, especially in Bukit Lawang, it is necessary to pay attention to the level of satisfaction of tourist visitors visiting Bukit Lawang. To measure the level of satisfaction with tourist visitors, of course, parameters or assessment criteria will be used starting from road access to tourist attractions to cottage facilities. Measuring the level of satisfaction is usually done manually, namely by distributing or conducting surveys of visitors. If only questions are asked without any stored data, of course the Tourism Office will have difficulty measuring or evaluating the level of tourist visitor satisfaction, because it does not have sufficient data. For this reason, it is necessary to build a system that can assist the Langkat Regency Tourism Office in identifying the level of visitor satisfaction at Bukit Lawang. With this system, of course the Department will find it easier to evaluate and identify the level of visitor satisfaction quickly and precisely. So that all deficiencies to visitor satisfaction can be resolved quickly. To measure the level of satisfaction required a method that can measure the level of satisfaction precisely, one of the methods used is Naive Bayes. Naive Bayes is a simple probabilistic classifier that calculates a set of probabilities by summing the frequencies and combinations of values from a given dataset. Based on the results of trials that have been carried out in this study, results are obtained based on the 20 data used with the results of 17 TRUE data and 3 FALSE data, with an accuracy value of 65%.

Klasifikasi Tingkat Kematangan Buah Kakao Berdasarkan Warna Dengan Metode KNN (K-Nearest Neightbor)

Zidan Hafiz — 2023-08-31

Technological developments aim to help facilitate human work in life. The role of technology in human work is very large, one of which is in agriculture and plantations. Classification is a way of grouping objects based on the characteristics possessed by the object of classification. In the process, classification can be done in many ways, either manually or with the help of technology. Cocoa pods certainly have color characteristics to determine the correct level of maturity of cocoa pods. used to classify the maturity level of cocoa pods. This research method uses the scientific method to solve a problem in research, of course the researcher must have a way or a method that is applied in solving the problem so that the research carried out can be resolved properly and in accordance with the expected results. The research method was carried out to look for something systematically using scientific methods and applicable sources, especially in the classification of cocoa pod maturity level based on color using the K-Nearest Neighbor method. The interface design is an illustration of what the cocoa pod maturity classification system will be built using the K-Nearest Neighbor method. An overview of the results is usually made in the form of user interface design or interface design. The K-Nearest Neighbors method can be applied to classify the maturity level of cocoa pods based on ripe and immature colors using matlab software. 2. The results of the image data training process as many as 30 image data are inputted, the training results obtained are 100%. 3. From the feature extraction of red, green, blue, hue, saturation, value and image area of cocoa pods based on color, it can be classified the maturity level of cocoa pods based on color, whether ripe or immature.

Data Mining Korelasi Penjualan Suku Cadang Sepeda Motor Menggunakan Metode Algoritma Apriori

Asma Ul Husna — 2023-08-31

By utilizing customer data that has been stored in a database, management can find out how the current sales system is less efficient, therefore a system is needed to process information data more quickly and precisely in increasing sales of motorbike spare parts by using the Data Mining application. The Apriori Algorithm method works by searching and finding patterns of association between the products being marketed, so that later it can help the company in improving the associated items. And with sales transaction data, companies can know better how they should increase spare parts stock in the company. From the results of testing sales of motorbike spare parts with a total of 219 data, the results of the Apriori Algorithm calculations are: A3 (N-Max) has 23 items, M2 (Yamaha) has 35 items, S1 (Brake Pads) has 15 items.

Mendiagnosa Penyakit Ginjal Menggunakan Metode Certainty Factor

Ramos Parulian Ambarita — 2023-08-31

In the current era of technological advancement, rapid developments are occurring in Artificial Intelligence (AI), including the concept of Expert Systems. Expert Systems allow knowledge from experts in a field to be integrated into a computer programme to make intelligent decisions. The use of this technology, particularly in healthcare such as common kidney diseases, has great potential in diagnosis and treatment. As a vital organ, the kidney plays an important role in the body, but if it malfunctions, it can cause a number of problems. One method used to address uncertainty in expert thinking is Certainty Factor, which tests the certainty of data or facts. With AI and Expert Systems, it is hoped that healthcare services can be improved, supporting the treatment of kidney disease and other health problems.

Diagnosa Penyakit Kanker Paru-Paru Pada Perokok Aktif Menggunakan Metode Certainty Factor (CF)

Nana Elvana — 2023-08-31

Smoking habits or too often exposed to cigarette smoke are the main causes of lung cancer. Lung cancer is a primary malignant tumor of the lower respiratory system that is epithelial in nature and originates from the bronchial branching mucosa. the large number of active smokers is one of the causes of lung cancer. There are still many people who do not know about the early symptoms of lung cancer and are unsure whether it is lung cancer or other cancers. The lack of special facilities for lung cancer in Indonesia, which are still very limited, is another factor that causes the long process of treatment given to patients who may or do suffer from lung cancer. To be able to ensure a diagnosis of lung cancer or other diagnoses of diseases suffered, people with symptoms need to go to an expert or specialist in internal medicine for a consultation. However, experts who are not available, costs to consult with experts are also quite expensive and limited, which is another shortage factor. Based on the problems that occur, an expert system is needed that can store accurate information from an expert in diagnosing lung cancer in patients. The Certainty Factor method is a method that can be used in expert systems which is a combination of inference rules with a certain knowledge base given by one or more experts in a particular field. Certainty Factor uses a value to assume an expert's degree of confidence in a data. With the existence of an expert system, the public can consult without having to wait for the presence of a doctor. From the results of the trials conducted, it was found that the patient suffered from Non Small Call disease with a value of 98.53%.

Penentuan Calon Penerima Program Keluarga Harapan (PKH) Dengan Metode Analytical Hierarchy Process (AHP)

Agi Kakana Bangun — 2023-08-31

Poverty is a situation where there is a lack of ordinary things to have such as food, clothing, shelter and drinking water. Poverty sometimes also means a lack of access to education and employment that can overcome the problem of poverty and gain the respect one deserves as a citizen. Poverty itself in developing countries is quite a complicated problem even though several developing countries have succeeded in implementing development in terms of production and national income. One of the government's social assistance-based programs is the Family Hope Program (PKH). To overcome the above problems, it is necessary to build a system that can make it easier for Kuala District, Langkat Regency to make decisions about recipients of PKH assistance. To support accuracy in building a decision-making system, a method is needed that is capable of making the right decisions based on predetermined criteria. In this research, the method used is AHP. Analytic Hierarchy Process (AHP) is a structured method for managing and analyzing complex decisions using mathematical and psychological concepts. The AHP method helps in determining the priority weight of each parameter that is taken into consideration in making decisions. Based on the value of importance of criteria and sub-criteria from 10 alternative data, the highest value was obtained, namely alternative recipient 8 with a system analysis value of 0.2105 with the income criterion of the head of the family being IDR. 2,657,000, Head of family's education is high school, well water source, home toilet, boarded house building, parent's house ownership status, number of dependents 3 people, number of dependents Education of children 3 people, owns a motorbike