bluuebunny/crossref_metadata_2025 huggingface dataset:
Tourist Places Recommender System Using Cosine Similarity and Singular Value Decomposition Methods
Authors: Tyas Theriana Ayu Waskitaning , Baizal Z K Abdurahman , Dharayani Ramanti
Published: May 2022

Tourism in the city of Bandung has various potentials in the field of culture, regional specialties, buildings, and other tourist attractions. On the Tripadvisor page there are many reviews from users who have visited tourist attractions in the city of Bandung. In this case, user reviews are an important element for analysis. The analysis process is carried out using rule-based sentiment analysis. In conducting the review analysis, we use vaderSentiment to weight the positive and negative values. Positive values are subtracted from negative values to get a compound value and converted to a rating value. The rating value obtained is then processed using the Cosine Similarity and Singular Value Decomposition methods to obtain recommendations for tourist attractions in the city of Bandung. For this method, we use the Root Mean Square Error method as a measure of the level of accuracy between the predicted values. The results of the measurement of the level of accuracy produce a value of 3,489 in the Cosine Similarity method, while the Singular Value Decomposition method gets a value of 1,231. The value in the Singular Value Decomposition method is smaller than the Cosine Similarity method with a difference of 2,258 values
Penerapan Speech Recognition Pada Aplikasi Mobile Kamus Bahasa Sasak
Authors: Yuliadi Yuliadi , Zaen Mohammad Taufan Asri , Rusdan Rusdan , Rodianto Rodianto , W Yunanri
Published: May 2022

Language is an important part of a country or region in communicating between individuals formally and informally. However, it becomes an obstacle, not all outsiders and native residents of Lombok Island (Sasak Ethnic) understand the dialect of Sasak, Lombok Island, West Nusa Tenggara. In addition, in formal and informal meetings, it is rare to use the Sasak language in communicating. Based on these problems we need a media that helps in interacting in the form of a dictionary. The Sasak Language Dictionary is presented in a mobile-based application by utilizing voice as input which is known as Speech Recognition technology. The application is built using a prototype methodology and programming tools using Embarcadero Delphi 10.32 Programming. and SQLite as database. The result of this study is to build a Sasak Language Dictionary mobile application using Speech Recognition in the form of utilizing voice as input.
Perbandingan Algoritma Random Forest Classifier, Support Vector Machine dan Logistic Regression Clasifier Pada Masalah High Dimension (Studi Kasus: Klasifikasi Fake News)
Authors: Willy Willy , Rini Dian Palupi , Samsuryadi Samsuryadi
Published: May 2022

Fake news is false information that looks like it is true. News can also be said as a political weapon whose truth cannot be accounted for which is spread intentionally to achieve a certain goal. Classification of news texts requires calculating a method for each word in the document. Each word processed per document means that the number of data dimensions is equal to the number of words. The more the number of words in a document, the more the number of dimensions in each data (high dimension). The large number of dimensions (high dimension), causes the model-making process (training) to be long and the shortcomings are also clearly visible in seeing the similarity of documents (document similarity). The dataset used in this study amounted to 20000 and 17 attributes. The method used in this study uses a Random Forest Classifier (RFC), Support Vector Machine (SVM) and Logistic Regression (LR) with high dimensions and the results of this study are to obtain a comparison of the accuracy values for each method used
Conversational Recommender Systems Based on Mobile Chatbot for Culinary
Authors: Fadhlullah Ghazi Ahmad , Baizal Z K Abdurahman , Ikhsan Nurul
Published: May 2022

Culinary places are one of the tourists attractions in a place that makes many new culinary places appear. Various types of new foods and drinks are present along with the addition of culinary places. However, this can be a problem when tourists visit a new destination and look for a culinary place that suits their tastes. In the previous research on the recommendation system for culinary places, users only gave their preferences at the beginning of the recommendation process and ignored the operating hours of the recommended culinary places. Therefore, we developed a recommendation system for culinary places by utilizing the context of time from users. We use the Conversational Recommender System on the chatbot platform with the Personalized PageRank algorithm to generate recommendations. In addition, we also use the explanation facility to get an explanation of the recommended items. We use questionnaires and the accuracy of recommendation results to measure user satisfaction and system performance. The evaluation results with a questionnaire involving 81 respondents concluded that users are pretty satisfied with the system built. However, testing with accuracy yields a value of 40%, proving that the system performance is low
Klasifikasi Motif Citra Batik Menggunakan Convolutional Neural Network Berdasarkan K-means Clustering
Authors: Masa Amin Padmo Azam , Hamdani Hamdani
Published: May 2022

Batik has several motifs and patterns so it is necessary to identify certain objects in an image, one of which is the recognition of the image of Yogyakarta batik using the Convolutional Neural Network (CNN) method which is already popular in the use of image data classification. The introduction of batik imagery aims to contribute to the digitization of batik image data and at the same time provide information on types of batik to the public. The batik image recognition process using CNN in this study combines the image segmentation process and the enhancement process with median filters and sharpening. The segmentation process carried out before CNN aims to help separate foreground objects from objects that are not needed in the background. The segmentation process that is commonly used is using K-means Clustering. Where K-means Clustering is used to group data in the same category. Furthermore, the enhancement process using the median filter and sharpening was carried out separately to compare the batik image classification process using CNN based on K-means Clustering from the median filter results and the sharpening results. The batik image classification process with CNN based on K-means Clustering on the median filter resulted in an accuracy value of 100%. Meanwhile, the batik image classification process with CNN based on K-means Clustering from the sharpening results resulted in an accuracy value of 80%.
Analisis Sentimen Pada Isu Vaksin Covid-19 di Indonesia dengan Metode Naive Bayes Classifier
Authors: Septianingrum Fitria , Jaman Jajam Haerul , Enri Ultach
Published: May 2022

The Covid-19 pandemic that has occurred in Indonesia and even in the world has not yet ended. Various efforts have been made by the Indonesian government to minimize the spread of this virus, such as the implementation of a lockdown, Large-Scale Social Restrictions (PSBB), a ban on going home during the Eid al-Fitr holiday, and so on. One of the new policies issued by the government is the vaccination program, where the government has started implementing the program since early 2021 for the people of Indonesia, which aims to increase antibodies to avoid exposure to the Covid-19 virus. To find out opinions, comments, or feedback given by the public on this new policy, sentiment analysis can be done. The process of this sentiment analysis includes data collection, namely the crawled tweet data originating from the Twitter social media. The data is then selected for further pre-processing stage so that the data is clean and ready for classification. Furthermore, sentiment weighting is carried out for data labeling using a lexicon dictionary and negative words. Then after that, the terms or words are weighted with tf-idf and followed by the feature selection process using Information Gain. Furthermore, the classification process is carried out using the Naive Bayes Classifier algorithm to classify the data into 3 classes, namely positive, negative, and neutral sentiments. The results of this study are to produce a model accuracy rate of 78%, recall 80%, and an AUC score of 0.904.
Analisis Perbandingan Algoritma ACO-TS dan ACO-SMARTER Dalam Menyelesaikan Traveling Salesman Problem
Authors: Peranginangin Jimmy , Purba Ronsen , Halim Arwin
Published: May 2022

The research conducted is the Comparative Analysis of the ACO-TS and ACO-SMARTER Algorithms in Solving the Traveling Salesman Problem where the problem to be solved is the traveling salesman problem (TSP). The purpose of this study is to hopefully be able to provide a comparison result of running time and the shortest distance between the ACO-TS algorithm and the ACO-SMARTER algorithm in solving the TSP. The test results show that the combination of the Ant Colony Optimization (ACO) algorithm and the Tabu Search (TS) algorithm is better in terms of achieving the optimum path and running time than the ACO and ACO-SMARTER algorithms in solving the Traveling Salesman Problem. The Tabu Search algorithm in the ACO algorithm acts as a controller for the routes that have been selected so that they are not processed again by the same ant. This will certainly make the ACO-TS algorithm faster in processing data because there is no data on the same route in the next round, where from 200 datasets the running time is obtained at ACO 11.5 seconds and the optimum distance is 76687, ACO SMARTER 8.5 seconds and the optimum distance is 74496 while the ACO-TS only takes 2.9 seconds and the optimum distance is 70558
Pengembangan Teknologi E-Commerce dengan Menerapkan Metode CRM dan Forecasting
Authors: Norman Norman , Rusda Depi
Published: May 2022

The development of e-commerce technology is a sales process that is carried out online which can make it easier to sell without having to come to the store directly. Dalwa Zain Collection store which is a clothing store that sells Muslim and Muslim clothing for men and women. This e-commerce sales system will be applied to the Dalwa Zain Collection store to make it easier for shop owners to make transactions and also make it easier for consumers at the purchase stage without having to go to the shop. In this e-commerce system, there are two methods, namely to apply the forecasting method to carry out the annual forecasting stage at the Dalwa Zain Collection store and to apply the CRM (Customer Relationship Management) method as the application of discounts on clothing in the Dalwa Zain Collection store. This is the stage of the process that will be carried out so that the Dalwa Zain Collection store can see its sales from year to year and also make the discount that will be set can be helped to overcome quickly.
Analisis Faktor Penerimaan Media Internet sebagai Sumber Informasi Kesehatan dengan Model UTAUT dan HBM
Authors: Widianto Heru , Pratama Ahmad R , Kurniawan Rahadian
Published: May 2022

People are increasingly turning to the internet for health-related information. It is very easy to perform or obtain health-related services or information on the internet using different types of devices. This study's goal is to assess public acceptance of the internet as a source of health information by combining the Unified Theory of Acceptance and Use of Technology (UTAUT) with the Health Belief Model (HBM). SEM techniques were used to analyze data collected from 324 respondents via online questionnaires. Two factors from the HBM model: self efficacy (SE) and cues to action (CA) were found as the strongest factors behind the acceptance of the internet as a source of health information. Two other factors from UTAUT model; Social Influence (SI) and Performance Expectancy (PE) also had significant effects, albeit not as strong, on the acceptance of internet media as a source of health information. This study's findings also point to the possibility of incorrect self-medication when excessive perceived self-efficacy (SE) is combined with symptoms as cues to action (CA) and social influence (SI) when looking up health information online
Implementasi Metode SMART Untuk Penentuan Platform Pembelajaran Jarak Jauh Masa Pandemi
Authors: Rajiansyah Rajiansyah , Fajri Ahmad
Published: May 2022

The pandemic period is difficult times for all nations and countries around the world because the pandemic period is a period that limits many activities carried out as usual due to an outbreak of the Covid-19 virus as the most contagious and quite deadly virus, including in learning activities for an educational institution for the sake of education. break the rope of the spread of a larger virus so that a platform is used that helps in carrying out the teaching and learning process, the many types of platforms currently available make it difficult to determine the most appropriate platform for its use based on several criteria such as usability, affordability, maintability, accessibility and compatibility. the selection using a decision support system to facilitate the decision-making process appropriately, the process of using a decision support system using the SMART (Simple Multi Attribute Rating Technique) method, the results obtained are ah A2 with a value of 0.92
Penerapan Apriori Hybrid Pada Transaksi Penjualan Barang
Authors: Asana I Made Dwi Putra , Ginantra Ni Luh Wiwik Sri Rahayu , Parwita Wayan Gede Suka , Krismentari Ni Kadek Bumi , Meinarni Ni Putu Suci
Published: May 2022

Ayu Nadi Swalayan is a retail company that produces a lot of every day sales transaction data, and it is stored for years without knowing the benefits and the placement of the goods is still random. From these problems, an effort is needed to process the data so the data is useful in the future. One of the process is using data mining techniques with apriori hybrid algorithm to find association rules for an items combination. Data product sale in a certain period is used to find the association rules. The results of this study are the development of applications that are used to determine consumer spending habits. So that the company can develop a strategy to promote the product sale and close placement for items that are often purchased together. The application testing found the effect of minimum support, minimum confidence on the number of rules, and lift ratio testing. The smaller the minimum support and minimum confidence, the more rules are generated and vice versa. The lift ratio value is directly proportional to the minimum confidence value and inversely proportional to the minimum support value. The higher the minimum confidence value, the higher the lift ratio value and vice versa. The more items in the transaction cause the minimum support threshold to be lowered in order to generate rules for the data analysis process with the hybrid apriori algorithm
Klasifikasi Kematangan Buah Pisang Ambon Menggunakan Metode KNN dan PCA Berdasarkan Citra RGB dan HSV
Authors: Adenugraha Setya Putra , Arinal Veri , Mulyana Dadang Iskandar
Published: May 2022

Banana fruit or in scientific language is called Musa Paradisiaca. One type of banana that is easy to grow and develop in the tropics of Indonesia is the Cavendish Banana or commonly known as the Ambon Banana. The quality of Ambon bananas must be maintained because Ambon bananas grown in Indonesia also supply the needs of foreign markets. The quality of bananas is very influential from the time of harvesting, the level of maturity of bananas is related to marketing reach. Basically, farmers use manual methods in determining the maturity level of Ambon bananas, so there are several factors that can make the classification results less accurate. Based on these problems, a system was made to classify the maturity level of Ambon bananas by utilizing the RGB and HSV color features using the K-Nearest Neighbor (KNN) method. Classification uses image processing by utilizing matlab software for making a classification system with 3 classes, namely raw, ripe, and overcooked. The results of this study are expected to help Ambon banana farmers in classifying the maturity level of Ambon bananas. In this study using data obtained from the place of observation. The data used in this study were 41 data which were divided into 30 training data and 11 test data. The data is classified using the KNN method by measuring the distance to the nearest neighbor with a value of K=5. From this study, the results obtained accuracy of 90.9% with the results of the classification of test data as many as 10 data received accurate classification results and 1 data received inaccurate classification results.
Pengembangan Sistem Pemantauan Aktivitas Pengawasan Satpam dengan Proses Validasi Dinamis QR-Code pada Aplikasi Patrolee
Authors: Saputra Laurentius Kuncoro Probo , Raharjo Willy Sudiarto , Restyandito Restyandito
Published: May 2022

Internet of Things (IoT) technology provides system integration to accelerate wireless remote data acquisition. This paper presents the implementation of IoT based applications to monitor security guard surveillance activities in the campus environment. The traditional reporting system still has many limitations. The security guard should make a written report to his supervisor and send the surveillance images using a third-party instant messaging application. The reporting results are not integrated. Implementation of IoT system which consists of Dynamic QR-code Display, Android Application, Web Application, and Cloud Database, enables the integration and real-time reporting system. Security guard reports can be seen directly, both written reports and the surveillance image, using a web application. Each security guard on duty has its unique QR code for each location and current surveillance schedule. It makes the security guard cannot ask their duties to other people. The results of this research show that this system has been able to meet the needs of security officers. The success rate of security guards when doing the task using this application is 90%.
Komparasi Metode K-Nearest Neighbor dan Random Forest Dalam Prediksi Akurasi Klasifikasi Pengobatan Penyakit Kutil
Authors: Erdiansyah Umri , Irmansyah Lubis Ahmadi , Erwansyah Kamil
Published: May 2022

Warts are a skin health problem, usually characterized by small, rough bumps on the surface of the skin caused by a virus, known as the human papillomavirus (HPV). The common way of treating warts is with immunotherapy, which is the treatment of warts by strengthening the body's immune system. In the process of predicting and diagnosing warts, it can be done by applying Machine Learning. This study focuses on the comparison of the K-Nearest Neighbor classification method with Random Forest to see the level of accuracy in predicting the success of the treatment of warts. Data for Immunotheraphy was obtained from the UCI Machine Learning Repository with a total of 90 data records, 7 attributes and 1 attribute class. Based on the results of testing the K-Nearest Neighbor and Random Forest methods to see the accuracy of the prediction of the success of the data being tested, the results obtained are the accuracy of the KNN method of 90.00% and the Random Forest method with an accuracy of 85.50%. From the results obtained from the tests that have been carried out, it is known that the Random Forest method is a better method than K-Nearest Neighbor in predicting accuracy in the Immunotheraphy Dataset.
Pengembangan Sistem Informasi Pariwisata Geopark Ciletuh Menerapkan Metode User Centered Design
Authors: Firdaus Hafidh , Hidayatullah Deny
Published: May 2022

Ciletuh Geopark is a tourist attraction located in Sukabumi Regency, West Java, Indonesia. In addition, Ciletuh Geopark is one of the tours that has a lot of geology, biology, and culture. One of the places that has an attraction for local and foreign tourists is Palangpang Beach. Many people do not know information about Palangpang Beach. So the creation of a solution to make this system. This design is made with PHP with MySQL programming as the database. The method used in this system is User Centered Design. This application have some reason to made, that is help some people to get some information about Palangpang Beach.
Prediksi Harga Saham Subsektor Farmasi Menggunakan Geometric Brownian Motion
Authors: Bhakti Henny Dwi
Published: May 2022

Investing in stocks is a popular type of investment today. During the current COVID-19 pandemic, the shares of companies in the pharmaceutical sub-sector are becoming more attractive. Stock price movements determine whether investors will increase their investment in a company or withdraw their money. To minimize the risk of investor loss, forecasting is carried out on the daily closing of stock prices. Forecasting is the best method to predict future stock prices Geometric Brownian motion is a method used to predict time series data, where random variables follow Brownian motion. In this study, simulation and analysis of stock returns and fluctuations (volatility) of 5 companies from the basic industry and chemical sector (Basic Industry & Chemicals), pharmaceutical sub-sector on the IDX will be carried out. The five companies are PT Darya-Varia Laboratoria Tbk (DVLA), PT Indofarma (Persero) Tbk (INAF), PT Kimia Farma (Persero) Tbk (KAEF), PT Kalbe Farma Tbk (KLBF), and PT Industri Jamu and Pharmaceutical Sido. Muncul Tbk (SIDO). After the Kolmogorov-Smirnov normalization test, the stocks that meet the normal distribution are KLBF and SIDO. Then the predicted MAPE value of the two stocks is calculated. The MAPE values for KLBF at 100 iterations, 1000 iterations and 10000 iterations were 2.1073%, 1.4382% and 1.2847%.. MAPE values for SIDO at 100 iterations, 1000 iterations and 10000 iterations are 2.0136%, 2.2568%, and 2.0677%.
Perbandingan Algoritma Stochastic Gradient Descent dan Naïve Bayes Pada Klasifikasi Diabetic Retinopathy
Authors: Hadistio Ryan Rinaldi , Mawengkang Herman , Zarlis Muhammad
Published: May 2022

The purpose of this research is to compare the performance of the Stochastic Gradient Descent and Naïve Bayes algorithms in classifying Diabetic Retinopathy. Diabetic retinopathy is a complication of diabetes that causes damage to the retina of the eye. These disturbances can be detected by early detection through data extracted from eye images. This research uses source data from the UCI Machine Learning Repository, namely Diabetic Retinopathy Debrecen, totaling 1,151 data records with 19 attributes consisting of 18 attributes and 1 target attribute. The validation test uses the Cross Validation method with a total of 10 k. From the comparison of the two proposed methods, the Stochastic Gradient Descent algorithm produces an average test accuracy of 70.16%, while Naïve Bayes produces an average accuracy of 56.74%. From the comparison of the two algorithms, the Stochastic Gradient Descent algorithm is known to be superior in classifying the Diabetic Retinopathy Debrecen Dataset.
Komparasi QoS Load Balancing Pada 4 Line Internet dengan Metode PCC, ECMP dan NTH
Authors: Tantoni Ahmad , Zaen Mohammad Taufan Asri , Mutawalli Lalu
Published: May 2022

The ability to communicate on the internet who do not know the distance and time are the key requirements for improving the work on the internet. To improve performance access to the internet is required solutions as the best of the internet network that can be relied on, so that companies use more than one ISP (Internet Service Provider) to maintain the quality of the internet access with the goal to avoid the interruption of internet access and have backup internet access network if you experience down resulting in disruption of the company's performance in carrying out their duties. One of the contributions of information technology to overcome the merging problems two or more-line internet is a technique of load balancing. This study aims to determine the comparison of QoS load balancing on a 4 line by the method of PCC, ECMP and NTH on real tool MikroTik rb2011UiAS-2HnD. The test method uses speedtest.net from the results it will be seen ping, speed download, speed date, as well as monitoring from the side of the router MikroTik. Stages of research using the method of NDLC (Network Development Life Cycle), namely analysis, design, simulation, prototype, implementation, monitoring and management. With the usefulness of this research is to know the performance resulting from each method of load balancing that is PCC, ECMP and NTH with 4-line internet on MikroTik
Prototype Sterilisasi Virus Barang Belanjaan Online Berbasis Arduino
Authors: Ashari Maulana , Zaen Mohammad Taufan Asri , Putri Juliyantika Ayudita , Imtihan Khairul , Bagye Wire
Published: May 2022

In this study, efforts were made to break the chain of spread of COVID-19 with the main technique of heating to dry the liquid on the surface of the groceries. Built a heating box with a length of width and height of 65cm using the main material of fiber glass with a thickness of 3mm. By using Arduino Uno as a control tool, the MLX temperature sensor is used to measure the temperature in the box and the Proximity sensor is used as a sensor to detect goods. The method used to design the tool is the Research and Development (R&D) method. The test results using an initial temperature of 47º and the desired temperature of 56ºC takes 07 minutes 21 seconds the temperature displayed by the LCD has reached 56ºC, when the surface temperature of the goods is measured using a thermogun, the results are 43.1ºC. Complete trial using an initial temperature of 29ºC and the desired temperature of 56ºC takes 2 minutes 18 seconds, the temperature displayed on the LCD has reached 56ºC. When the surface temperature of the goods is measured using a thermogun, the results are 55.5ºC. The results of the last test show that the temperature is close to 56ºC.
Identifikasi Objek Menggunakan Proses Deteksi Tepi Metode Laplacian of Gaussian Dan Canny Terhadap Citra Sidik Jari
Authors: Suharto Edi , Simargolang Muhammad Yasin , Siregar Muhammad Noor Hasan , Windarto Agus Perdana
Published: May 2022

Identification is the identification or determination of an object based on evidence as a clue. The objective of the research was to identify biometric images using edge detection of LoG (Laplacian of Gaussian), Canny, and LoG+Canny with different shapes and dimensions. It is expected that the object can still be identified with different shapes and dimensions. The sample of data used was 20 fingerprint images. This fingerprint image was tested using the methods LoG, Canny and LoG+Canny. The process begins with the image reading, and then the image is converted to grayscale, edge detection and image segmentation. The final result is the identification of the image. The results show that the average accuracy is 89.9 per cent for the LoG method, while 81.8 per cent for the Canny method and 90.7 per cent for the LoG + Canny method. From 10 fingerprint image tests, 8 fingerprint images can be identified by both methods. While the LoG + Canny method is capable of identifying 9 fingerprint images. The LoG method can detect images of 2, 4, 5, 6, 7, 8, 9, 10; while the Canny method can detect images of 2, 3, 4, 6, 7, 8, 9, 10; and the LoG + Canny method can detect images of 1, 2, 3, 4, 6, 7, 8, 9, 10. The minimum and maximum pixel values for the LoG method are 11 pixels for the test image and 25327 pixels for the database image. While the minimum and maximum pixel values for the Canny method are 148 pixels for the test image and 42323 pixels for the database image. In the meantime, the minimum and maximum pixel values for the LoG + Canny method are 806 pixels for the test image and 57972 pixels for the database image. The LoG + Canny method can outperform other methods for the identification of fingerprint images from the results of the tests carried out. In addition to the higher accuracy value, the resulting error value is also much smaller. The object images in the LoG method that have not been identified are numbers 1 and 3 with an error of 27.27 percent and 58.33. While the Canny method that has not been identified is number 1 and 5 with an error of 98.31 per cent and 59.92 per cent. The LoG + Canny method that cannot be identified is number 5 with an error of 61.69 per cent. The mean error values for the three methods were 10.1%, 18.2% and 9.3% (LoG, Canny, LoG + Canny).
Sistem Pendukung Keputusan Penentuan Wali Kelas Berdasarkan Prestasi Guru Dengan Metode Analytical Hierarchy Process (AHP) Berbasis Web
Authors: Aminuddin Fattachul Huda , Riyanda Afif Rahman , Djauhari Teuku
Published: May 2022

Decision Support System (DSS) is a procedure-based model for processing data and assisting management in making decisions. Decision Support System (DSS) is a problem solving program and provides a solution to a decision in both structured and unstructured situations. Currently in the homeroom at SMA Ferdy Ferry Putra Jambi, it is still done subjectively by the principal. The assessment carried out by the principal is only based on the internal closeness factor between the teacher and the principal. Some possibilities for homeroom teachers are also based on age and years of service at school, causing injustice among teachers. The purpose of this study is to assist the school in determining homeroom teachers based on the achievements and services of teachers in educating students. The research method used is the Analytical Hierarchy Process (AHP) method. Research in making this application is carried out using the waterfall model with 6 stages, namely needs analysis, design or design, coding, testing, implementation, and maintenance. Making this application program was developed with the PHP programming language and the database used is MySQL. With this system, it can help the school in determining the ranking of teachers based on the value of services that will be selected as homeroom teachers
Review: Metode-Metode Ekstraksi Ciri dan Klasifikasi Identifikasi Pembicara
Authors: Adhinata Faisal Dharma , Ramadhan Nur Ghaniaviyanto
Published: May 2022

Identifying a person's identity still often uses an ID card (KTP, SIM, passport, etc.). This method has a weakness because the ID Card is easily damaged and lost. Biometric recognition systems provide a solution by using human body parts as identity recognition. Sounds are readily available biometric information. Voice pattern recognition is used for the speaker identification process to obtain the identity of someone speaking. This paper reviews several feature extraction and classification methods that are often used in speaker identification. The selection of feature extraction methods and classification functions in computation and the level of accuracy of the speaker identification system. Based on the survey dataset applied with the feature extraction method, the Mel Frequency Cepstral Coefficients (MFCC) method has high accuracy even with noise input. Then in classification, the Gaussian Mixture Model (GMM) method is most often used because it can work in noise. Recently, a hybrid classifier has been developed, which increases the accuracy value.
Sistem Pendukung Keputusan Penentuan Kerani Timbang Lapangan Terbaik Menerapkan Metode Operational Competitiveness Rating Analysis (OCRA)
Authors: Nasyuha Asyahri Hadi , Zulkifli Zulkifli , Purnama Iwan , Sidabutar Agustina , Karim Abdul , Mesran Mesran
Published: May 2022

The weighing clerk is part of the BUMN employees whose job is to calculate incoming and outgoing income from the results of the company's raw material scales. Of course, every company engaged in this field requires quality weighing machines that can improve the quality of a company. In selecting the best field weigh-in, several criteria can be used as references, such as performance, responsibility, age, level, and number of dependents. And due to the large amount of data that is not suitable for field weighing clerks but has registered to be field team assistants, the head of the company is confused and it takes a long time to select suitable field weighing clerks to be employed. In order to assist in the selection of candidates for the weigh-in election, a decision support system is needed. The Operational Competitiveness Rating Analysis (OCRA) method is one of the supporting methods in determining the priority criteria for the selection of field weigh-in candidates. As for the results in the research on the selection of the best field weighing clerk, alternative A2 with a value of 0.583 on behalf of the Libra Purba.
Penerimaan Bantuan Pangan Non Tunai (BPNT) Menggunakan Metode ARAS
Authors: Hutagalung Juniar , Nofriansyah Dicky , Syahdian Mufthi Adi
Published: May 2022

Non-Cash Food Assistance (BPNT) is social food assistance that is paid in non-cash form every month by the government. However, the problem of identifying BPNT recipients has not been identified properly and it is not certain that the poor really deserve to receive BPNT. So far, the existing system has not been optimal for selecting BPNT recipients with the existing criteria. Data management still uses a manual system and is not effective in determining who is entitled to receive BPNT and who is not. A creative solution to overcome this problem is the use of a web-based decision support system (DSS) using the Additive Ratio Assessment (ARAS) method. A system based on human and computer intelligence that creates options to improve decision making. The purpose of this research is to develop a system that helps decision making in deciding the acceptance of BPNT in poor families. This makes it easy to determine who is eligible and who is not eligible for assistance. This method is easy to apply for ranking by comparing it with other methods so that the results are more precise and accurate. The calculation process for the ARAS method using a very complex web-based system greatly facilitates and speeds up the determination of BPNT receipts. To facilitate implementation, 10 data with 5 criteria were used as sample data. Based on the calculation results of the potential beneficiaries on behalf of Selamat and Prayogi, the priority is getting assistance with a final score of < 0.07.
Pengembangan Sistem Informasi Peminjaman Alat Laboratorium Berbasis Android dan Realtime Database Menerapkan Framework FAST
Authors: Jayadi Dimas , Darusalam Ucuk
Published: May 2022

Practical tools are one of the lecture facilities that are at risk of being damaged or lost, so a system for recording borrowing and returning transactions is needed so that the existence of borrower data and tools can be known. Therefore, an android-based information system was designed as a medium for borrowing and returning laboratory equipment, to make it easier to borrow tools, record equipment borrowing, and inventory laboratory equipment. The method used in this research is the FAST (Framework for the Application Systems Thinking) method. This application is built using the Java programming language and utilizes the Firebase Real-time Database for data storage and processing. The application of this android-based information system has had a positive impact on laboratory assistants and colleagues in the process of borrowing and returning equipment. In addition, for the Computer Vision laboratory assistant Multimedia, this information system helps in carrying out inventory and maintenance of lab equipment.
Prediction of Basic Material Prices on Major Holidays Using Multi-Layer Perceptron
Authors: Ihsan Rivan Nur , Saadah Siti , Wulandari Gia Septiana
Published: May 2022

The prediction of the price of basic necessities on major holidays in Indonesia, such as Eid al-Fitr, Christmas, New Year, Chinese New Year, and Eid al-Adha, is something that needs to be observed, because there are often movements in the prices of basic commodities that increase or decrease very drastically. One of the main ingredients experiencing this is eggs, which often experience a significant increase, so it is necessary to make observations in the form of predictions to keep control of fluctuations, especially before and after the big day occurs. In this study, predictions were made on the price of basic commodities on the big day. With the prediction of the cost of goods on the big day, it is hoped that related parties can be assisted in monitoring and stabilizing the movement of basic commodity prices on the market. In this study, a prediction system for the price of basic commodities was produced using the Multi-Layer Perceptron (MLP) method. This MLP method can predict time-series data that experiences a lot of fluctuation. In this prediction, MLP can make predictions on ten prices of basic commodities on major holidays every day. The results of this study were divided into three groups, namely Worst, Average, and Best. The division of these three groups separates which staple ingredients have the closest predictions to their actual values. The Worst group is the group whose prediction results are still quite far from the actual, the Average group which is close to the actual value, and the Best group which has the best results because it is very close to the actual value. With prediction results measured using MSE, the Worst group consisted of cooking oil (MSE 0.00197), beef (0.00186), rice (0.00118), and sugar (0.00100). Then the Average group consisted of eggs (0.00096), red chili (0.00085), chicken (0.00074), garlic (0.00062), and cayenne pepper (0.00056). Finally, the Best group only consisted of Shallots with an MSE of 0.00040.
Analisis Sentimen Gofood Berdasarkan Twitter Menggunakan Metode Naïve Bayes dan Support Vector Machine
Authors: Petiwi Melati Indah , Triayudi Agung , Sholihati Ira Diana
Published: May 2022

The Covid-19 pandemic in Indonesia has an impact on every sector of life, including the economy. The government implements social activities that make people have to carry out activities at home. Because of this, humans choose to do everything digitally, including ordering food. With the application of public interest in ordering food online, the income of one of the food orders, namely Gojek (Gofood) has increased. However, Gofood has many pros and cons in the community. In this case, many people give their opinion about the use of social media, especially twitter. The purpose of this study was to analyze public opinion on the performance of Gojek (Gofood) in Indonesia. The grouping into three classes, namely positive, negative and neutral classes were tested using the Naïve Bayes and SVM methods and compared the two methods. The analysis of public sentiment regarding Gofood on Twitter resulted in 92.8% worthy neutral, 5.2% worthy positive and 2.0% worthy negative. Comparing the accuracy results, the Support Vector Machine method has greater accuracy than the Naïve Bayes method, with the Support Vector Machine accuracy values of 83% and 98.5%, while the Nave Bayes accuracy values are 74.6% and 91.5% respectively.
Sistem Pakar Untuk Mendiagnosa Penyakit Mata Menerapkan Metode Certainty Factor dan Forward Chaining
Authors: Oktaviansyah Marcelino , Tamara Rima , Fitri Iskandar
Published: May 2022

Disorders of the eye become a disease that is often experienced. There is a new symptom model found, causing confusion that occurs. Diseases of the eye often attack humans, especially in the current era of digital technology, because they spend more time staring at cell phone or computer screens. So the application of this expert system is made to provide solutions for the community to diagnose the symptoms that are often experienced. In making this application, the forward chaining method and certainty factor are used in the application built and comparison with the combined forward chaining and naive Bayes method. The test is carried out by testing 40 data samples based on existing symptoms, carried out by the system and also manually to see the accuracy of the values given. The results given are that there is a fairly high level of certainty in the diagnosis of hypermetropia with a certainty value of 88.43% and the smallest certainty value in the diagnosis of presbyopia with a value of 61.702% of the total testing obtained a probability level of certainty ranging from 51%-79%.
Implementasi Algoritma Haversine Formula dan Location Based Service Pada Aplikasi Pencarian Lokasi Bird Contest Berbasis Android
Authors: Prihantoro Dimas Dwi , Wahyuddin Mohammad Iwan
Published: May 2022

At this time, the chirping bird competition has become so popular that it can be said to be a trend in Cibinong District. The number of enthusiastic chirping maniacs who have just entered this competition, not a few of the chirping maniacs do not know where the competition is taking place in Cibinong District. With the lack of information about the competition venue in Cibinong District. So a location search application was made using the Location Based Service method as the location of the user's point and the Haversine Formula Algorithm as a measure of the distance. From the measurement results of the haversine formula by comparing the application's haversine distance to the distance of google maps to get an average value of 0.039 kilometers.
Analisa UI/UX Terhadap Perancangan Website Laundry dengan Metode Human Centered Design dan User Experience Questionnaire
Authors: Salsabilah Salsabilah , Wahyuddin Moh. Iwan , Sari Ratih Titi Komala
Published: May 2022

The development of information technology today has developed very rapidly where in its development can help people from all walks of life in doing anything, one of which is in the laundry service business sector.  My laundry is one of the businesses that offer Laundry services that provide kiloan washingservices. In My laundry  In doing data collection or recording my laundry data still does manually. In  solving the problems that occur in my laundry system the solution is to apply an information technology system that uses a website. In a design of user interface and user experience can be used as basic things in the creation of a website. In conducting  analysis and design of user interface and user experience  using the Human Centered Design (HCD) approach and user experience questionnaire (UEQ) method is expected to provide conveniencefor users of the website
Konsep Sistem Pendukung Keputusan & Pengembangan Sistem Informasi Media Sosial Dalam Menghasilkan Framework Empathy Netizen
Authors: Nurdayana Mardella Maulida , Suharnomo Suharnomo
Published: May 2022

Social media is growing very rapidly in the current era of globalization. This development requires a guide to be able to manage the flow of communication well on social media. In this study, the method used is honeycomb, what is social media listening? and Daniel Goleman, these three concepts will be able to produce a netizen empathy framework on social media. Furthermore, this research is also a development of previous research: Designing the Concept of Leaderships Intelligence (CI2.1) Version 2.0 inside social media Using Ken Watanabe Problem Solving 101 Methods. If the previous research discussed the categories of leadership in social media in detail, then in this follow-up study, how do we apply the concept of empathy in communication so that it can produce netizens who can provide solutions to the community. Problems such as: understanding each other in communication is still something that must be discussed and given a solution, listening and providing solutions are also important things that must be discussed and giving an opinion and proper assessment of a comment or criticism is also a problem that must be addressed immediately. The results of this study are a framework and guide so that netizens can improve the quality of empathy in communication, provide solutions and other things that can be used positively in order to form a positive environment on social media and produce creative solutions.
PENGENALAN KARAKTER BRAILLE MEMANFAATKAN CONVOLUTIONAL NEURAL NETWORK
Authors: Andriansyah Marindo , Junaedi Hartarto
Published: May 2022

ABSTRACTBraille is a character designed for the blind. Braille letters consist of six raised dots arranged in three rows and two columns. Braille is read by touch, so finger sensitivity is very important. Braille combinations need to be memorized, making them very difficult to learn. This study discusses the introduction of braille characters using the Convolutional Neural Network (CNN) method. CNN will process 3 data sets, 60, 100, and 150 data with each data using 5, 10, 25, and 50 epochs. The highest accuracy value in the training process is 99.87% with a loss value of 0.232. In the recognition process, the highest accuracy is 99.62% with a recognition error of 1 image out of 260 images.

Keywords: Braille, CNN, Character, Recognition.

 

ABSTRAKHuruf braille merupakan karakter yang dirancang untuk orang buta. Huruf braille terdiri dari enam titik timbul yang tersusun dalam tiga baris dan dua kolom. Huruf braille dibaca dengan menggunakan sentuhan, oleh sebab itu sensifitas jari sangat penting. Kombinasi huruf braille perlu dihafalkan, sehingga sangat sulit untuk dipelajari. Penelitian ini membahas pengenalan karakter braille dengan menggunakan metode Convolutional Neural Network (CNN). CNN akan memproses 3 kelompok data, 60, 100, dan 150 data dengan masing-masing data menggunakan 5, 10, 25, dan 50 epoch. Nilai akurasi tertinggi pada proses traning sebesar 99.87% dengan nilai loss sebesar 0.232. Dalam proses pengenalan akurasi tertinggi sebesar 99.62% dengan kesalahan pengenalan 1 gambar dari 260 gambar.

Kata Kunci: Braille, CNN, Karakter, Pengenalan.
The Kandungan Fitokimia dan Aktivitas Antioksidan Krim Fraksi Etanol Kulit Buah Jeruk Manis (Citrus sinensis (L.) Osbeck)
Authors: SARI WAHYUNITA YULIA , Yuliastuti Definingsih , Ulfa Maria
Published: May 2022

Buah jeruk manis umumnya dimanfaatkan pada bagian daging buah, sedangkan kulitnya hanya menjadi limbah. Limbah kulit buah jeruk manis banyak dijumpai di masyarakat memiliki kandungan senyawa antioksidan. Limbah kulit buah jeruk manis dapat diolah menjadi sediaan krim yang dapat dimanfaatkan oleh masyarakat.

Krim dari limbah kulit buah jeruk manis dibuat menggunakan metode ekstraksi maserasi dan fraksinasi cair-cair. Metode ekstraksi maserasi menggunakan pelarut etanol 70%, sedangkan metode fraksinasi menggunakan pelarut n-Heksana, etil asetat dan etanol 70%. Krim fraksi etanol 70% kulit buah jeruk manis dibuat dalam beberapa formula FI (3%), FII (6%) dan FIII (9%). Skrining kandungan fitokimia dari kulit buah jeruk manis dilakukan menggunakan pereaksi kimia.

Kulit buah jeruk manis memiliki kandungan senyawa vitamin C, flavonoid dan minyak atsiri. Sediaan krim fraksi etanol 70% kulit buah jeruk (FI, FII, FIII) menunjukkan bahwa krim memiliki warna, tekstur dan sifat fisik yang baik.