Articles
Data Mining Menggunakan Metode Asosiasi Apriori untuk Merekomendasi Pola Obat Pada Puskesmas
Dewinta Marthadinata Sinaga;
Agus Perdana Windarto;
Heru Satria Tambunan;
Irfan Sudahri Damanik
Journal of Information System Research (JOSH) Vol 3 No 2 (2022): Januari 2022
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)
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DOI: 10.47065/josh.v3i2.1237
Drugs are one of the most important components in terms of health, both to cure and reduce pain due to illness suffered by everyone, besides that the use of drugs also gives us information about what diseases everyone suffers so that the information is very helpful for health workers. For this reason, drugs need to be managed properly, effectively and efficiently. This study aims to analyze the a priori algorithm on drug output data at the Parsoburan Health Center Pematangsiantar to find out what types of drugs are most needed by patients at the same time. The data used is in the form of drug output data in April 2021. Based on the a priori algorithm calculations, 70 association rules were formed with a number minimum of support 90% and a minimum confidence of 90%. It is hoped that the results of the research can help the Parsoburan Health Center Pematangsiantar optimize quality health services for planning future drug needs and produce useful information for decision making.
Implementasi Market Basket Analysis Menggunakan Assocation Rule Menerapkan Algoritma FP-Growth
Desi Asima Silitonga;
Agus Perdana Windarto
Journal of Information System Research (JOSH) Vol 3 No 2 (2022): Januari 2022
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)
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DOI: 10.47065/josh.v3i2.1239
Pharmacy is a medium for selling various kinds of drugs by class and other products related to health. Pharmacies serve transactions in the form of doctor's prescriptions and over-the-counter drugs every day. Drug sales per day can reach dozens of transactions. Sales transaction data in the form of doctor's prescriptions are increasing every day and are stored as archives for bookkeeping without thinking about other benefits. However, this data can produce important information in determining the pattern of goods layout in accordance with consumer buying patterns using the fp-growth algorithm. The data used in this study is based on doctor's prescription transaction data. The results of the association rule can be used as input for the pharmacy in determining the pattern of the location of the goods at the pharmacy
Use of Binary Sigmoid Function And Linear Identity In Artificial Neural Networks For Forecasting Population Density
Anjar Wanto;
Agus Perdana Windarto;
Dedy Hartama;
Iin Parlina
IJISTECH (International Journal of Information System and Technology) Vol 1, No 1 (2017): November
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa
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DOI: 10.30645/ijistech.v1i1.6
Artificial Neural Network (ANN) is often used to solve forecasting cases. As in this study. The artificial neural network used is with backpropagation algorithm. The study focused on cases concerning overcrowding forecasting based District in Simalungun in Indonesia in 2010-2015. The data source comes from the Central Bureau of Statistics of Simalungun Regency. The population density forecasting its future will be processed using backpropagation algorithm focused on binary sigmoid function (logsig) and a linear function of identity (purelin) with 5 network architecture model used the 3-5-1, 3-10-1, 3-5 -10-1, 3-5-15-1 and 3-10-15-1. Results from 5 to architectural models using Neural Networks Backpropagation with binary sigmoid function and identity functions vary greatly, but the best is 3-5-1 models with an accuracy of 94%, MSE, and the epoch 0.0025448 6843 iterations. Thus, the use of binary sigmoid activation function (logsig) and the identity function (purelin) on Backpropagation Neural Networks for forecasting the population density is very good, as evidenced by the high accuracy results achieved.
Evacuation Planning for Disaster Management by Using The Relaxation Based Algorithm and Route Choice Model
Dedy Hartama;
Agus Perdana Windarto;
Anjar Wanto
IJISTECH (International Journal of Information System and Technology) Vol 2, No 1 (2018): November
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa
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DOI: 10.30645/ijistech.v2i1.14
Research in the field of disaster management is done by utilizing information and communication technology. Where disaster management is discussed is about evacuation planning issues. The evacuation stage is a very crucial stage in the disaster evacuation process. There have been many methods and algorithms submitted for the evacuation planning process, but no one has directly addressed evacuation planning on dynamic issues concerning time-varying and volume-dependent. This research will use the Relaxation-Based Algorithm combined with the Route Choice Model to produce evacuation models that can be applied to dynamic issues related to time-varying and volume-dependent because some types of disaster will result in damage as time and evacuation paths are volume-dependent so as to adjust to the change in the number of people evacuated. Disaster data that will be used in this research is sourced from Disaster Information Management System sourced from DesInventar. The results of this study are expected to produce an evacuation planning model that can be applied to dynamic problems that take into account the time-varying and volume-dependent aspects.
Analysis of Weight Product (WP) Algorithms in the best Go Car Driver Recommendations at PT. Maranatha Putri Bersaudara
Roni Kurniawan;
Agus Perdana Windarto;
M Fauzan;
Solikhun Solikhun;
Irfan Sudahri Damanik
IJISTECH (International Journal of Information System and Technology) Vol 3, No 1 (2019): November
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa
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DOI: 10.30645/ijistech.v3i1.28
This study aims to rank the best Go Car Driver. The problem arises because of the inaccuracy in giving value to the driver which results in the decision being given incorrectly so that the assessment tends to be subjective. This research was conducted at PT. Maranatha Putri Bersaudara. Sources of data obtained by observing, interviewing. The settlement method used is a decision support system with the Weight Producted method. The assessment criteria used are Performance (C1), Number of orders (C2), Rating (C3), Attitude (C4), Rating (C5) and Appearance (C6) where the alternatives used are 4 samples. The results obtained using the Weighted Product method are Alternative1 and Alternative4 which are recommended as the best go car driver with the assessment results of 0.0307 and 0.0272. It is expected that research results can be input to the relevant parties in recommending the best go car driver so as to minimize subjective judgment.
Penerapan Metode Data Mining C4.5 dalam Penentuan Kelayakan Rehabilitas Rumah Warga
Aulia Sugarda;
Saifullah;
Jalaluddin;
Agus Perdana Windarto;
Wendi Robiansyah
Journal of Computing and Informatics Research Vol 1 No 3 (2022): July 2022
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)
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DOI: 10.47065/comforch.v1i3.321
The purpose of the study was to find out which houses deserve to be rehabilitated in Pematang Dolok Kahean Village. The source of the data used in this research is using datasets that already exist in Pematang Dolok Kahean Village. The solution given is to classify the feasibility level of residents' houses using the C4.5 data mining method and using the Rapidminer software assistance. This method was chosen because it is one of the most widely used decision tree methods to predict a case. The results of the study stated that the system's accuracy value was 83.33% using split validation where this method produced several rules that could be used in determining the feasibility of the rehabilitation of residents' houses so that government subsidies could be channeled appropriately.
Analisis Model Backpropagation Dalam Meramalkan Tingkat Penjualan Saldo “Link Aja”
Dwi Findi Auliasari;
Gita Febrianti;
Agus Perdana Windarto;
Dedy Hartama
Journal of Computing and Informatics Research Vol 2 No 1 (2022): November 2022
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)
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DOI: 10.47065/comforch.v2i1.382
Analysis of a prediction (forecasting) is very important in a study, so that research becomes more precise and directed (Wanto and Windarto, 2017). As is the case in predicting the level of Link Aja's balance sales. This research is expected to be useful for an agency as one of the study materials in business development. A system to predict the level of sales of Link Aja balance at PT. Wahana Putra Yudha. Artificial Neural Network is a method that is able to perform a mathematical process to predict the level of sales of Link Aja Balance at PT. Wahana Putra Yudha. By using the backpropagation method, the previous data processing process is carried out which will be used as input to predict the sales level of Link Aja Balance. The data were taken from January 2021 to April 2022. January 2021 to August 2021 were used as training data, while September 2021 to April 2022 were used as test data. The training architecture model used to predict the sales level of Link Aja's Balance is: 4-2-1; 4-25-1; 4-50.1; 4-75-1; and 4-100-1. The best architecture is 4-50-1, the percentage result is 75% in each test
PkM: Pelatihan Peningkatan Skill Siswa Sekolah Kejuruan pada Pembuatan Game Sederhana berbasis Android
Agus Perdana Windarto;
M Mesran;
Anjar Wanto
Jurnal TUNAS Vol 3, No 2 (2022): Edisi April
Publisher : LPPM STIKOM Tunas Bangsa
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DOI: 10.30645/jtunas.v3i2.63
In accordance with the title of this community service program (P2M), the method of applying science and technology is in the form of android training in making simple games. Skills training activities are supported by lectures, questions and answers, and of course hands-on practice in the computer laboratory. The training module will be given to participants as a tool for practical activities in the laboratory. The purpose of implementing this community service program is to improve the skills of Pematangsiantar Exemplary Private Vocational School Students, by making simple android-based games for Pematangsiantar Exemplary Private Vocational High School Students, so as to minimize the gap between the skill levels of the Pematangsiantar Exemplary Private Vocational High School students. with the needs of the real world of work. From the evaluation results and the findings obtained during the implementation of this P2M activity, it can be concluded that this P2M program has been able to provide enormous and targeted benefits for Pematangsiantar Exemplary Private Vocational High School Students in this activity. This form of training is a very effective form of providing refreshment and additional insight and new knowledge in the field of information technology outside of the learning process received in their respective schools.
Business Strategy Training for "Yuni Phea" Sewing Business Housewives Group in South Siantar District, Pematang Siantar City
Marisi Butarbutar;
Acai Sudirman;
Agus Perdana Windarto;
Erbin Chandra;
Onita Sari Sinaga
Jurnal Pengabdian Masyarakat Vol 3 No 2 (2022): Jurnal Pengabdian Masyarakat
Publisher : Institut Teknologi dan Bisnis Asia Malang
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DOI: 10.32815/jpm.v3i2.1357
The substance of the problems faced by partners, one of which relates to aspects of human resource communication. The group of housewives who are members of the community group "YUNI PHEA" still holds on to their own egos and finds it difficult to work as an effective team, participants still prioritize individual interests (super man) and sometimes ignore the importance of working as a team (super team). In addition, the production capacity produced by the group of housewives is still limited due to production equipment such as sewing machines which are still inadequate in terms of quantity and quality and members still use the machines owned by their fellow members and are old enough to cause limitations in terms of production and market. share that has not been clearly identified and promotional efforts that have not been optimal. Indicators of the success of this service activity include increased production capacity by 90%, production results are neater and have quality variations, increased partner turnover of at least 90%, and increased business competitiveness of at least 90%.
Akurasi Algoritma Fletcher-Reeves untuk Prediksi Ekspor Karet Remah Berdasarkan Negara Tujuan Utama
Rapianto Sinaga;
Mora Malemta Sitomorang;
Deri Setiawan;
Anjar Wanto;
Agus Perdana Windarto
Journal of Informatics Management and Information Technology Vol. 2 No. 3 (2022): July 2022
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)
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DOI: 10.47065/jimat.v2i3.170
Crumb rubber is a natural rubber specially designed to ensure its technical quality. Rubber is produced mainly in Southeast Asia, where Indonesia is the second largest producer in the world after Thailand. This study aims to predict the export of powdered rubber in Indonesia. The prediction method used is FletcherReeves which is one of the artificial neural network methods commonly used to predict data. The research data used is crumb rubber export data by main destination country for the period 2012-2020 which was obtained from the website of the Indonesian Central Statistics Agency. Based on this data, network architecture models will be trained and defined, including 7-10-1, 7-15-1, 7-20-1, 7-25-1, 7-30-1 (trancgf). Of the five models, after training and testing, the best data architecture model is 7-15-1 (trancegf) 7 is the input layer, 15 is the number of neurons in the hidden layer and 1 is the exit layer. The level of accuracy of the architectural model with the MSE value is 0.00482054.