Building of Informatics, Technology and Science
Building of Informatics, Technology and Science (BITS) is an open access media in publishing scientific articles that contain the results of research in information technology and computers. Paper that enters this journal will be checked for plagiarism and peer-rewiew first to maintain its quality. This journal is managed by Forum Kerjasama Pendidikan Tinggi (FKPT) published 2 times a year in Juni and Desember. The existence of this journal is expected to develop research and make a real contribution in improving research resources in the field of information technology and computers.
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<![CDATA[Method comparison of Naïve Bayes, Logistic Regression, and SVM for Analyzing Movie Reviews ]]>
<![CDATA[Muhammad Maulidan Aziz]]>;
<![CDATA[Mahendra Dwifebri Purbalaksono]]>;
<![CDATA[Adiwijaya Adiwijaya]]>
<![CDATA[ Building of Informatics, Technology and Science (BITS) Vol 4 No 4 (2023): Maret 2023 ]]>
Publisher : <![CDATA[Forum Kerjasama Pendidikan Tinggi ]]>
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DOI: 10.47065/bits.v4i4.2644
<![CDATA[A film can be categorized as a successful film based on the reviews given by the critics. The reviews can range from professional critics to public reviews from the general audience. Due to a large number of reviews and opinions on a film, this study aims to create a sentiment analysis model and compare the methods used to analyze datasets from a movie review. Sentiment Analysis is a method for studying and analyzing opinions, then classifying these opinions into several classes. This research will use the Naïve Bayes method, Logistic Regression, and Support Vector Machine (SVM) to analyze film review data. The film review dataset used is a collection of film reviews taken from the Rotten Tomatoes website and will be pre-processed before implementing the Naïve Bayes, Logistic Regression, and SVM methods. The SVM classifier with 80:20 data splitting has the best performance, with a result of 99.4% accuracy score and 93.5% F1 score.]]>
<![CDATA[Optimization in Time and Score using IID Algorithm for K-Modes Clustering ]]>
<![CDATA[Farah Yulianti]]>;
<![CDATA[Tjong Wan Sen]]>
<![CDATA[ Building of Informatics, Technology and Science (BITS) Vol 4 No 4 (2023): Maret 2023 ]]>
Publisher : <![CDATA[Forum Kerjasama Pendidikan Tinggi ]]>
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DOI: 10.47065/bits.v4i4.2791
<![CDATA[Nowadays, there are numerous methods for analyzing data, one of which is cluster analysis. Because most practical data in today's analysis contains categorical attributes, categorical data clustering has recently received a lot of attention. To cluster categorical data, unsupervised machine learning techniques, which used frequency-based method, such as K-Mode’s clustering are used. The K-Modes algorithm takes advantage of the differences between the data points (total mis-matches or dissimilarities). The lower the dissimilarities, the more similar the data points, and thus the better the cluster. This paper aims to improve K-Mode’s clustering performance by incorporating the intercluster and intracluster dissimilari-ty measure, or IID measure, into the K-Modes algorithm rather than just using the standard simple-matching method to increase the algorithm's accuracy and execution time. This combined algorithm improves accuracy and execution time of the K-Modes algorithm. As a result, this algorithm can be used as an alternative to better cluster categorical data.]]>
<![CDATA[Penerapan Forecasting Menggunakan Metode Time Series Untuk Menentukan Proyeksi Sales di Perusahaan Manufacturing Furniture ]]>
<![CDATA[Lukito Angga Prasakti]]>;
<![CDATA[Christina Juliane]]>
<![CDATA[ Building of Informatics, Technology and Science (BITS) Vol 4 No 4 (2023): Maret 2023 ]]>
Publisher : <![CDATA[Forum Kerjasama Pendidikan Tinggi ]]>
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DOI: 10.47065/bits.v4i4.2802
<![CDATA[The large population certainly encourages companies, including manufacturing companies, to continue to develop their production both in terms of quality and quantity, especially since the number of companies with the same focus is quite large. This is because, every certain company wants to get a lot of profit and minimal consumer or customer complaints. One way that is considered to be able to overcome this is by carrying out company policy referring to forecasting product sales in the future. Therefore, researchers want to find out more about the application of forecasting to determine monthly sales projections for the following year at a Furniture Manufacturing Company. The aim is to determine the role of forecasting in making policies on the company's production at a later time by considering sales projections based on the company's forecasting results. The method used is time series by collecting data through documentation at the regular local market in 2022 to be precise 12 months. After the data is collected, it will be analyzed in depth so that it is known from the research results that careful forecasting will produce forecasts that are not far from reality and can help in calculating sales projections for furniture manufacturing companies at a later time, with a MAPE value of 0.06]]>
<![CDATA[Penerapan Metode MOOSRA dan MOORA dalam Keputusan Pemilihan Produk Asuransi Terbaik ]]>
<![CDATA[Andik Adi Suryanto]]>;
<![CDATA[Sitti Nur Alam]]>;
<![CDATA[Warkianto Widjaja]]>;
<![CDATA[Hamid Wijaya]]>;
<![CDATA[Iwan Adhicandra]]>
<![CDATA[ Building of Informatics, Technology and Science (BITS) Vol 4 No 4 (2023): Maret 2023 ]]>
Publisher : <![CDATA[Forum Kerjasama Pendidikan Tinggi ]]>
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DOI: 10.47065/bits.v4i4.2938
<![CDATA[At present, public opinion regarding the selection of insurance products is very low because people still do not understand enough to insure themselves against a product that will guarantee their necessities of life. Especially now that there are so many insurance products out there, it's likely that people don't want to register for insurance. Therefore, people must be careful in choosing an insurance product so that it fits what they want. The Decision Support System is a computerized system and is designed to assist management in making decisions to solve semi-structured and unstructured problems so that the decision-making process can be of higher quality. This application that will be made is an application that is guided by the MOORA method. Therefore, an application that is guided by the MOORA method is very suitable for calculating insurance product selection. From the results of our research we conducted the MOOSRA and MOORA methods for selecting insurance products easier and more precise than the manual work method. applying the MOORA method produces an alternative A5, namely Prudential with a value of 0.217 as the best alternative.]]>
<![CDATA[Text Classification of Indonesian Translated Hadith Using XGBoost Model and Chi-Square Feature Selection ]]>
<![CDATA[Dita Julaika Putri]]>;
<![CDATA[Mahendra Dwifebri]]>;
<![CDATA[Adiwijaya Adiwijaya]]>
<![CDATA[ Building of Informatics, Technology and Science (BITS) Vol 4 No 4 (2023): Maret 2023 ]]>
Publisher : <![CDATA[Forum Kerjasama Pendidikan Tinggi ]]>
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DOI: 10.47065/bits.v4i4.2944
<![CDATA[Aside from the Holy Qur'an, Hadith is indeed a life guide that every Muslims in this world must follow. The technology for classifying texts and sentences, including categorizing hadiths, is evolving in tandem with the advancement of the times. The model used to perform classification has also been developed and optimized such as the use of the XGBoost algorithm which is more optimized than the previous tree algorithm. This can also make it easier for us as Muslims to study hadiths by categorizing them according to recommendations, prohibitions, and information. This study conducted text classification of Indonesian translations of hadith texts based on recommendations, prohibitions, and information using the XGBoost algorithm, TF-IDF for its feature extraction, and Chi-Square for its feature selection. In this study, experiments were carried out by changing the order of the preprocessing process for the stopword removal and stemming parts, performing the classification process with and without using chi-square as a feature selection, and adding parameter value during the modeling process with XGBoost and the highest final results obtained were 79% for accuracy, 79% for precision, 78% for recall and 78% for F1-score.]]>
<![CDATA[Conversational Recommender System based on Functional Requirement using Knowledge Graph for Building Personal Computer ]]>
<![CDATA[Rafi Rizkya Aryanta]]>;
<![CDATA[Z. K. A Baizal]]>
<![CDATA[ Building of Informatics, Technology and Science (BITS) Vol 4 No 4 (2023): Maret 2023 ]]>
Publisher : <![CDATA[Forum Kerjasama Pendidikan Tinggi ]]>
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DOI: 10.47065/bits.v4i4.2978
<![CDATA[When a person wants to build a personal computer, this person needs to browse many kinds of computer components. Besides that, this person needs to consider the compatibility between hardware and an affordable price. This will be a problem for people who are still unfamiliar with the computer, due to their lack of understanding of how compatibility between computer components works and the time-consuming nature of market research. To deal with this problem, the recommender system will assist in finding and matching compatibility efficiently based on the functional requirements of the user. The recommender system will issue various products based on the preferences and interests of the user, but some recommendations still need to be checked for compatibility. With the help of developing a Conversational Recommender System by utilizing the Knowledge Graph, it will be easier to construct the relationship between component compatibility. We propose this research by using Knowledge Graph as alternative from ontology to build Conversational Recommender system in Building Personal Computer. This research will involve the user to prove whether the recommendations from this system meet the needs and accuracy of the recommendations requested. The main results of this study will issue a recommendation for the development of personal computers by considering compatibility using the Conversational Recommender System using the Knowledge Graph approach.]]>
<![CDATA[Mask Detection on Motorcyclists Using YOLOv4 ]]>
<![CDATA[Salma Salsabila Firdauz]]>;
<![CDATA[Ema Rachmawati]]>;
<![CDATA[Mahmud Dwi Sulistiyo]]>
<![CDATA[ Building of Informatics, Technology and Science (BITS) Vol 4 No 4 (2023): Maret 2023 ]]>
Publisher : <![CDATA[Forum Kerjasama Pendidikan Tinggi ]]>
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DOI: 10.47065/bits.v4i4.2980
<![CDATA[The use of mask is a mandatory for everyone in the pandemic regulation to prevent the spread of COVID-19 infection. This becomes a pandemic regulation for everyone, especially in public places like in traffic situation, such as pedestrian and motorcyclists. However, many motorcyclists ignore this rule or do not use the mask properly, let alone they have high risk in being infected by the virus; Thus, a computer vision-based solution is required to help monitoring it. This study aims to built a system to automatically detect the use of mask on motorcyclists. Here, we propose a YOLOv4 model, one of YOLO variants, which is popular in the object detection task and featured with a considerably high speed in real-time situation. This study also implements domain adaptation to discuss the object detection performances. Based on the experimental results in various scenarios, our model obtained average accuracy of 78.3% and IoU of 64.8% for class with_mask, average accuracy of 78.4% and IoU of 56.3% for class without_mask, and average accuracy of 87% and IoU of 55.5% for class incorrect_mask]]>
<![CDATA[Sign Language Translator Based on Raspberry Pi Camera Using The Haar Cascade Classifier Method ]]>
<![CDATA[Gempur Bayu Aji]]>;
<![CDATA[Fazmah Arif Yulianto]]>;
<![CDATA[Andrian Rakhmatsyah]]>
<![CDATA[ Building of Informatics, Technology and Science (BITS) Vol 4 No 4 (2023): Maret 2023 ]]>
Publisher : <![CDATA[Forum Kerjasama Pendidikan Tinggi ]]>
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DOI: 10.47065/bits.v4i4.2990
<![CDATA[Sign language is the main tool of communication for people with hearing impairments. Communication is very limited and difficult to understand between normal people who do not know sign language, so an interpreter is needed. Where not everyone, even a few normal people, learns sign language, especially the Indonesian Sign Language System (SIBI). Motion Detection is an important subject in the field of computer vision, which is used by many systems. Today's Internet of Things is very helpful and facilitates daily human activities. An internet network allows a device to be controlled from a considerable distance. This study described a sign language translator tool for the deaf and speech impaired using a raspberry-pi camera and displayed it on the other device monitor. This system was built using the Python programming language and the OpenCV Library. The system is using Haar Cascade Classifier algorithm, where there will be data on all hand shapes based on the letters to be translated. This application uses the OpenCV library and Visual Studio Code IDE software connected to the Raspberry Pi Camera. The publisher will send data to other devices using the MQTT Broker to connect and display detection results to other device monitors wirelessly using a local network. The research was conducted at various distances between the hand and the webcam, from 30cm to 150cm. The research results using the Haar Cascade Classifier method to detect sign language obtained an accuracy of 82%.]]>
<![CDATA[Perbandingan Algoritma K-Means dan Algoritma K-Medoids Pada Kasus Covid-19 di Indonesia ]]>
<![CDATA[Novianti Puspitasari]]>;
<![CDATA[Gidion Lempas]]>;
<![CDATA[Hamdani Hamdani]]>;
<![CDATA[Haviluddin Haviuddin]]>;
<![CDATA[Anindita Septiarini]]>
<![CDATA[ Building of Informatics, Technology and Science (BITS) Vol 4 No 4 (2023): Maret 2023 ]]>
Publisher : <![CDATA[Forum Kerjasama Pendidikan Tinggi ]]>
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DOI: 10.47065/bits.v4i4.2994
<![CDATA[Analyzing Covid-19 data has been conducted in many types of research, but research on classifying each case from Covid-19 data in all provinces in Indonesia has yet to be available. This study uses two clustering algorithms, namely K-Means and K-Medoids, to classify positive cases recovered and died in the Covid-19 data into three clusters, namely low, medium and high. The research data is Covid-19 case data in all provinces in Indonesia from 2020 to 2021. In the clustering calculations, the three distance methods used in this study are the Chebyshev Distance, Manhattan Distance, and Euclidean Distance. Based on the Silhouette Coefficient test results for the three distance calculation methods, it was found that Manhattan Distance is the best distance calculation method for K-Means and K-Medoids. Furthermore, the results of testing the Sum Squared Error (SSE), Silhouette Coefficient (SC) and Davies Index Bouldin (DBI) methods for the resulting clusters show that the value generated by the K-Means algorithm is higher in the SC and DBI methods. This result is evidenced by the SC value of 0.838; 0.838; and 0.925 in positive cases, recovered and died. While the DBI value is 0.305 for positive cases, 0.295 for recovered cases and 1.569 for dead cases. Based on these values, it proves that K-Means is superior in grouping and placing clusters compared to K-Medoids.]]>
<![CDATA[Penerapan Metode MABAC dengan Pembobotan ROC Dalam Sistem Pendukung Keputusan Pemilihan Pengajar dengan Kinerja Terbaik ]]>
<![CDATA[Kraugusteeliana Kraugusteeliana]]>;
<![CDATA[Agustian Zen]]>;
<![CDATA[Suryani Suryani]]>;
<![CDATA[Sitti Nur Alam]]>;
<![CDATA[Edy Winarno]]>
<![CDATA[ Building of Informatics, Technology and Science (BITS) Vol 4 No 4 (2023): Maret 2023 ]]>
Publisher : <![CDATA[Forum Kerjasama Pendidikan Tinggi ]]>
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DOI: 10.47065/bits.v4i4.3000
<![CDATA[Selection of the best teacher is one of the problems in a decision making according to semi-structured criteria. In this research, the decision support system explains how the process of selecting alternative teachers who have the best performance in elementary schools applies the MABAC method and weights it using the Rank Order Centroid (ROC) method. The use of this method can solve the problem of determining the best teacher that occurs in elementary schools. The final result of completing the method will produce the highest ranking value which will be determined to be the highest alternative. The data used in this study were 10 alternative teacher data using 5 criteria, resulting in 1 highest ranking of the 10 alternatives obtained by alternative 1 named Servin Manullang with a value of 0.6086 as a recommendation for the teacher with the best performance]]>
