Reviewerly/exHarmony huggingface dataset:
Analisis IT Service Management Pada Aplikasi Traveloka Menggunakan Framework ITIL V3

Information technology nowadays is developing very rapidly, especially in the tourism sector. The use of technology in the tourism sector has made Traveloka's services popular because they can be accessed easily, quickly and reliably. The Traveloka service provides a service where users can order plane tickets from various airlines that collaborate with Traveloka with different price variants. This service makes it easier for people to enjoy their holidays and find out plane ticket prices easily. This research used data collection through questionnaires and obtained 30 respondents. Then a validity and reliability test is carried out to measure the quality level of a statement, after which a maturity level calculation will be carried out to analyze whether Traveloka's services are good enough to carry out service operations in the community. This research uses the ITIL V3 framework to analyze Traveloka services, especially in the Service Operation domain, which consists of 5 subdomains, namely the maturity level in the Event Management subdomain gets a value of 4.41, the maturity level in the Incident Management subdomain gets a value of 4.22, then for the Problem subdomain Management got a maturity level of 4.17, then for the Request Fulfillment subdomain the maturity level got a value of 4.21 and finally for the Access Management subdomain it got a maturity level of 4.30. So it can be seen that based on the results of the maturity level calculation it can be stated that all subdomains are at the Managed Level.
Penerapan Algoritma Apriori Dalam Memprediksi Penjualan Sepeda Motor

Currently, companies operating in the motorbike sector are experiencing a decline in sales of spare part products and are not appropriate in determining the promotional strategies given to customers. A lot of transaction data is used as a reference for selling products at capital prices which only results in small profits. If it is still not sold, the incoming goods are delayed because the capital has not been returned. Therefore, a system is needed to process information data more quickly and precisely in predicting motorbike sales patterns using a priori algorithm data mining applications. The results of calculations using the a priori algorithm show that if a consumer buys a Yamaha lower arm and tires then the support value = 23.33 and the confidence value = 77.78 and if the consumer buys a Yamaha lower arm and AC filter then the support value = 26.67 and the confidence value = 72.72. The research objective is to predict and analyze motorbike sales patterns implemented on a desktop-based application. This is to make it easier to analyze the competitiveness of the best-selling motorcycle products simultaneously. As a recommendation for decision makers to improve marketing and promotion of better motorbike products.
Penerapan Data Mining Menggunakan Algoritma K-Means Untuk Clustering Perokok Usia Lebih dari 15 Tahun

Smoking is an activity that can have a bad impact on health, both for yourself and for others. This is because there are various kinds of ingredients that are dangerous to health, there are 4000 types of chemicals found in cigarettes, starting from nicotine and other substances that can cause cancer in humans. The dataset obtained from BPS (Central Statistics Agency) can be utilized by using K-Means Clustering to determine the grouping of smokers aged more than 15 years in each region. The grouping of smokers aged over 15 years can be seen through 3 clusters, Cluster 1 is the highest level of smoking in 10 provinces out of 34 provinces studied, Cluster 2 is the medium level with 15 provinces out of 34 provinces studied, and Cluster 3 is the lowest level. with 9 Provinces.
An investigation into common errors in Vietnamese-English translation made by college freshmen: A case study at Foreign Trade University - Ho Chi Minh Campus

This study aims to investigate students’ common errors in Vietnamese-English translation. For the objectives, 70 first-year students at Foreign Trade University – Ho Chi Minh campus, were invited to participate in this study. To identify students’ errors in Vietnamese-English translation, the participants were asked to complete five weekly assignments. The results revealed that students made grammatical, lexical, and spelling errors. The causes of these observed errors were also indicated, which included the difference between English and Vietnamese languages, inadequate culture background, students’ insufficient linguistic competence in English language and Vietnamese language, lack of cultural background knowledge, students’ inappropriate translation strategies, interference of Vietnamese, misunderstanding, and students’ carelessness. In addition, some suggestions were offered in the light of the findings identified in the study to help students improve their translation ability.
Creation a Blockchain-based Product Qualification System for E-Marketplace using Practical Byzantine Fault Tolerance Algorithm

An indicator of e-marketplace effectiveness is to facilitate transparent transactions between sellers and buyers by offering good products and adequate infrastructure to handle system requirements. A good product must be in accordance with the product qualification which consists of the classification of feasibility or not, and the benefits of the product. However, this often has problems including those caused by frequent problematic system conditions, non-transparent product qualifications, undistributed data, human error until data security. The researcher proposes the creation of a product qualification system for e-marketplace using blockchain technology. The product qualification system consists of data verification and validation carried out by stakeholders involved in the decentralized network. Transactions that have been executed and validated will be stored in the distributed ledger. The focus of this research is the implementation of blockchain that is allowed to use the PBFT algorithm on product qualification records in the e-marketplace. The purpose of this research is to create a blockchain-based product qualification system for e-marketplace that is transparent and immutable and the successful performance of the system in information storage and management security. The results show the creation of a web-based apps product qualification system that implements a blockchain using Hyperledger Fabric and the performance obtained through system testing and data validation testing.
Penerapan Algoritma C.45 Dalam Pengklasiﬁkasian Data Penjualan Gerai Makanan Cepat Saji Berbasis Website

With the development of technology, there are many methods that can be used to analyze various kinds of problems, both in the world of education, social and even the business world. One method that can be used is the data mining method. Fast food is one example of a business that is being built by many people today, especially in the city of Batam. With so many fast food outlets in the city of Batam, this study aims to classify the types of food that are in demand and not in demand in the city of Batam. To assist the writer in classifying the best-selling and not-selling food types, in this study the authors used the data mining method, namely applying the C.45 Algorithm approach. Apart from using the C.45 Algorithm to test the calculation results, the author uses a website-based information system. From the research that has been carried out, the results obtained are that the best-selling food for children is the Original Burger (BO) and for adults the best-selling type of food is Kebab (K), while the less popular type of food for all ages is Burger Crispy.
Pemanfaatan Teknologi Augmented Reality Sebagai Media Navigasi Berbasis Aplikasi Android

The navigation media on the Universitas Teknologi Yogyakarta campus environment currently still uses conventional guidance media in the form of printed pictures and mock-up plans, so it is considered ineffective and inefficient in providing directions for students, staff, or campus visitors, especially in the outdoor areas where signage is rarely installed. This research aims to assist 3D virtual navigation services by utilizing augmented reality technology based on longitude and latitude coordinate point data of an area, which is implemented in the form of an Android mobile application. The research method used is the case study method, with a qualitative approach. This application development model uses the waterfall model. The stages used in this research include planning, data collection, analysis, design, implementation, and application testing using Black box testing with the test case method, which produces application testing that descriptively explains the application work process. Application test results show that route search navigation, information features, and application menus work well. The combination of augmented reality technology and a global positioning system can be implemented to recognize various navigation routes based on longitude and latitude numerical values very well.
Rancang Bangun Aplikasi Petani Sawah Sugita Menggunakan Algoritma Dijkstra Untuk Mempermudah Penjualan Hasil Pertanian

In general, the buyers of rice field produce are often middlemen who offer the lowest possible prices to the farmers. This is due to the lengthy distribution chain that causes a significant price difference between the low prices paid to farmers for their rice and the high prices consumers pay for milled rice. Therefore, in an effort to cut out the distribution chain that disadvantages both farmers and consumers, the idea of developing the Petani Sawah Sugita mobile-based application emerged. This application enables farmers to sell their rice and milled rice directly to consumers at prices that benefit both parties. The research was conducted by applying the four main stages of the SDLC. The requirements analysis phase involved observations and direct interviews with farmers in one of the rice fields located in the Ciasuk area, Tangerang Regency, Banten. The design phase was carried out by creating UML diagrams. The implementation phase was done with the assistance of Android Studio, resulting in the Sugita Rice Field Farmer mobile application. The application's standout feature is the location search for farmers or nearest products from users, built using the Dijkstra algorithm. The system testing phase was performed using black box testing. The test results showed that 105 out of 114 test cases, or 92.1%, met the expected outcomes. In conclusion, the development of the Sugita Rice Field Farmer application proceeded well and was successfully implemented. This application can help reduce product delivery costs and foster relationships between users and farmers. Furthermore, it simplifies the process for farmers to market their agricultural products to the wider community and provides valuable experience for farmers to stay up-to-date and leverage existing technology advancements.
Sistem Informasi Penilaian Prestasi Kerja Pegawai dengan Metode Pengembang Perangkat Lunak Model Waterfall

Providing an assessment of employee work performance is a method for evaluating their competence with the aim of development to produce competitive employees. A Civil Servant (PNS) who achieves good (high) work performance should get a reward (compensation) that is comparable. It aims to motivate and reward civil servants for improving performance. However, some opportunities can turn into threats if they are not anticipated, such as negative responses from the public if the government is unable to improve the quality of its employees' performance. Inaccurate and ineffective assessments can cause the process of assessing the performance and quality of State Civil Apparatus (ASN) to be inaccurate and inappropriate. Therefore, an assessment system is needed that is relevant, practical, reliable and acceptable so that the assessment results are more accurate good and useful for employees and personnel administration at the Pontianak Fisheries Training and Extension Center (BP3). This system refers to the Waterfall model, where the progress of a process is considered to flow continuously like a waterfall. In the waterfall model, each step must be sequential and you cannot proceed to the next step but must complete the first step then proceed to the second step, and so on. With the system that has been built, the employee performance appraisal process can be well-documented and more transparent. The results of testing using the black box testing method showed that the system functionality could meet all the expected requirement specifications.
Determination of The Water Quality Status of The Kalimalang River In Telaga Murni Recidence, Bekasi District

The behavior of the people around the riverbanks, such as throwing garbage directly into the river body, and the river's proximity to steel-producing companies impacts river water quality. This research aims to determine the Kalimalang River water quality status in Telaga Murni housing. The sampling method used in this study is the Grab Sampling method with a combination of Purposive Sampling, which is taken from the most polluted points so that it is expected to obtain river water samples that best follow the conditions of river water quality from upstream to downstream. From the results of laboratory tests &amp; calculations using the Storet method and Pollution Index, river water in Telaga Murni housing is classified as heavily polluted. The Phenol and Total Coliform values exceed the quality standards indicating contamination from domestic and industrial wastewater.
Komparasi Metode Perhitungan Jarak K-Means Paling Baik Terhadap Pembentukan Pola Kunjungan Wisatawan Mancanegara

Understanding patterns among foreign tourists is an urgent matter. These patterns can become knowledge that helps in making better decisions because they are data-driven. The pattern to be elaborated on is regarding the clustering of visits by foreign tourists to tourist destinations in Jakarta. Data mining is an approach that extracts knowledge patterns from a dataset. K-Means is one of the data mining algorithms used for clustering data, where data is grouped based on similarity in features and attributes. This study compares the Euclidean Distance, Manhattan Distance, and Haversine Distance methods to obtain more representative data clusters for the datasets. The datasets in this study are not normally distributed due to outlier data; hence, the DBSCAN algorithm is used for improvement without removing or cutting the data, as it can result in a significant amount of missing values that could affect information that does not align with empirical facts. In this study, 5 clusters were created based on elbow calculation results. The K-Means cluster testing in Euclidean distance yielded a Silhouette Score of 0.36, Inertia of 0.86, and Davies-Bouldin Index of 2.39. The Manhattan method resulted in a Silhouette Score of 0.65, Inertia of 1.46, and Davies-Bouldin Index of 0.47. Meanwhile, applying the Haversine method resulted in a Silhouette Score of 0.36, Inertia of 0.03, and a value of 2.39 for the Davies-Bouldin Index.
Comparison of K-Means and K-Medoid Algorithms in Classifying Village Status (Case Study: Gorontalo Province)

In the national development process, the village occupies a very important position. This is because it is the smallest government structure and has direct contact with the community. Seeing the importance of its role in national development, one of which is Gorontalo Province, based on directions from the central government, is trying to implement the Village Fund Allocation (ADD) policy for all villages in Gorontalo Province. In distributing the allocation of funds, it is necessary to map the status of the Village to find out the amount that must be given. This test uses the average execution time and the Davies Bouldin Index (DBI). After testing it is known that the K-Medoid Algorithm has a better DBI value than the K-Means Algorithm with the DBI value of the K-Medoid Algorithm being 0.050. On the other hand, the K-Means Algorithm has a better average execution time than the K-Medoid Algorithm, where the average execution time is 1 second.
Pengembangan Sistem Monitoring Pemeriksaan Pasien di Instalasi Kedokteran Nuklir Berbasis Open-Source ERP dengan Metode Quickstart

As a national reference center for nuclear medicine services, the general hospital in the Bandung area is required to consistently enhance the quality of its services, including improving patient care and reducing errors that occur during the patient examination process. Currently, the nuclear medicine installation department offers 45 types of examination services, resulting in a high volume of daily patient examinations. This situation presents a distinct challenge for the nuclear medicine installation department as it lacks a system for monitoring patient examinations. The issue of data and information integration becomes crucial in patient examination activities, particularly because a lack of integration can lead to suboptimal examination reporting processes. This research aims to develop an monitoring system for patient examination activities using the Odoo application, employing the Quickstart development method. The primary focus of this study is on the integration of data and information in monitoring patient examinations. Each patient examination data can be input into the Odoo application, centralizing the storage of data and information. This research aims to offer a solution to the challenges faced by integrating business processes with patient examination monitoring systems. It also proposes data and information integration within patient examination activities and other departments within the nuclear medicine installation. This integration will result in a well-structured reporting system that is easy to generate, providing various forms of patient examination reports as an outcome.
Sistem Pendukung Keputusan Untuk Menetukan Jenis Perawatan Wajah Menggunakan Metode AHP dan SAW

Currently, facial care is highly desired by society, especially for women in this world. Problems with the face can be caused by unsuitable care products used because they don't know the problems with each individual face. One of the treatments that can be done is at the Putri Ms Glow store, where we can ask for solutions or good consultations in dealing with problems on each patient's face. Given these problems, it is necessary to create or design a web-based Decision Support System using the AHP and SAW methods. The existence of the AHP and SAW methods can be expressed as a comparison that can make it easier to calculate a ranking weight between alternatives. In order to make it easier for patients to carry out consultations or treatment, the design of this web application was carried out using a system that was designed or a system that is currently running, where data is obtained from the results of observations or interviews in order to determine criteria and alternatives in making decisions for Putri Ms Glow. After the data is collected, weighting calculations are carried out from AHP and after that they are ranked using SAW to determine which patients are prioritized first. Based on the results of research and calculations that have been tested using the AHP method, it helps weight alternatives and criteria with a weight scale of 1-9 , after the weighting was carried out, the ranking was carried out using the SAW method to get the final score, rank 1 was obtained by Resti with a final score of 1.0067 and rank 15 was obtained by Suci with a final score of 0.5633. The before, it is the priority for Resti to get treatment first.
Memprediksi Kualitas Produk Inspeksi Dalam Meminimalisasi Resiko Produk Ng Meggunakan Algoritma Regresi Linier

Predicting the product is a form of analyzing data, predicting the product is an important factor that determines the smooth running of the product. Utilization of product and defect data can be used in carrying out the process of data mining and modeling stages to predict the number of product defects at one time. The application of the simple Linear Regression algorithm equation model can be implemented where the results also provide a new insight for the prediction needs of the number of product defects. The simple Linear Regression equation model after comparison with actual calculation results (observations) and also with the Rapid Miner application in general shows similar results. Evaluation and testing of the RMSE value was also obtained when evaluating the applied linear regression model, with an RMSE value of 0.984 with a standard deviation of +- 0.0
Prediksi Penyakit Diabetes Untuk Pencegahan Dini Dengan Metode Regresi Linear

Estimation is a method in which we can estimate the population value by using the sample value and which can model an equation to calculate the estimate i.e. a linear regression algorithm attempts to model the relationship between two variables by fitting a linear equation to observe the data. The application of a simple Linear Regression algorithm model can be implemented well and is able to provide a new insight for the need for predictions about the condition of diabetes data quality in controlling sugar levels in the body. Predictions of diabetes in the future can be known through the use of datasets using a prediction method approach through structured stages in analyzing the data used to produce an RSME value when evaluating a model of 0.000 +/- 0.000. Performance testing of the models and algorithms used in the evaluation can produce a picture that is relevant to the scenario being modeled. The RMSE value is obtained when evaluating the model performance of 0.000 +/- 0.000 through the RapidMiner Studio application.
Klasterisasi Stok Produk Retail Untuk Menetukan Pergerakan Kebutuhan Konsumen Dengan Algoritma K-Means

− Retail product clustering is a product arrangement that is adjusted to the flow of placement or this layout is more suitable for product placement according to standards. Utilization of existing data through the clustering method approach can be applied in analyzing product grouping of data on availability and inventory of goods in warehouses so that it can provide knowledge and information. The clustering method is processed using the K-Means algorithm, where the results also show a new insight, namely grouping products based on 3 clusters. Cluster 1 is a product category with low availability or Low, namely 939 out of 1000 availability categories based on the number of products tested, then cluster 2 is a product category with medium or Medium availability, namely 51 out of 1000 availability categories based on the number of products tested, and finally cluster 3 is a product category with fairly high availability or High, namely 10 out of 100 availability categories based on the number of products tested. Tests using Rapid Miner tools can also produce similar insights, namely that each cluster has cluster group members according to manual calculations such as Cluster_0 in Rapid Miner has 51 cluster members representing the Medium cluster, Cluster_1 has 939 cluster group members representing the Low cluster, and Cluster_2 has 10 cluster members corresponding to the cluster representation High.