bluuebunny/crossref_metadata_2025 huggingface dataset:
Penerapan Supply Chain Management (SCM) Dalam Pemantauan Stok Barang Berbasis Web
Authors: Nasution Sri Wahyuni , Manurung Nuriadi , Rahayu Elly
Published: January 2023

Umi Nala Shop store is engaged in selling toys, such as floats, laptop screens, construction sets, ambulance cars, small cars, jeep cars, and many more. The problem is that this store does not know the amount of inventory of goods in the warehouse. This store purchases goods from suppliers for the inventory of goods to be sold without knowing the available stock. This makes the inventory of goods to be sold by the store uncontrollable. The store records incoming and outgoing goods and transactions manually using paper so that data can be lost. The Umi Nala Shop has more than 200 resellers but is inactive and has ten suppliers to supply the goods sold. The sale of goods at the Umi Nala Shop is still offline, where customers come directly to the Umi Nala Shop. Marketing is carried out through social media networks such as Facebook, WhatsApp, and Instagram. In carrying out its business, it is necessary to pay attention to inventory management to provide for consumer needs and control inventory when there is a high demand for goods. For the store to compete, it is necessary to implement Supply Chain Management (SCM) to integrate suppliers, warehouse manufacturing, and storage so that goods are distributed in the correct quantity at the right time, to minimize costs and provide satisfaction to consumers. The purpose of this study is to build an SCM application that can make it easier for stores to find out the amount of inventory to ensure the availability of goods. The results of this study with the implementation of Supply Chain Management at the Umi Nala Shop store can help and make it easier for store owners to manage the supply chain of goods.
Penerapan dan Implementasi Metode Certainty Factor Dalam Sistem Pakar Diagnosa Awal Gangguan Menstruasi PALM-COEIN
Authors: Azzahra Putri , Haerani Elin
Published: January 2023

Menstrual disorders are changes that occur in the cycle, the amount of blood, and other changes related to the menstrual cycle. Menstrual disorders are often considered a common problem that can affect daily activities. Menstrual disorders that are ignored on an ongoing basis can cause various reproductive system disorders and are also an early sign of dangerous diseases. Many women ignore the menstrual disorders they experience because they are constrained in consulting a doctor both in terms of time, distance, and cost. To help overcome these obstacles, an expert system can be a solution. This expert system is made using the certainty factor method which consists of 43 symptoms with 7 types of disease. This system produces output in the form of a percentage of the type of possible disease experienced by the user and suggestions based on the symptoms selected by the user. The expert system built is expected to be a medium of information about menstrual disorders and can contribute to providing benefits to the community, especially women, to make an initial diagnosis of menstrual disorders experienced without being constrained in terms of time, distance, or cost
Recommender System Movie Netflix using Collaborative Filtering with Weighted Slope One Algorithm in Twitter
Authors: Rifaldy Rakhmat , Setiawan Erwin Budi
Published: January 2023

Movies are entertainment that many people enjoy filling their spare time. After watching a movie, people usually write reviews about the movie on social media such as Twitter. As the number of movies grows, a recommendation system is created, which is useful for finding movies they might like based on the movies they have seen. This study developed a movie recommendation system using Collaborative Filtering (CF) with the Weighted Slope One (WSO) algorithm. The dataset used is taken from tweet data on Twitter. Then the tweet dataset is converted into a rating value which will later be used in the recommendation system. This study uses Mean Absolute Error (MAE) to measure accuracy. In Collaborative Filtering, the system gets the best MAE of 0.924. Then for Weighted Slope One, the system gets the best MAE of 0.568.
Sentiment Analysis on Twitter Against IndiHome Providers Using Chi-Square and Ensemble Bagging Methods
Authors: Aini Anisa Nur , Jondri Jondri , Astuti Widi
Published: January 2023

During the Covid-19 pandemic, internet usage has increased rapidly. Now the internet is used as a means in the online teaching and learning process and work from home. One of the internet service providers is IndiHome. IndiHome is an internet service provider company that has a huge number of users. A large number of IndiHome users causes frequent problems, and this is one of the factors that IndiHome users provide various kinds of opinions or responses. Sentiment analysis is used to see the opinion or opinion given by someone on a particular object or problem. This study conducted a sentiment analysis using the Chi-square and the Ensemble Bagging method with three base classifier methods, namely K-Nearest Neighbor (K-NN), Support Vector Machine (SVM), and Naive Bayes (NB). Prediction results on labels obtained from each base classifier are combined using a hard majority vote. Tweet data collection was carried out in March 2022, and 6,962 tweets were collected. This study conducted two test scenarios. Scenario 1 is a scenario without oversampling with test results showing that Ensemble Bagging has the highest accuracy value of 83.32%, and in scenario 1 with hyperparameter tuning, Ensemble Bagging has the highest accuracy value of 83.93%. Scenario 2 is a scenario with oversampling, showing that Ensemble Bagging has the highest accuracy value of 84.51%, and scenario 2 with hyperparameter tuning also shows Ensemble Bagging has the highest accuracy value of 84.56%.
Performance Analysis of Bandung City Traffic Flow Classification with Machine Learning and Kriging Interpolation
Authors: Ramdani Nuraena , Prasetyowati Sri Suryani , Sibaroni Yuliant
Published: January 2023

This research focuses on making classification maps using the Classification And Regression Trees (CART), Random Forest and Ordinary Kriging methods. The dataset used is data from the Area Traffic Control System (ATCS) of the Bandung City Transportation Agency and the Google Maps application in April 2022. After the dataset is obtained, then the data pre-processing process will be carried out then the CART and Random Forest classification learning models will be made, after the CART and Random Forest classification learning is complete. From the CART and Random Forest classification models, traffic congestion classification map will then be made using the ArcMap application with the Ordinary Kriging interpolation method. The results of the comparison of classification maps made with Ordinary Kriging interpolation with the Gaussian Model semivariogram in both methods, namely CART and Random Forest. With the CART method has an accuracy of up to 88% while the classification map made with the Random Forest method has an accuracy of up to 90%. This proves that in this study the Random Forest method is far superior in building classification maps compared to the CART method
Analysis of Community Sentiment on Twitter towards COVID-19 Vaccine Booster Using Ensemble Bagging Methods
Authors: Maden Artamira Rizqy Amartya , Jondri Jondri , Astuti Widi
Published: January 2023

COVID-19 is an infectious disease caused by a newly discovered type of coronavirus. Based on recommendations from the Technical Advisory Group on Virus Evolution, WHO established a new variant called Omicron. Due to the rapid spread of COVID-19, a booster vaccine was created to deal with the new virus variant. However, the strategy of giving vaccines that never ends is considered controversial by the community, and this is shown by the number of people who express their opinions, both positive and negative opinions on social media, one of which is Twitter. This research was conducted by collecting data with the help of the Twitter API. The classification method uses ensemble bagging with three basic lessons, namely Naive Bayes, K-Nearest Neighbor, and Decision Tree. Meanwhile, the feature extraction used in this research is TF-IDF (Term Frequency-Inverse Document Frequency). The performance of the ensemble bagging method by applying Hyperparameter Tuning is a precision of 0.72, recall of 0.71, F1-Score of 0.72, and accuracy of 0.72.
Penerapan Metode Hybrid Case Base Pada Sistem Pakar Diagnosa Penyakit Jantung
Authors: Handayani Ayu , Hutahaean Jeperson , Nasution Akmal
Published: January 2023

Many people have died of sudden heart attacks. The role of a specialist doctor is very necessary to overcome this, but the role of the doctor is also bumped due to limitations in terms of numbers and hours worked. In addition, in general, people with heart disease often ignore and do not understand the causes and symptoms of heart disease. Most patients are reluctant to have their heart health checked because they are constrained by expensive medical expenses, as well as a lack of service to patients. In the process of consulting for heart disease, the patient must come to the hospital and do an examination in person which of course must go through a series of procedures starting from registration onwards to get results. To overcome this problem, an expert system application is needed for the early diagnosis of heart disease. The purpose of this study was to build a web-based system of heart disease diagnosis expert applications. This expert system application uses the Hybrid Case Base method which is a combination of the Rule-Based Reasoning (RBR) and Case-Based Reasoning (CBR) systems. The RBR system and the CBR system have their advantages and disadvantages. The analysis and design of the systems used are UML and Entity Relationship Diagrams. In this expert system application, patients will consult by answering several questions about the symptoms of heart disease displayed by the system by checking the symptoms they experience. Then the system will provide diagnostic results based on the symptoms experienced by the patient. The results of this study can diagnose the type of heart disease experienced by patients and their treatment solutions and what percentage of the patient is likely to suffer from the disease quickly
Seleksi Fitur Menggunakan Eigen Vector Untuk Peningkatan Kinerja K-Means Clustering Dalam Pengelompokan Data
Authors: Syahputra Nugroho , Zarlis Muhammad , Efendi Syahril
Published: January 2023

The large number of data set attributes from the data grouping process with K-Means Clustering can affect the number of iterations produced. In this research, Eigen Vector is used to perform feature selection on the data set. The selected data set is then clustered using K-Means Clustering. The data set used in this research is the Wine Quality Dataset obtained from the UCI Machine Learning Repository, with 11 attributes, 4898 data records and 7 attribute classes. Then the South German Credit Dataset was obtained from kaggle.com with 20 attributes, 1000 data records and 2 attribute classes. The results of this research indicate that the number of iterations obtained from the comparison of tests using K-Means without feature selection is that in the Wine Quality Dataset, 11 iterations are obtained, and in the South German Credit Dataset, there are 10 iterations. Meanwhile, K-Means with Eigen Vector feature selection obtained the number of iterations in the Wine Quality Dataset with a total of 5 iterations, and in the South German Credit Dataset with a total of 4 iterations. Clustering evaluation was calculated using Sum of Square Error (SSE). The SSE value in K-Means Clustering without feature selection from the Wine Quality Dataset is 678.5735, while in the South German Credit Dataset it is 1534.3167. While the K-Means Clustering with Eigen Vector from the Wine Quality Dataset is 383.0517, and the South German Credit Dataset is 469.0698. From the results of the proposed method is able to reduce the percentage of errors and minimize the number of iterations on K-Means Clustering with feature selection using Eigen Vector
The Box for Early Detection of Gas Leaks and Fires uses Notification System to The Fire Department
Authors: Saparuddin Saparuddin , Amin Muhammad , Sudarmin Sudarmin
Published: January 2023

Fire is one of the tragedies that cannot be predicted, besides being unwanted by the community, fires are also often uncontrolled when the fire has started to grow. Fire incidents are very dangerous and disrupt people's lives. Many types of fire detection devices have developed recently to minimize the occurrence of material losses and fatalities that provide a sense of security for the users of these detectors, but there are still some things that need to be added to this detector in order to reduce the number of material losses and victims. soul, the researcher wants to design a tool with a working system when the fire sensor detects the fire value and the gas sensor detects the gas value, the sensor sends data to the NodeMCU. Furthermore, NodeMCU will send a message in the form of a notification in the form of the complete address of the owner of the house where the fire occurred as input into the program sketch. A notification is sent to the Tanjungbalai City Fire Department operator and the buzzer will turn on and the LED will light up
Penerapan Metode Certainty Factor Dalam Mendiagnosa Penyakit Kehamilan Berbasis Web
Authors: Purnawan Dania , Hutagalung Jhonson Efendi , Azmi Sri Rezki Maulina
Published: January 2023

Diseases or disorders in pregnancy can cause death, especially for pregnant women and babies. This will also affect the infant mortality rate. Diseases that attack a woman's womb cannot be considered trivial and require the intervention of an expert, while an expert for this disease is still rare and certainly requires no small cost. In creating experts (human experts), it takes a relatively long time and costs are not small. One alternative effort to overcome this need is to create a web-based intelligent system. In this study, an expert system will be developed that can be used as a means to carry out early diagnosis of pregnancy diseases. The application of the system is equipped with a certainty factor calculation method that aims to show the level of confidence in the diagnostic results. From the symptoms experienced there is a 20% certainty level and for toxoplasma there are 80% that the patient has gestational anemia.
Comparison of Weighted Moving Average Method with Double Exponential Smoothing in Estimating Production of Oil Palm Fruit
Authors: Anggraini Putri , Amin Muhammad , Marpaung Nasrun
Published: January 2023

Oil palm is one of the largest agricultural products in Indonesia and has high economic value and can improve the welfare of oil palm farmers. The research was conducted at PT. Agro Putra Lestari regarding palm oil production, having its address at Jln.Imam Bonjol No.179 Kisaran with the name of the leader being Mr. Anda Puta Lubis, SE, M, Ma. PT. Agro Putra Lestari is a company that produces palm fruit products which is still running. PT. Agro Putra Lestari spread across the Asahan area, including Meranti, Simondol 1, Simondol 2, Simondol 3, Lahan Camat, Sitampu Saring, Marpaung, Miri-Miri, Solo Baru, and Lahan Kembar. The problem that often occurs is the amount of oil palm fruit production which is fluctuating so that the company does not know the estimated production of oil palm fruit in the following month. PT. Agro Putra Lestari has difficulty in knowing the results of oil palm fruit production in the following month because of improper planning to predict the production and have not applied the comparison of the weighted moving average and double exponential smoothing methods in predicting the amount of oil palm fruit production at PT. Agro Putra Lestari. The data used is from June 2021 to May  2022. The results of the forecasting of the two methods are compared to find out which forecasting results have the smallest error value, where the smallest error value can be used as a reference for future oil palm fruit production.
Implementasi Sistem Pendukung Keputusan Penilaian Soft Skill Guru Berbasis Web Menggunakan Metode Weight Product
Authors: Pratama Rizky , Dalimunthe Ruri Ashari , Saputra Endra
Published: January 2023

MTs Nurul Iman Simpang Empat is a private school institution located in Asahan Regency which has 32 madrasa teachers. This madrasa has quite complete facilities and is supported by technology facilities and a fairly complete information system. MTs Nurul Iman Simpang Empat is also included in the pilot MTs for other schools, because MTs Nurul Iman Simpang Empat has many achievements in various fields. Every year, the Principal holds a Teacher Soft Skill Assessment to improve the quality of education in Madrasahs. This study aims to determine the soft skill system for teachers in the school so that the performance of each teacher is obtained. Obstacles from Teacher Performance Assessment at MTs Nurul Iman Simpang Empat are still subjective in assessment based on assessment because there is no system of assessment used in Teacher Soft Skill Assessment. In the decision support system there are several methods that can be used in solving a problem. The research method used is a qualitative method with data collection techniques using interviews and literature studies. The program design method uses a weight product with the PHP programming language and MySQL as the database
Mesin Pendeteksi Uang Palsu Dengan Sensor LDR Berbasis Kecerdasan Buatan
Authors: Maharani Sri , Hutagalung Jhonson Efendi , Syahputra Abdul Karim
Published: January 2023

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 Mendiagnosa Penyakit Lupus dengan Metode Forward Chaining Menggunakan Web
Authors: Bugis Indah Wahyuni , Hutagalung Jhonson Efendi , Harahap Indra Ramadona
Published: January 2023

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)
Penerapan Metode Multi Objective Optimization on the Basis of Ratio Analysis (MOORA) Dalam Pemilihan Mekanik Terbaik Sepeda Motor
Authors: Sinaga Ahmad Sofian , Helmiah Fauriatun , Latiffani Chitra
Published: January 2023

A mechanic is a person in charge of checking, maintaining, repairing, replacing spare parts according to the analysis of the Service Advisor (the person who serves and receives every customer or customer complaint) listed in the workshop work order, with reference to the standardization of work that has been set and most mechanics specialize in in certain areas such as auto mechanics, bicycle mechanics, motorcycle mechanics, boiler mechanics, general mechanics, air conditioning and freezing, aircraft mechanics, diesel engine mechanics. One of the existing methods in a decision support system is the MOORA (Multi-Objective Optimization On The Basis Of Ratio Analysis) method. The reason the author chose the MOORA method is because this method is very simple, stable, and powerful, even this method does not require an expert in mathematics to use it and requires simple mathematical calculations. In previous research, it is known that there is no selection of the best mechanic at company. With the use criteria used are troubleshooting (analyzing problems and repairing vehicles), years of service, attendance and letters of reprimand. With these criteria, it is expected to produce the best motorcycle mechanic decisions
Komparasi Algoritma Klasifikasi Data Mining Menggunakan Optimize Selection untuk Peminatan Program Studi
Authors: Anam Khaerul , Nurhakim Bani , Juliane Christina
Published: January 2023

The selection of a study program is a unique opportunity for a student. STMIK IKMI Cirebon is now a KIP Kuliah provider, offering three study program. The research problem is the unavailability of a model of student interest in the study program, so it is necessary to carry out an interest in the study program by applying an algorithm to the classification model. The algorithm used as a comparison is the Decision Tree algorithm (C4.5), Naive Bayes, k-Nearest Neighbor and Support Vector Machine. The classification model applies the Optimize Selection operator by looking for the dominant attribute in its influence on the specialization of the student study program. Finally, the comparison model will be tested by parametric t-test in order to test the significance of the algorithm. The results of the algorithm accuracy test obtained that the SVM algorithm has the best accuracy with a value of 80.76%. While the algorithm with the lowest accuracy is Naive Bayes with a value of 74.64%. While the other two algorithms have a sequential accuracy rate of 80.47% for Decision Tree and 76.09% for k-NN. The results of this study are used to classify study preference for students in STMIK IKMI Cirebon which is useful for predicting study interest based on the background of students
Clustering Hasil Belajar Menggunakan Algoritma K-Means Dengan Optimize Parameter Dalam Menjamin Mutu Pendidikan Di Era Pandemi Covid-19
Authors: Rifai Ahmad , Dikananda Fatihanursari , Juliane Christina
Published: January 2023

The COVID-19 pandemic has greatly affected the learning environment, with the excuse of stopping the spread of COVID-19 infection. Teaching and learning activities that have generally been completed on campus face-to-face now have to be transferred to distance learning. However, one of the drawbacks of implementing distance learning is that it makes students less active, so that KBM feels tiring. The purpose of this study is to classify student learning outcomes during the COVID-19 Pandemic. The method used is the Knowledge Discovery Database (KDD) using the K-Means Algorithm. The number of clusters selected is the number of clusters with the smallest Davies Bouldin Index (DBI). The results of this study obtained 3 clusters with a DBI value of 1.379 and a centroid distance of 0.342. Cluster_1 is the data group with the highest quality index, Cluster_2 is the data group with the second highest quality index, and Cluster_0 is the data group with the lowest quality index of all clusters. By knowing the clusters of PJJ learning outcomes, it will make it easier for universities to take improvement steps to improve the quality of learning in accordance with the characteristics of each existing cluster
Sistem Pakar Untuk Mendiagnosa Sindroma Permentruasi (PMS) Dengan Metode Dempster Shafer Berbasis Web
Authors: Rini Nur Adha , Yesputra Roly , Sudarmin Sudarmin
Published: January 2023

Sindroma Permenstruasi merupakan peyakit haid yang terjadi pada wanita dengan tingkat yang berbeda untuk itu perlu diketahui tipe penyakit tersebut dengan melakukan diagnosa guna mudah dalam mengatasi penyakit tersebut. Kemajuan sistem pakar dapat mengatasi permasalahan ini yaitu dengan merancang sebuah sistem komputer berbasis web yang terintegrasi dengan database dan bahasa pemrograman seperti PHP-MySQL sehingga dapat membantu penderita Sindroma Permenstruasi untuk mendiagnosa gejala-gejala dan tipe penyakit tersebut. Tujuan dari penelitian ini adalah untuk membangun sebuah sistem pakar untuk mendiagnosa penyakit Sindroma Permenstruasi berbasis web. Aplikasi sistem pakar dalam pengambilan keputusan ini menggunakan metode Dempher Shaper dengan membangkitkan nilai true dan false pada basis pengetahuan baru dan lama dan membandingkan dengan nilai bobot pada masing-masing frame sehingga didapatkan persentasi dari tipe penyakit tersebut.  Hasil dari implementasi sistem yaitu sistem memberikan pertanyaan berupa gejala-gejala yang harus dijawab oleh pasien berdasarkan gejala yang dialami oleh pasien dan hasil dari proses tersebut sistem akan  memberikan informasi tipe penyakit Sindroma Permenstruasi jenis apa yang dialaminya guna mendapatkan solusi
Analisis Kinerja Algoritma Machine Learning Untuk Klasifikasi Emosi
Authors: Sudianto Sudianto
Published: January 2023

Social media is a place to express or share daily activities. Various new events are often discussed on social media, such as on Twitter. Frequently, the conversations conducted by Twitter users when giving a review or opinion have various emotions, such as anger, sadness, fear, or joy. Emotions are difficult to describe the challenges that occur, sometimes leading to multiple interpretations and misunderstandings leading to debates and reporting to the authorities. So this shows that emotions in reviews and opinions are essential for classification because emotions that come from texts are difficult to understand. In addition, the classification of emotions needs to be done to speed up the identification of emotions. The purpose of this study is to find out which algorithm has optimal performance in the classification of emotions. Machine Learning methods are the Naïve Bayes algorithm, Random Forest, and Support Vector Machines; this is done to determine the dominant algorithm in classifying emotions. The results of the modeling and classification using the Random Forest algorithm obtained a dominant accuracy with an accuracy value of 81.3%, followed by the SVM algorithm with an accuracy value of 76.6% and an accuracy value of 79.1% Naïve Bayes algorithm. In addition, from the speed of time in completing the classification, the Random Forest algorithm has the fastest time of 1.27 seconds
Penerapan Algoritma Apriori Data Mining Untuk Menentukan Penyusunan Layout Barang Pada Toko Ritel
Authors: Triayudi Agung
Published: January 2023

Retail is an activity that includes the sale and purchase of goods. For retail stores, the continuity of the business processes that are carried out is very dependent on the sale of goods or the purchase of goods from consumers. Retail stores today must have a strategy or a way to increase sales of their goods. One strategy that can be applied in increasing sales is the preparation of the layout of goods. Errors in the preparation of the layout of goods are of course very detrimental to retail stores, these errors can lead to a stagnant sales process or also decreased sales. The arrangement of the layout of goods can be done by looking at the characteristics of the goods purchased by consumers or commonly referred to as goods associations. Data mining is a technique that can be used to process data. In data mining itself there are many ways that are used to solve problems, one of the ways used to solve problems in data mining is the a priori algorithm. The combination of items obtained by consumers buying item A will also buy Item B with a support value of 20% and a confidence value of 50%. Another combination of items is that consumers buying item A also buys item D with a support value of 10% and a confidence value of 25%. The last combination of item sets, namely Consumers buying item B will also buy item D with a support value of 20% and a confidence value of 50%
Implementasi Algoritma Zhu-Takaoka Untuk Pencarian Nama Obat Pada Aplikasi Katalog Obat Berbasis Android
Authors: Sony Sony
Published: January 2023

Medicine is an object that is currently needed by humans, there are many names of drugs with different benefits, making it difficult for many people to find information on the name of the drug and the benefits of the drug. Technology is needed to make it easier for someone to find information on drug names and the benefits of the drug, therefore the author will build an android-based drug catalog application. With this android-based drug catalog application users can easily search for drug names by entering the name of the drug to be searched in the search table, after which the name of the drug with the benefits of the drug will appear.
Penerapan Association Rule Menggunakan Frequent Pattern Growth Untuk Rekomendasi Produk Jersey Sepakbola
Authors: Musaddad Anwar , Nurdiawan Odi , Dwilestari Gifthera
Published: January 2023

The phenomenon of the beginning of the year, what some football fans have been waiting for, is the publication of the latest jersey from their favorite team. When the new jersey was launched, football fans flocked to buy the jersey, but there were several shops available for the new jersey. This was experienced by the Eighteen Sport shop, in fulfilling the wishes of fans, there were obstacles to re-stock the jerseys that were most in demand. So many items that have not been sold. The focus of this research lies in managing jersey sales data in June, July and August, as well as high interest in the demand for club jerseys. The high demand for jerseys is influenced by the achievements of the club itself. This study uses the FP Growth algorithm with the aim of getting a recommendation pattern from the wishes of football fans. Based on the results of the support management, it was found that consumers by buying 1 jersey item will buy back 1 different jersey item as many as 15 patterns. Consumers by buying 2 jersey items will repurchase 1 different jersey item as many as 46 patterns. Consumers by buying 3 jersey items will repurchase 1 different jersey item as many as 37 patterns. Consumers by buying 4 jersey items will repurchase 1 different jersey item for 10 patterns. So that the pol data becomes the owner's recommendation to make a repeat purchase.
Prediksi Jumlah Kunjungan Pasien Menggunakan Simulasi Monte Carlo
Authors: Rafiska Rian
Published: January 2023

Klinik adalah jenis fasilitas pelayanan kesehatan yang menyediakan pelayanan rawat jalan, rawat inap, dan gawat darurat kepada masyarakat. Klinik Utama Khusus Mata (KUKM)-Kita merupakan fasilitas kesehatan milik swasta yang memberikan pelayanan kesehatan khususnya dengan keluhan mata bagi masyarakat Kota Sungai Penuh dan Kabupaten Kerinci. Karena jumlah pasien yang datang setiap harinya tidak bisa diketahui, hal ini mengakibatkan pihak manajemen KUKM-Kita tidak bisa menyiapkan sumber daya yang optimal dalam memberikan pelayanan kepada masyarakat. Untuk mengatasi masalah ini, maka perlu dilakukan simulasi untuk memprediksi jumlah pasien yang akan berkunjung di masa yang akan datang. Metode yang digunakan dalam penelitian ini ialah metode simulasi Monte Carlo. Penelitian ini bertujuan untuk memberikan informasi yang dibutuhkan pihak KUKM-Kita dalam memprediksi jumlah kunjungan pasien kedepannya. Dalam penelitian ini data yang diolah ialah data jumlah kunjungan pasien pada tahun 2019 sampai 2021 di KUKM-Kita. Hasil dari penelitian ini adalah prediksi jumlah kunjungan pasien yang setiap tahunnya mengalami peningkatan. Dengan hasil ini pihak KUKM-Kita bisa munggunakan informasi yang didapatkan untuk menjadi rujukan dalam membuat keputusan dan kebijakan untuk memperbaiki pelayanan kedepannya.
Penerapan ML dengan Teknik Bayesian Regulation untuk Peramalan Usia Penduduk di Beberapa Negara Asia
Authors: Puspadini Ratih , Wanto Anjar , Arminarahmah Nur
Published: January 2023

Knowing the age of life of the population in a country is useful for evaluating the performance of the government, whether the government is able to prosper the population in general, and improve health status in particular. The purpose of this paper is to forecast the age of the population in several major countries in Asia, so that the government has a benchmark in determining policies to further improve the welfare and health of the population in their respective countries. The forecasting method in this paper will use Machine learning algorithms with Bayesian Regulation techniques. The research data used is data on population expectations in several Asian countries sourced from the United Nations: "World Population Prospect: The 2010 Revision Population Database". This research is a development of research that has been done before, using the Cyclical order technique. Previous research used 5 architectural models (3-5-1, 3-8-1, 3-10-1, 3-5-8-1 and 3-5-10-1), with the best model being 3-5-10 -1 which results in an accuracy of 97%, MSE 0.0008358919, training time of 27 seconds and an error rate of 0.03. Meanwhile, this research only uses 3 modified architectural models (2-5-1, 2-10-1 and 2-5-10-1), with the best model being 2-5-1. The result is that this study is better than previous studies. The benchmark is seen from a smaller error rate (0.02), better accuracy (100%), to a faster training time (5 seconds). So it can be concluded, Bayesian Regulation technique works better than Cyclical order and the 2-5-1 architectural model will be used to make predictions
Penerapan Algoritma Naïve Bayes Untuk Diagnosa Hama Pada Tanaman Aglaonema SP dan Monstera Adansonii
Authors: Widiantoro M Riandi , Robo Salahudin , Almukarrama Almukarrama
Published: January 2023

Aglaonema sp and Monstera Adansonii are the most popular ornamental plants during the COVID-19 pandemic. Aglaonema sp and Monstera Adansonii become the target of the keepers because the colors and patterns on the leaves are unique. Despite the high popularity of Aglaonema sp and Monstera adansonii, not many keepers know the problems faced by their plants. The least number of triggers is knowledge of the keepers in caring for their plants. Therefore, to help the community in maintaining Aglaonema sp and Monstera Adansonii plants, an expert or expert in the field of ornamental plants is takes. Due to the difficulty of finding an expert, a system that is able to keep knowledge from an expert is required. An expert system is part of an intelligence that uses a person's knowledge that is summarized and processed carefully to solve problems. One of the statistical data calculation methods is Naïve Bayes. The Naïve Bayes method is a computational technique for predicting probabilities by calculating how many possible sets by adding up the frequency and combined values ​​of the dataset. The software created is able to share understanding with the community about Aglaonema sp and monstera adansonii plants and what treatment should be given to their ornamental plants
Klasifikasi Citra Jenis Kapasitor Menggunakan Kombinasi Algoritma K-Nearest Neighbor dan Principal Component Analysis
Authors: Nuraini Rini
Published: January 2023

To learn about electronic devices, one must know about the types of electronic components. Capacitors are one of several important electronic components. Capacitors are part of passive components that are able to store energy or electric charge at a temporary time. Capacitors or commonly called capacitors have many types. However, some people do not know about these types of capacitors. Especially for someone or a student who will learn about electronic components. The purpose of this study is to develop a digital image processing system for the classification of transistor types by applying the K-Nearest Neighbor (KNN) and Principal Component Analysis (PCA) methods. PCA serves to reduce and retain most of the relevant information from the original features according to the optimal criteria. Based on the results of feature extraction and data reduction performed by PCA, it is easier for the KNN algorithm to classify. KNN performs a classification based on the data closest to the object being processed. Based on the test results, the developed model is able to produce an average accuracy value of 82.50%. This means that PCA and KNN algorithms can be used in the process of classifying capacitor type images properly
The Penerapan Zeigarnik Effect Sebagi Motivasi Pengerjaan Tugas Akhir Pada Sistem Informasi Tugas Akhir Mahasiswa
Authors: Pratiwi Clarina Juliatuty , Heroza Rahmat Izwan
Published: January 2023

The final project is a scientific work based on independent research by students to measure students' abilities by applying the lessons they have learned. In the process, sometimes there are obstacles in the administrative and guidance processes that make students uncomfortable and unmotivated and delay doing their final assignments, especially during the current pandemic which is difficult to be in the outside environment. By utilizing existing technology, an information system design was made that implements a user experience design, namely the Zeigarnik Effect as a stimulation for students to be more motivated in working on the final project. To determine the effect of the application of the Zeigarnik Effect on the design of the Final Project Information System for Students of the Faculty of Computer Science, Sriwijaya University, a Design Thinking approach was used in finding solutions to problems encountered and measuring the System Usability Scale (SUS) and User Experience Questionnaire (EUQ) to determine the level of usability and the evaluation value of the UX factor in the design of the information system is one of the motivational variables in the stimulation factor. So as to produce an information system design that has usability values ​​that are easy to use and meet user satisfaction and motivate users in working on the final project.
Penerapan Algoritma FP-Growth dalam Penentuan Promosi Kampus
Authors: Zulkarnain Iskandar , Valentine Hany Maria
Published: January 2023

Campus or college is an institution as well as an institution that is included in the education sector. Now the campus is included in a business sector that is engaged in education. Therefore, the campus is also inseparable from the promotion process. The promotion carried out by the campus has the aim of making prospective new students register on the campus. For private campuses, students are input that can be useful to continue the operational process for the campus. The problem that is still widely found at this time is the process of determining campus promotions is still based on assumptions. Where the assumptions used are not based on a fact or special reference. Determination of promotion on campus can be seen based on the data of students who have registered actively on the campus. From the student data, it can be processed based on Regional Origin, School Origin, Department and Study Program taken. Data mining is a technique used to process large amounts of data. Frequent Pattern Growth Algorithm (FP-Growth) is an algorithm that is included in the data mining association technique. The results obtained in the study that for determining the promotion strategy are if you take the Study Program = Informatics Engineering (PS1) then the Department = Science (J1) and Regional Origin = Deli Serdang (AD1) with a Support value = 30% and a Confidence value = 60% and Department = Science (J1), Regional Origin = Deli Serdang (AD1) with Support = 30% and Confidence = 75%. Based on the results of the process that was carried out, it was found that the promotion target was Deli Serdang, the Department was Science and the Study Program of interest was Informatics Engineering.
Kebakaran Hutan Implementasi Metode CLARA Clustering Untuk Pengelompokan Data Potensi Kebakaran Hutan/Lahan Berdasarkan Persebaran Titik Panas (Hotspot)
Authors: Lidrawati Enni , Bahri Saiful , Zubaedi Umam Faqih , Carolina Vinnesa Patricia , Kusrini Kusrini , Maulina Dina
Published: January 2023

Forest or land fires are events that often occur in various countries in the world that require serious handling from all parties because they have an impact on all lines of life. Therefore, early treatment is needed, one of which is by grouping fire-prone areas using hotspot data. Hotspots can be obtained by satellite in this study taking hotspots from NASA satellites. The data used are latitude, longitude, brightness and confidence. The method used is the Clara Clustering method because this method has the advantage of being resistant to outliers and can be used in large amounts of data. This study concludes that the Clara method can process 16,579 hotspot data with the best Shilhoutte Coefficient value of 0.89 with 2 clusters while the potential possessed by cluster 1 is included in high potential with an average brightness of 3670K and a confidence value of 1 or hight. Meanwhile, cluster 2 has moderate potential with an average brightness of 3490K and a confidence value of 3 or nominal.
Sentiment Analysis of Indonesian Economics News Summary on The ICI using Long Short Term Memory
Authors: Muhith Muhammad Raihan , Atastina Imelda
Published: January 2023

Many investors use news summary as a reference while deciding whether to purchase, sell, or hold shares as part of their investment activity. The information provided by the news, on the other hand, frequently fails to meet expectations. Therefore, this study aims to classify economic news summary using sentiment analysis method followed by analyzing the results to determine the correlation between Indonesian economic news summaries and Indonesia Composite Index (ICI) trends. The dataset for this study is a collection of news articles from the Kontan online news site. This study begins with the collection of a dataset that includes 1720 training data and 440 test data that have been automatically summarized using the cosine similarity approach and labeled (positive/negative) based on the ICI trend the next day after the data was crawled. We use Term Frequency – Inverse Document Frequency (TF-IDF) as the word weighting technique and Long Short Term Memory (LSTM) method as the classifier to build the model. From the model training process that has been carried out for eight trials by tuning hyperparameters, the training accuracy is 86% and the F1-Score is 89.3%. While the testing accuracy and F1-score are 68.1% and 75.8% consecutively
Sistem Pemantauan Debu Secara Real-Time Pada Daerah Pertambangan Batu Bara
Authors: Iswan Iswan , Mulyadi Mulyadi
Published: January 2023

Bunyu Island is one of the districts in Bulungan Regency and has abundant natural resources, thus making it much ogled by large mining companies to extract and process these natural resources. However, it may change the air quality around the mining area to be poor. This research developed a device that had an electronic sensor as an input device, a NodeMCU ESP8266 microcontroller as a process device, and Blynk Application viewer as an output device. This research was carried out in two stages of testing, namely the GP2Y1010AU0F sensor and the Blynk Application software. In sensor testing, it was done by testing the tool error and continuing to test the voltage using 3 samples in the form of smoke, paper ash, and dust to test the voltage against dust density. In the error test, the result were nit too large, namely 1.43% and 1.67% of the error value, and in the stress test, different results were obtained in the sample test according to the density of each sample. While at the stage of testing the Blynk Application software, it was carried out indoors and outdoors. In software testing good results were obtained where the Blynk application displayed a notification when the read dust was above the threshold.
Perancangan Aplikasi Android pada Alat Monitoring Kecelakaan dengan Intellegent Transport System
Authors: Putra Muhammad Dandy Pratama , Handayani Ade Silvia , Taqwa Ing. Ahmad , Husni Nyayu Latifah , Novianti Leni
Published: January 2023

The increasing number of transportation also increases the number of traffic accidents. It can happen not only in the open road but also in the quiet road so that the bad things can happen to the accident victims. The delays of handling the accidents often occur due to the delay information that received by the police or the nearest hospital. This is due to the information that obtained by local people and forwarded to the authorities is slow. Therefore a system that can monitor the vehicle remotely will be needed nowdays. By building an accident monitoring system using the Intelligent Transport System (ITS), it is hoped that it can monitor the vehicle and through Android can directly check the coordinates of the vehicle and the condition of the vehicle. In the design of the accident monitoring system tool using the SVM (Support Vector Machine) method. Testing this tool uses hardware consisting of Rasberry PI 3, Arduino Uno, Sensor FC04, Accelerometer 6050, Vibration Shock Sensor, Camera Pi Noir, panic button, GPS and Android Application as an interface with the user. The results of this research show that the tool made has a percentage of delays between 1 to 5 seconds, all data from the accident monitoring system tool is directly sent to the Android application in real time based on the internet network speed connection