Reviewerly/exHarmony huggingface dataset:
Penerapan K-Means pada Segmentasi Pasar untuk Riset Pemasaran pada Startup Early Stage dengan Menggunakan CRISP-DM

Early stage startup would conduct ideation, problem solving, and market research. One of the stages in market research is market segmentation. Normally, early stage startups do not have enough resources, thus many processes are done manually. This encourages inacurracies and lessen the objectiveness in evaluating market situation which is important for the growth of early stage startups. This research focuses on developing a machine learning based application for market segmentation. The framework used here is CRISP-DM, which is a framework used in data mining. This framework has six phases, which consists of business understanding, data understanding, data preparation, modelling, deployment, and evaluation, to identify the input and output of a process. The data model used in this application is K-Means, which is a common algorithm used for clustering or dividing a set of data into groups according to their attributes. The application developed is able to output results in the form of visualization and the segmentation in excel format. With this, the early stage startup is able to process their data to identify segments in the market. For future research, this application could be improved in the efficiency and accuracy of the model. The application could be improved in the aspects of UI/UX design, the algorithm used, the number of clusters, and the analysis of the dataset, as well as adding a predictive analysis feature
Peramalan Tingkat Pencemaran Udara Akibat Kendaraan Bermotor Dengan Metode Time Series Cheng

Air pollution can be defined as the presence of a substance, energy, from different components in environmental air activities through various community activities, including in the field of transportation because 70% of air pollution comes from vehicles. In line with various human needs to move places and activities, transportation activities will also increase following the existing growth, this progress can be seen by the increasing number of existing vehicles and continues to grow from year to year, including in the Special Region of Yogyakarta (DIY). The increasing number of vehicles can lead to congestion, which has a negative impact in the form of air pollution. One of the most common pollutants produced by motorized vehicles is carbon monoxide (CO), carbon monoxide produced by motorized vehicles produces a negative nuisance to public health. Carbon monoxide is a toxic gas, which can interfere with hemoglobin (Hb) to deliver fresh oxygen to the body, when oxygen supplies are reduced it will cause shortness of breath and even death as the worst consequence. Based on the problems described, it becomes a reference in predicting the amount of carbon monoxide parameters in the air using Fuzzy Time Series Cheng which will be displayed in a web-based application. The study was conducted using 30 data obtained from the Environmental Service of the city of Yogyakarta, with the results of the accuracy test using the Mean Absolute Percentage Error (MAPE) getting an inaccuracy value of 6.10% which is included in the very good forecasting category
Pengembangan Aplikasi Pengenalan Kuliner Dan E-Recipe Khas Kalimantan Tengah Berbasis Android

The culinary specialties of an area are part of local wisdom that must be preserved. Central Kalimantan with its cultural customs and local craftsmanship which is still very high has a variety of culinary delights with unique and interesting tastes and appearances. The problem that occurs is that the younger generation now knows more about European-style foreign cuisine and other foreign countries so that when asked about the local cuisine, not many people know about it. The culinary introduction along with its recipes aims to introduce as well as maintain and preserve these recipes so that they can still be passed on by the younger generation, especially the local people of Central Kalimantan. Along with the times, Android-based applications are in great demand among young people because of the various features that make it easy and enough to download the application on the Play Store. This application is named e-Recipe Cullinary KalTeng. The user interface of this application is designed using Figma and developed using the Flutter Platform with the Dart programming language. Features in this application include dishes and snacks typical of Central Kalimantan, each of which is also listed as a recipe. This application is tested using Black Box and the results show that the entire application can run well and is user friendly
UTILIZATION OF PHOTO STORY MEDIA IN LEARNING TO WRITE NARRATIVE ARRANGEMENTS GENRE-BASED APPROACH

This study aims to describe the ability of students to write narrative essays based on a genre-based approach using MPS and using video. This research is an experimental research. The population of this research is the students of Class X SMA DDI Maros, Maros Regency totaling 128 people. The sampling technique was random sampling, selected Class X-1 (experimental class) and Class X-3 (control class). The research data is in the form of writing a narrative essay based on a genre-based approach. The collected data were analyzed using descriptive statistical techniques and inferential statistics. The results showed that students' writing skills using photo story media proved to be more effective. Based on the acquisition of the mean score reached 84.00 (experimental class) while students who received video media obtained an average score of 59.71 (control class). Hypothesis testing through parametric inferential statistical analysis type independent sample T test obtained 8.111&gt; 2.00 which indicates that H0 is rejected and H1 is accepted.
Relationship between quality management and blockchain technology in supply chains

Ever since 2009, when it officially attracted the first great attention of the public, blockchain as a system decentralization technology has promised radical changes in all areas of human labor. As it is a technology that provides complete transparency and resistance to data tampering, as well as an instrument that prevents data manipulation and distributes power and authority throughout the system, and prevents the excessive influence of individual elements of different systems, this concept becomes one of the most resonant notions of the technological, scientific and economic community.This paper explains the basic notions and concepts in the field of quality management, quality infrastructure, and supply chains, as well as the mechanisms and components of blockchain technology, and then proposes the architecture of the information system implemented in quality infrastructure, based on blockchain, as well as its advantages and disadvantages.The goal of this paper is to present the basic concepts of blockchain and how it can be implemented in today's quality infrastructure, improve standardized management systems and their inherent processes and ultimately assure users of system compliance with their requirements and needs.The paper was written based on a combination of results and conclusions of available scientific research papers dealing with problems in the field of quality management, supply chains and blockchain, as well as the conceptualization of systems that could be implemented in a real environment in the future. The key result of this paper is the proposal of mechanisms, elements and roles, as well as the implementation of blockchain technology in supply chains, and its integration with Internet of Things, all in order to build a more robust quality infrastructure and increase the efficiency of processes established through quality management.Finally, as the conclusion of the paper, further research on new models of system architecture is proposed, as well as potential solutions that would overcome the limitations and uncertainties mentioned in this paper.
Prediksi Kebutuhan Energi Listrik Menggunakan Metode Jaringan Syaraf Tiruan

Government owned company of electricity play an important role in the distribution of electrical energy services. The Bagan Batu Auxiliary Service Unit (ULP) is one of the ULPs that plays an important role in the distribution of electrical energy in the Bagan Batu area. Along with the increase in the number of customers every year, the problem of demand for electrical energy changes and increases every year. To predict short-term electrical energy needs, this study uses the Backpropagation Artificial Neural Network method with the help of the MATLAB R2015B tool. The research data for training and network testing uses the history of energy sold (kWh) for the last 10 years with other variables consisting of household customers, business, social, industrial, population growth, Gross Regional Domestic Product (GRDP). The results of the research produce predictions of electrical energy for the next 3 years from 2022 to 2024. This research produces the best architectural model 6-6-1 with the smallest MSE error of 0.003312731 and produces Mean Absolute Percentage Error (MAPE) value of 6%. The research implies benefits for stakeholders to take action on the provision of electrical energy
PENGARUH PENGUASAAN KOSAKATA TERHADAP KEMAMPUAN DEBAT SISWA KELAS X SMA NEGERI 2 KUTACANE

This study aims to determine the effect of vocabulary mastery on the debating ability of students in class X SMA Negeri 2 Kutacane. This type of research is a causal relationship correlation research. Data were collected using tests for class work answering vocabulary questions and conducting debates. The sample in this study was 52 students. The results of the research on vocabulary mastery of class X SMA Negeri 2 Kutacane were seen from 3 levels of assessment, namely high, medium, and low categories. Students who have a high level of vocabulary mastery in the high category are 5 students (15.4%), while students who have a moderate level of vocabulary mastery are 15 students (28.8%) and 29 students have a low category (55.8 %). Thus, it can be concluded that the students' vocabulary mastery is in the medium category. The interpretation of the least square formula values ​​a and b to determine the extent of the estimated influence between vocabulary mastery and debate with a simple linear regression formula Y=0.01+0.0012X is the regression coefficient of the vocabulary mastery variable (X) has a positive sign, which contains the implication that vocabulary mastery (X) affects students' debating ability (Y). The results of the F test, it is known that the Fcount of vocabulary mastery is 0.0067 while the Ftable is 7.16. Fcount is smaller than Ftable, then Ho is accepted and Ha is rejected, meaning = not significant. The conclusion means that this study proves the hypothesis which states that there is a significant and insignificant effect of vocabulary mastery on the debating ability of the tenth graders of SMA Negeri 2 Kutacane. The correlation between X and Y is categorized as having a weak relationship based on the results of the simple linear regression formula test and based on the significance test the results show tcount &lt; t table or 0.0067 &lt; 1.67 which means it is not significant.
EFFEKTIVITAS PEMANFAATAN MEDIA BLOG MENINGKATKAN KEMAMPUAN SISWA DALAM PEMBELAJARAN MENULIS CERPEN DI KELAS XI SMA NEGERI 2 LAWE BULAN

This study aims to determine the improvement of short story writing skills through the use of blog media in class XI students of SMA Negeri 2 Lawe Bulan in the 2021/2022 academic year. The population in this study were all students of class XI and a sample of 36 people. The method used in this study is an experimental method with a one group pretest and posttest design with data analysis using the "t" test. From data processing, it was found that the average value of the initial test of short story writing skills by students was 52.10 and was included in the poor category, with a standard deviation of 6.09 and an increase in the final test score with an average value of 87.36 and included in the good category, with a standard deviation of 7.33. Based on the results of the students' initial and final test scores and if it is associated with the KKM value of Indonesian language subjects for high school, it is 70, the students' short story writing ability is included in the good category. From hypothesis testing, it is obtained that the value of t count = 24.19 and in consultation with the value of t_table at a significant level of 5% = 2,030, thus t_count &gt; t_table or 24.19 &gt; 2,030 then the hypothesis is accepted. So it can be concluded that there is an increase in the ability to write short stories through the use of blog media in class XI students of SMA Negeri 2 Lawe Month in the 2021/2022 Academic Year.
Penerapan Algoritma K-Medoids Clustering Dalam Pembentukan Zona Cluster Vaksin Boster

The effects of the COVID-19 virus pandemic are quite bad for people's lives both in Indonesia and especially in North Sumatra. The spread of the virus is quite fast from the interaction of every community, causing the government to make policies to limit the activities of each community. In addition to policies in limiting community activities, the government also makes policies by distributing vaccines for free to every community starting from the first vaccine, the second and last vaccine is the third vaccine (booster). The purpose of the vaccine itself is to stimulate the body's antibodies to recognize the weakened virus in the vaccine. The aim of the vaccine is to slow the spread of the virus itself. The third vaccine (booster) is a complementary vaccine given by the government so that antibodies can completely inhibit a person from being affected by the COVID-19 virus. Therefore, it is necessary to accelerate the process of administering the third vaccine (booster). This can be done by forming clusters in each region. The purpose of forming clusters is to be able to identify priority areas that should be given the third vaccine (booster). Therefore we need a technique that is able to group/cluster the third vaccine administration zone (booster). One technique that can be used is the K-Medoids Algorithm. The expected results of the research using the K-Medoids Algorithm are able to form a cluster zone which will later be able to find out which areas are the priority for giving the third vaccine (booster).
Penerapan Metode Double Moving Average Dalam Peramalan Permintaan Produk Beras

UD. Putra Tunggal is a trading business that sells people's basic needs such as rice, cooking oil, sugar and other basic needs of the community. This trading business requires forecasting in an effort to process data and produce accurate reports. This is done because UD. Putra Tunggal to determine the demand for rice is unpredictable, so he often experiences a lack of supply of rice to be purchased in serving the demand for rice needed by customers. In designing this system, the author uses the Double Moving Average (DMA) forecasting method for the decision support process in determining the amount of rice stock to be sold for the next month, using the calculation method. Forecasting application is made using visual basic net 2010 programming language with Microsoft Access for data base. From making the system an application can be produced that can control demand optimally and economically and with a high level of accuracy and can predict the amount of rice demand at UD. Putra Tunggal so that the forecast results can help trading businesses to avoid running out of rice demand stocks at UD. Putra Tunggal. The results of the forecasting of sales of CABE rice products 1 year ago, namely in January in 2021, it has been predicted that sales in January 2022 will decrease to 195 sacks of rice to be sold
Klasifikasi Sentimen Masyarakat Terhadap Pemberlakuan Pembatasan Kegiatan Masyarakat Menggunakan Text Mining Pada Twitter

Corona Virus Disease 2019 (Covid-19) is currently a pandemic in the world, including in Indonesia. Various policies have been carried out to break the chain of the spread of Covid-19, one of which is the government's policy of implementing Community Activity Restrictions (PPKM). PPKM is one of the most discussed topics on social media, including Twitter. Tweets on Twitter given by the public to the PPKM policy that was held to evaluate the implementation of PPKM, it is necessary to classify public sentiment using text mining, in this study using the K-Nearest Neighbor (KNN) and Naïve Bayes Classifier (NBC) algorithms with data from tweets. Twitter during the PPKM last year with 3,516 data. Where the results are that the NBC algorithm is better than the KNN algorithm with an accuracy of 79.67% compared to 78.86%, the polarity of public sentiment towards PPKM is also obtained with positive sentiment of 36.83% with a total of 1,295, neutral sentiment of tweets 54.15% with the number of 1,902 tweets, and 9.02% negative sentiment with a total of 317 tweets
PENERAPAN METODE MAKE A MATCH UNTUK MENINGKATKAN KEMAMPUAN MENULIS PANTUN PADA SISWA KELAS VII SMP NEGERI 1 LAWE ALAS

This study aims to determine the improvement of rhyme writing skills through the application of the make a match method to class VII students of SMP Negeri 1 Lawe Alas in the 2021/2022 academic year. As for the population in this study were all students of class VII totaling 43 people and a sample of 22 people. The method used in this study is an experimental method with a one group pretest and posttest design with data analysis using the "t" test. From data processing, it was found that the average value of the initial test of rhyme writing skills by students was 62.27 and included in the less category, with a standard deviation of 4.29 and an increase in the final test score with an average value of 86.36 and included in the good category, with a standard deviation of 4.92. Based on the results of the students' initial and final test scores and if it is associated with the KKM value of Indonesian language subjects for junior high schools of 70, the students' rhyme writing skills are included in the good category. From hypothesis testing, it is obtained that the value of t count = 17.33 and in consultation with the value of t_table at a significant level of 5% = 2,080, thus t_count &gt; t_table or 17.33 &gt; 2,080 then the hypothesis is accepted. So it can be concluded that there is an increase in the ability to write rhymes through the make a match method in class VII students of SMP Negeri 1 Lawe Alas in the 2021/2022 academic year.
Improving Recognition of SIBI Gesture by Combining Skeleton and Hand Shape Features

SIBI (Sign System for Indonesian Language) is an official sign language system used in school for hearing impairment students in Indonesia. This work uses the skeleton and hand shape features to classify SIBI gestures. In order to improve the performance of the gesture classification system, we tried to fuse the features in several different ways. The accuracy results achieved by the feature fusion methods are, in descending order of accuracy: 88.016%, when using sequence-feature-vector concatenation, 85.448% when using Conneau feature vector concatenation, 83.723% when using feature-vector concatenation, and 49.618% when using simple feature concatenation. The sequence-feature-vector concatenation techniques yield noticeably better results than those achieved using single features (82.849% with skeleton feature only, 55.530% for the hand shape feature only). The experiment results show that the combined features of the whole gesture sequence can better distinguish one gesture from another in SIBI than the combined features of each gesture frame. In addition to finding the best feature combination technique, this study also found the most suitable Recurrent Neural Network (RNN) model for recognizing SIBI. The models tested are 1-layer, 2-layer LSTM, and GRU. The experimental results show that the 2-layer bidirectional LSTM has the best performance.
Analysis of Expertise Group Using The Fuzzy K-NN Classification Algorithm (Case Study: School of Computing Telkom University)

The School of Computing at Telkom University has four Expertise Groups that defines the lectures taken by students. Deciding the Expertise Group, will be influential in deciding elective courses and raising the topic of the Final Project. There are many students who are still having difficulty in deciding the Expertise Group and finally only decide based on the most popular Expertise Group without seeing their potential and abilities. The impact of wrong decision of the Expertise Group are delays in graduation time. It will then affect accreditation of study program and university rank, especially in the timely graduation indicator. Therefore, it is necessary to have a system that can predict the decision of the Expertise Group for the School of Computing students based on their academic scores. In this study, prediction using the Fuzzy K-Nearest Neighbor classification algorithm was chosen because it can determine the class based on the nearest neighbor and consider ambiguous data because of the weighting value in each class. There are five tests carried out to get the best model, namely (1) examine the best split training and validation data, (2) examine the best K value, (3) compare Fuzzy K-Nearest Neighbor with Naïve Bayes and Decision Tree (C4.5) which is a commonly used classification algorithm, (4) examine the values of accuracy, precision, recall, f1-score, and (5) examine the values of accuracy using Cross-Validation method. The result is that the model made using Fuzzy K-Nearest Neighbor has an accuracy value of 72% in the case of imbalance data, 62% in the case of applying the undersampling technique, and 56% in the case of applying oversampling. Based on experiments with the other two algorithms, it was found that compared to the other two algorithms, the Fuzzy K-Nearest Neighbor has a higher accuracy value in the case of imbalance data and the case of applying to undersampling, but it has a lower accuracy in the case of applying oversampling, due to the lack of Fuzzy K-Nearest Neighbor in handling small minority data variations.
Rancang Bangun Customer Relationship Management(CRM) Dalam Penjualan Berbasis E-Commerce

The development of the business world has entered a new era, where there are more and more new companies and competing companies in the service, trade, and manufacturing sectors. The higher the level of customer education, the customer will indirectly become critical and careful in making their choices. In a situation like this, the company must not only rely on the products it produces, but the company must also establish good relationships with each of its loyal customers so that customers will be loyal to the company. Umi Nala Shop Aneka Serbu is engaged in sales such as selling children's toys, household appliances and various types of gifts. The problems that occur at Umi Nala Shop Aneka Serbu are, the sales process at Umi Nala Shop Aneka Serbu is still doing conventional sales, there are no facilities that help customers to get information, submit an assessment of the product and also experience difficulties in processing and storing customer data. who have made buying and selling transactions, there is no facility for customers to submit complaints or product evaluations. This study utilizes CRM features that aim to help the service system at Umi Nala Shop Aneka Serbu to attract new customers and retain old customers and expand the sales system. This application is made using the PHP programming language and MySQL as the database server. With this system, it is hoped that the system of marketing, sales, service and utilization of Customer Relationship Management will have a positive influence on customer loyalty so that customers remain loyal to Umi Nala Shop Aneka Serbu