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Showing 136 articles found for "Platforms"

MACHINE LEARNING CONTENT-BASED FILTERING WOMEN EMPOWERING RECOMMENDATIONS ON YOUTUBE

Yuliana, Yuliana, Mira, Mira, Hari Kristianto, Aloysius
Abstract: Abstract: YouTube is one of the most popular video streaming platforms, but it has constraints that can cause problems when clients have difficulty finding content according to their wishes. The main objective of this study… udy is to increase user capacity in viewing content specifically in the field of women's empowerment. By using content-based filtering techniques, the system will analyze user preferences and interests through recommendations for women's empowerment content. The data source is via the YouTube API and is analyzed using PHP programming content-based filtering techniques. The system's recommendations provide a list of women's empowerment content with a user request display. The results of the research evaluation obtained a precision value of 62%, meaning that the recommendations match the topic being searched for, namely women's empowerment. The recall value of 84% indicates that the system has succeeded in finding relations from the database. The f1-score value of 72% indicates that there is a balance between precision and recall, meaning that a system is needed that is not only accurate but also complete. While the cosine value shows a score of 0.7071 approaching the maximum value (1.0). The recommendation of the content-based filtering method produces quite effective women's empowerment content. Keywords: content-based filtering, recommendations, women Empowerment, youtube  

EVALUATION OF HYBRID MOVIE RECOMMENDATION SYSTEM BASED ON NEURAL NETWORKS

Widjaja, William, Robert, Johanes Terang Kita Perangin - Angin
Abstract: Abstract: Recommendation systems are becoming increasingly important with the growth of streaming platforms. The purpose of this study is to compare the performance of Content-Based Filtering, Neural Collaborative Filtering,… ing, and a combination of both in a movie recommendation system. The method used in this study involves retrieving movie details from the TMDB API and ratings from the MovieLens 32M Dataset (2010-2023). Each model's performance is evaluated using evaluation metrics such as RMSE and MAE. The results of this study indicate that Neural Collaborative Filtering achieves the best prediction performance (RMSE = 0.785423, MAE = 0.581262), followed by the hybrid model (RMSE = 0.800863, MAE = 0.660872), while Content-Based Filtering produces low performance and limits the capabilities of the hybrid model. In conclusion, these findings highlight the superiority of latent feature-based models such as NCF that learn directly from user interaction patterns over content-based approaches in the context of modern recommendation systems. Keywords: content-based filtering; hybrid filtering; movie recommendation; neural collaborative filtering.   Abstrak: Sistem rekomendasi menjadi semakin penting seiring berkembangnya platform streaming. Tujuan dari penelitian ini adalah membandingkan kinerja Content-Based Filtering, Neural Collaborative Filtering dan kombinasi keduanya dalam sistem rekomendasi film. Metode yang digunakan dalam penelitian ini melibatkan pengambilan detail film dari TMDB API dan rating dari dataset MovieLens 32M Dataset (2010-2023). Setiap peforma model dievaluasi dengan menggunakan metrik evaluasi seperti RMSE dan MAE. Hasil dari penelitian ini menunjukkan bahwa Neural Collaborative Filtering mencapai kinerja prediksi terbaik (RMSE = 0.785423, MAE = 0.581262), diikuti oleh model hybrid (RMSE = 0.800863, MAE = 0.660872), sementara Content-Based Filtering menghasilkankan peforma yang rendah dan membatasi kemampuan model hybrid. Kesimpulannya, penelitian ini menyoroti superiotas model berbasis latent feature seperti NCF yang belajar langsung dari pola interaksi pengguna dibandingkan pendekatan berbasis konten dalam konteks sistem rekomendasi modern. Kata kunci: content-based filtering; hybrid filtering; neural collaborative filtering; rekomendasi film.

ANALYSIS OF THE QUALITY OF "ONLINE EQUIVALENT" E-LEARNING USING WEBQUAL 4.0 AND IPA METHODS

Rahman, Taufik, Azizah, Alfi
Abstract: Abstract: The use of e-learning in non-formal education is increasingly important to support the improvement of access to learning, one of which is through the online platform. This study aims to analyze the quality of online… nline services using WebQual 4.0 and Im-portance Performance Analysis (IPA) methods to evaluate the suitability between user expectations and perceptions. The research method used a quantitative approach by distributing questionnaires to active users, then analyzed using the WebQual Index to measure the overall quality of the system as well as the IPA to determine improvement priorities. The results showed that the quality of SeTARA Online was relatively good with a WebQual Index value of 0.798. However, there is still a gap between user expectations and satisfaction with a negative gap value of -0.238. The IPA analysis identified indicators in Quadrant I as priority improvements, especially in the aspects of service interaction and information presentation. These findings underscore the need for continuous development of features and technical support to optimize the user experience. The conclusion of this study suggests that there should be improvements in priority indicators to increase user satisfaction, as well as strengthen the effectiveness of online learning. Advanced research can expand variables, compare with other platforms, and combine quantitative and qualitative analysis methods for more comprehensive results.   Keywords: e-learning; importance performance analysis; quality of service; online equivalent; webqual 4.0

SENTIMENT ANALYSIS OF PEGIPEGI.COM ON GOOGLE PLAYSTORE WITH NAÏVE BAYES ALGORITHM

Hardian, Riski, Oktaviana, Luzi Dwi, Hamdi, Aulia
Abstract: Abstract: Today, many users use online platforms rather than offline platforms for ticket bookings, involving a wide range of services such as flights, hotels, trains, buses, and entertainment. PegiPegi.com, as one of the… e fastest growing online travel agencies in Indonesia, demonstrates success by understanding the value of technology and maintaining strong partnerships. Users of this platform often provide reviews, viewing user reviews can be done manually but this will have a less effective impact, so it needs to be done automatically with sentiment analysis. This research the Naïve Bayes method in sentiment analysis of PegiPegi.com reviews, with a focus on understanding customer satisfaction and service improvement. By combining these approaches, this research contributes to a deeper understanding of user responses to OTA services and presents the evaluation results of the Multinomial Naive Bayes classification model with an accuracy rate of 89.5%. The high precision in the Negative class demonstrates the model's ability to identify negative reviews. However, there are challenges in classifying the Neutral class, indicating the potential for further improvement. Nevertheless, the F1 score of 0.522 reflects a good balance between overall precision, recall so it can be concluded the naïve bayes algorithm is successful for performing sentiment analysis. Keywords: Sentiment analysis; naïve bayes algorithm; pegipegi.com; playstore     Abstract: Saat ini banyak pengguna platform online dibandingkan offline untuk pemesanan tiket, yang melibatkan berbagai layanan seperti penerbangan, hotel, kereta api, bus, dan hiburan. PegiPegi.com, sebagai salah satu agen perjalanan online yang berkembang pesat di Indonesia, menunjukkan keberhasilan dengan memahami nilai teknologi dan mempertahankan kemitraan yang kuat. Pengguna platform ini sering memberikan ulasan, melihat ulasan pengguna bisa saja dilakukan secara manual tetapi hal ini akan memberikan dampak yang kurang efektif, sehingga perlu dilakukan secara otomatis dengan analisis sentiment. Penelitian ini bertujuan untuk menerapkan metode klasifikasi Naïve Bayes dalam analisis sentimen ulasan PegiPegi.com, dengan fokus pada pemahaman kepuasan pelanggan dan peningkatan layanan. Dengan menggabungkan pendekatan ini, penelitian ini berkontribusi pada pemahaman yang lebih dalam tentang tanggapan pengguna terhadap layanan OTA dan menyajikan hasil evaluasi model klasifikasi Multinomial Naive Bayes dengan tingkat akurasi 89,5%. Presisi tinggi di kelas Negatif menunjukkan kemampuan model untuk mengidentifikasi ulasan negatif. Namun, ada tantangan dalam mengklasifikasikan kelas Netral, menunjukkan potensi untuk perbaikan lebih lanjut. Namun demikian, skor F1 0,522 mencerminkan keseimbangan yang baik antara presisi keseluruhan dan daya ingat sehingga dapat disimpulkan algoritma naïve bayes berhasil untuk melakukan analisis sentimen. Keywords: Analisis sentimen; naïve bayes; pegipegi.com; playstore

ASSESSING EFFECTIVENESS JEMBER REGENCY EDUCATION DEPARTMENT WEBSITE USING COBIT FRAMEWORK

Sari, Ciptianingsih Ghonita, Wardoyo, Ari Eko, A’yun, Qurrota
Abstract: Abstract: In the digital era of transformation, educational websites serve as vital platforms for transparently disseminating information to stakeholders. This study evaluates the effectiveness of the Jember Regency Education… ation Department website using the COBIT 5 framework. This study aims to enhance the effectiveness and usability of the Department of Education website in Jember Regency by aligning it with stakeholders' evolving needs through comprehensive evaluation and targeted recommendations. Employing a qualitative descriptive approach, the research identifies challenges such as mobile optimization issues, slow loading times, security vulnerabilities, and content relevance concerns. Despite commendable accessibility, these challenges significantly impact user experience and website credibility. The findings underscore the urgent need for website optimization, improved security measures, and continuous content updates. This research provides actionable recommendations to align the website with IT governance standards, offering a roadmap for enhancement. Furthermore, the MEA Capability Results highlight discrepancies between the current scores and expected standards, indicating the necessity for comprehensive alignment with COBIT 5 guidelines to optimize website functionality and better meet user expectations.Top of Form             Keywords: COBIT 5 framework; Jember Regency Department of Education; website effectiveness     Abstrak: Pada era transformasi digital, situs web pendidikan menjadi platform penting untuk menyebarkan informasi secara transparan kepada para pemangku kepentingan. Studi ini mengevaluasi efektivitas situs web Dinas Pendidikan Kabupaten Jember menggunakan kerangka kerja COBIT 5. Studi ini bertujuan untuk meningkatkan efektivitas dan kegunaan situs web Dinas Pendidikan di Kabupaten Jember dengan menyelaraskannya dengan kebutuhan yang berkembang dari para pemangku kepentingan melalui evaluasi komprehensif dan rekomendasi yang ditargetkan. Dengan pendekatan deskriptif kualitatif, penelitian ini mengidentifikasi tantangan seperti masalah optimasi seluler, waktu muat yang lambat, kerentanan keamanan, dan kekhawatiran tentang relevansi konten. Meskipun aksesibilitasnya baik, tantangan-tantangan ini secara signifikan memengaruhi pengalaman pengguna dan kredibilitas situs web. Temuan ini menegaskan perlunya pengoptimalan situs web, peningkatan langkah-langkah keamanan, dan pembaruan konten yang berkelanjutan. Penelitian ini memberikan rekomendasi yang dapat dilaksanakan untuk menyelaraskan situs web dengan standar tata kelola TI, menawarkan panduan untuk peningkatan. Selain itu, hasil Kemampuan MEA menyoroti perbedaan antara skor saat ini dan standar yang diharapkan, menandakan kebutuhan akan penyesuaian yang komprehensif dengan pedoman COBIT 5 untuk mengoptimalkan fungsionalitas situs web dan memenuhi harapan pengguna dengan lebih baik. Top of Form   Kata kunci: Dinas Pendidikan Kabupaten Jember; efektivitas website; kerangka kerja COBIT 5

THE INFLUENCE OF STUDENST PERCEPTION OF DATA SECURITY AND PRIVACY ON TRANSACTION TRUST IN THE TOKOPEDIA APPLICATION

Wiranti, Ririn, Angraini, Angraini, Fronita, Mona, Monalisa, Siti, Munzir, Medyantiwi Rahmawita
Abstract: Abstract: The current development of technology has successfully met various societal needs, one of which is the buying and selling activities. This development has led people to engage in online transactions, where buyers… rs do not necessarily have to meet sellers in person. Tokopedia is one of the most popular e-commerce platforms used in Indonesia. Security issues arose when in 2020 Tokopedia experienced a breach, with data from around 91 million accounts being compromised by hackers. Consequently, Tokopedia needed to establish a Data Protection and Privacy Office (DPPO) to protect and safeguard user data privacy.This research addresses how perceptions of security and privacy can influence users' trust in transacting on Tokopedia. Using multiple linear regression analysis, the study evaluates the relationship between perceptions of data security and privacy with trust in transacting on Tokopedia. Based on the calculations of the multiple linear regression model using previously collected respondent data, it was found that perceptions of data security do not directly affect trust in transactions. However, perceptions of privacy are considered to have a significant influence and can increase trust in transactions among students in Pekanbaru.   Keywords: data security; e-commerce; tokopedia; transaction trust; user perceptions   Abstrak: Perkembangan teknologi saat ini telah sukses mencapai berbagai kebutuhan masayarakat salah satunya kegiatan jual beli, perkembangan ini membawa manusia untuk dapat melakukan jual beli secara online dimana tidak mengharuskan pembeli bertemu penjual secara langsung. Tokopedia menjadi salah satu platform e-commerce yang sangat popular digunkanan diindonesia. Masalah keamaan terjadi dimana pada tahun 2020 tokopedia mengalami peretasan dengan sekitar 91 juta akun berhasil diperoleh datanya oleh peretas, sehingga Tokopedia perlu membentuk data protection and privacy office (DPPO) guna melindungi dan menjaga privasi data pengguna Tokopedia.terkait hal tersebut penelitian ini mengangkat bagaimana persepsi keamanan dan privasi dapat mempengaruhi kepercayaan pengguna dalam bertransaksi ditokopedia. Dengan menggunakan metode regresi linear berganda, evaluasi dilakukan untuk menjelaskan hubungan antara persepi keamanan data dan privasi terhadap kepercayaan bertransaksi ditokopedia. Berdasarkan perhitungan model regresi linear berganda menggunakan data responden yang telah dilakukan sebelumnya didapat persepsi keamanan data terhadap kepercayaan bertransaksi tidak berpengaruh secara langsung. Namun pada persepsi privasi terhadap kepercayaan bertransaksi dinilai sangat berpengaruh dan dapat meningkatkan kepercayaan bertransaksi di kalangan mahasiswa di pekanbaru.   Kata kunci: e-commerce; keamanan data; kepercayaan transaksi; persepsi pengguna; tokopedia    

ANALYSIS OF PUBLIC OPINION ON INDONESIAN TELEVISION SHOWS USING SUPPORT VECTOR MACHINE

Farasalsabila, Fidya, Utami, Ema, Hanafi, Muhammad
Abstract: Abstract: There are a great number of academics that are now conducting research on sentiment analysis by employing supervised and machine learning techniques. The research can be carried out with the assistance of a variety… iety of sources, including reviews of movies, reviews of Twitter, reviews of online products, blogs, discussion forums, and other social networks. With the progress of technology, individuals may now effortlessly utilize social media platforms to access and share information, as well as express their viewpoints to the general public, without any constraints of distance or time. Twitter is a social media network that serves as a repository for opinions. Diverse techniques are employed to provide optimal and realistically precise pressure detection. The analysis and discussion affirm that the Support Vector Machine (SVM) was effectively employed in this study, utilizing public opinion data on television program reviews in Indonesia. An SVM classifier is employed to examine the Twitter data set by utilizing various parameters. The study successfully completed the preprocessing process by collecting a total of 400 data points, consisting of 320 reviews from 4 television shows for training data and 80 reviews for testing. The data was filtered and classified using SVM, with 200 positive and 200 negative data points for comparison. The experiment utilized the SVM method using TF-IDF to achieve the most accurate test results. The test accuracy was 80%, while the training data accuracy reached 100%.             Keywords: Sentiment Analysis; Support Vector Machine; Television Shows Review, TF-IDF,    Abstrak: Saat ini, banyak akademisi sedang menyelidiki analisis sentimen melalui pemanfaatan teknik yang diawasi dan pembelajaran mesin. Kajian dapat dilakukan dengan menggunakan beberapa sumber seperti review film, review Twitter, review produk online, blog, forum diskusi, atau jejaring sosial lainnya. Dengan kemajuan teknologi, masyarakat kini dapat dengan mudah memanfaatkan platform media sosial untuk mengakses dan berbagi informasi, serta menyampaikan pandangan mereka kepada masyarakat umum, tanpa batasan jarak dan waktu. Twitter adalah jaringan media sosial yang berfungsi sebagai gudang opini. Beragam teknik digunakan untuk menghasilkan deteksi tekanan yang optimal dan presisi secara realistis. Analisis dan pembahasan menegaskan bahwa Support Vector Machine (SVM) efektif digunakan dalam penelitian ini, memanfaatkan data opini publik tentang review program televisi di Indonesia. Pengklasifikasi SVM digunakan untuk memeriksa kumpulan data Twitter dengan memanfaatkan berbagai parameter. Penelitian berhasil menyelesaikan proses preprocessing dengan mengumpulkan total 400 titik data yang terdiri dari 320 review dari 4 acara televisi untuk data pelatihan dan 80 review untuk pengujian. Data disaring dan diklasifikasikan menggunakan SVM, dengan 200 titik data positif dan 200 titik data negatif sebagai perbandingan. Percobaan ini menggunakan metode SVM dengan menggunakan TF-IDF untuk mencapai hasil pengujian yang paling akurat. Akurasi pengujiannya mencapai 80%, sedangkan akurasi data pelatihan mencapai 100%.   Kata kunci: Analisis Sentimen, Review Tayangan Televisi, TF-IDF,  Support Vector Machine

IMPLEMENTING RESTFUL WEB SERVICE IN MENTOR SEARCH SYSTEM WITH AGILE SCRUM METHODOLOGY

Pratama, Fandy Indra, Budianita, Avira, Wijaya, Akhmad Pandhu, Syaifudin, Haikal Makin, Mustofa, Tegar Widya
Abstract: Abstract: The rapid development of technology makes stakeholders need easy and fast services. One of them is an easy and fast tutor search service. Parents who have a very busy life and school materials that develop very… rapidly make parents less able to help their children learn at home so parents need a solution in the form of an information system to facilitate the search for tutors. In the development of this information system adopts by combining the architecture of the model view controller (MVC) and restful web service because development using the architecture is very easy, fast and can be developed into multi platforms. Then in the development of this system using the Agile Scrum Methodology approach which is able to complete system development very quickly and organized. Regular communication in this Scrum approach makes the team feel comfortable because each member knows each other's progress process and obstacles. So that the achievements of each target can always be controlled and completed. So that the creation of an information system for the search for tutors is on target and can be used by the public.             Keywords: Agile, Agile Scrum Methodology, Information System, restful web service   Abstrak: Pesatnya perkembangan teknologi membuat stakeholder membutuhkan pelayanan yang mudah dan cepat. Salah satunya adalah layanan pencarian guru les yang mudah dan cepat. Orang tua yang memiliki kehidupan yang sangat sibuk dan materi sekolah yang berkembang sangat pesat membuat orang tua kurang bisa membantu anaknya belajar di rumah sehingga orang tua membutuhkan solusi berupa sistem informasi untuk memudahkan pencarian tutor. Dalam perkembangannya sistem informasi mengadopsi dengan menggabungkan arsitektur model view controller (MVC) dan restful web service karena pengembangan menggunakan arsitektur tersebut sangat mudah, cepat dan dapat dikembangkan menjadi multi platform. Kemudian dalam pengembangan sistem ini menggunakan pendekatan Agile Scrum Methodology yang mampu menyelesaikan pengembangan sistem dengan sangat cepat dan terorganisir. Komunikasi yang teratur dalam pendekatan Scrum ini membuat tim merasa nyaman karena setiap anggota saling mengetahui proses kemajuan dan hambatan masing-masing. Sehingga capaian setiap target dapat selalu terkontrol dan selesai. Serta terciptanya sistem informasi pencarian tutor tepat sasaran dan dapat digunakan oleh masyarakat   Kata kunci: Agile, Agile Scrum Methodology, Sistem Informasi, restful web service

WEB-BASED CLUSTER OPTIMIZATION USING K-MEDOIDS AND DAVIES BOULDIN INDEX

Christian, Ryan, Jollyta, Deny
Abstract: Abstract: Clustering data has always been a fascinating subject to research numerous perspectives. A variety of knowledge is produced by the calculating process utilizing various algorithms. The genesis of cluster optimization… ization is based on differences of opinion about the cluster's results. In general, cluster and optimization findings are generated using software such as Matlab, RapidMiner, and programming languages like Python. Users, however, have not been satisfied with the results so far. The various outcomes are the primary motivations for continuing to create and develop applications. The goal of this research is to create an application that can evaluate cluster data using the K-Medoids method, which can then be further optimized using the Davies Bouldin Index (DBI). Because the target application is students and lecturers who use it in learning and observers of the cluster field, the application can indeed be accessible through a browser to make it easier to use. For ease of using it, the program is available on both desktop and mobile platforms. Through separately created applications, it is intended that this research will give an alternative to clustering and optimization.             Keywords: application, cluster, dbi, k-medoids, optimization     Abstrak: Clusterisasi data selalu menjadi topik yang menarik untuk dikembangkan dari berbagai sisi. Proses perhitungannya yang menggunakan berbagai algoritma menghasilkan knowledge yang beragam. Perbedaan pendapat terhasil hasil cluster menjadi dasar munculnya optimalisasi cluster. Umumnya hasil cluster dan optimalisasi diperoleh dari pengolahan menggunakan aplikasi yakni Matlab, RapidMiner, dan bahasa pemrograman seperti Pyhton. Namun demikian hasil yang muncul belum mampu memuaskan pengguna. Hasil yang berbeda menjadi alasan utama pembuatan maupun pengembangan aplikasi masih terus dilakukan. Penelitian ini bertujuan untuk membangun sebuah aplikasi yang dapat memproses data cluster menggunakan algoritma K-Medoids untuk selanjutnya dioptimalisasi dengan Davies Bouldin Index (DBI). Untuk memudahkan penggunaan, aplikasi dapat diakses pada browser karena target aplikasi adalah mahasiswa dan dosen yang menggunakan pada pembelajaran serta pemerhati bidang cluster. Aplikasi dirancang pada platform desktop dan mobile demi memudahkan pengaksesan. Diharapkan, penelitian ini memberikan alternatif dalam proses clusterisasi dan optimalisasi melalui aplikasi yang dirancang mandiri.   Kata kunci: aplikasi; cluster; dbi; k-medoids; optimalisasi

PROJECT-BASED LEARNING ON CRYPTOGRAPHIC USING LMS

Syaifuddin, M, Amrullah, Amrullah, Ginting, Rico Imanta, Iswan, M, Hutagalung, Juniar
Abstract: Abstract:” Cryptography is one of the important subjects to learn because the content of the discussion discusses data security. Data security has a very important role considering that most transaction activities are… are carried out on the internet. Many platforms offer virtual transactions, such as motorcycle taxis, online marketplaces, and banking. For transacting on the internet, reliable data security is needed to maintain the security of user data from internet crimes (cybercrime). For cryptography learning to produce students who understand cryptography in-depth, this learning is carried out independently. One of the lessons to improve independent skills is a project approach. With project-based learning, students will be actively involved in completing projects given by the lecturer. To facilitate interaction and monitor projects completed by students, an LMS (Learning Management System) was created. The lecturer will later upload the student projects through the LMS, and if the student wants to work on the project, they can download it from the LMS.             Keywords: Cryptography; LMS; Online transactions     Abstrak:” Kriptografi merupakan salah satu mata pelajaran yang penting untuk dipelajari karena isi bahasannya membahas tentang pengamanan data. Saat ini, keamanan data memiliki peran yang sangat penting, mengingat sebagian besar aktivitas transaksi dilakukan di internet. Banyak platform yang menawarkan transaksi virtual, seperti ojek online, pasar online dan perbankan. Dalam bertransaksi di internet dibutuhkan keamanan data yang handal untuk menjaga keamanan data pengguna dari kejahatan internet (cyber crime). Agar pembelajaran kriptografi menghasilkan mahasiswa yang memahami kriptografi secara mendalam, maka pembelajaran ini dilakukan secara mandiri. Salah satu pembelajaran untuk meningkatkan kemampuan mandiri adalah dengan pendekatan  project. Dengan pembelajaran berbasis project,  mahasiswa akan terlibat aktif menyelesaikan project yang diberikan dosen. Untuk memudahkan interaksi dan monitor project yang diselesaikan mahasiswa, maka dibuat LMS (Learning Manajement System). Setiap project mahasiswa nantinya akan di unggah oleh dosen melalui LMS dan mahasiswa bisa mengunguh project di LMS Dengan menambahkan LMS dan pembelajaran yang berbasis project pada  pembelajaran kriptografi menunjukkan hasil belajar yang lebih baik. Hal ini dapat dilihat pada hasil tinjauan dilangan dengan penyelesaian sebuah soal dan hasil ujian akhir mahasiswa.   Kata kunci: Kriptografi; LMS; Transaksi Online,