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All Journal Information Technology and Telematics Dinamik Dinamika Hukum Publikasi Eksternal Scientific Journal of Informatics Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Ilmiah Universitas Batanghari Jambi IKRA-ITH Informatika : Jurnal Komputer dan Informatika Fokus Ekonomi Jurnal Sisfokom (Sistem Informasi dan Komputer) INTECOMS: Journal of Information Technology and Computer Science IKRA-ITH ABDIMAS PengabdianMu: Jurnal Ilmiah Pengabdian kepada Masyarakat To Maega: Jurnal Pengabdian Masyarakat JURNAL MAHAJANA INFORMASI Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Jurnal Pengabdian Masyarakat: Darma Bakti Teuku Umar Suluah Bendang: Jurnal Ilmiah Pengabdian Kepada Masyarakat Dinamika Informatika: Jurnal Ilmiah Teknologi Informasi Journal of Soft Computing Exploration JEEE-U (Journal of Electrical and Electronic Engineering-UMSIDA) Journal of Community Development and Disaster Management Jurnal Pengabdian Masyarakat Intimas (Jurnal INTIMAS): Inovasi Teknologi Informasi Dan Komputer Untuk Masyarakat ABDINE Jurnal Pengabdian Masyarakat Media Abdimas The Indonesian Journal of Computer Science Servis : Jurnal Pengabdian dan Layanan kepada Masyarakat Andan Jejama: Indonesian Journal Of Community Engagement
Dewi Handayani Untari Ningsih
Universitas Stikubank
Religion Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Library & Information Science Public Health Social Sciences Other

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Journal : Journal of Soft Computing Exploration

 1 
Content-based filtering using cosine similarity algorithm for alternative selection on training programs Abdurrafi, Muhammad Falah; Ningsih, Dewi Handayani Untari
Journal of Soft Computing Exploration Vol. 4 No. 4 (2023): December 2023
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joscex.v4i4.232

Abstract

The large selection of training programs provided by the Ministry of Manpower of the Republic of Indonesia makes it difficult for prospective trainees to choose a training program that suits their interests and needs. The purpose of this research is to support the selection process so that an appropriate method is needed to recommend the selection of training programs that match the interests and needs of users. One of the selection methods that can be used is the Content-Based Filtering method with similarity measurement using Cosine Similarity. The content-based filtering method is a content-based filtering method, which recommends training programs based on the suitability between the description of the training program and the interests of prospective trainees using the cosine similarity distance measurement. The test results using the Content-Based Filtering method were able to achieve an average precision value of 88%, indicating the ability of the system to provide training program recommendations that are very relevant and in accordance with the interests and needs of the trainees.
Improved playstore review sentiment classification accuracy with stacking ensemble Santoso, Dwi Budi; Munna, Aliyatul; Untari Ningsih, Dewi Handayani
Journal of Soft Computing Exploration Vol. 5 No. 1 (2024): March 2024
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joscex.v5i1.247

Abstract

In today's digital era, user reviews on the Playstore platform are an invaluable source of information for developers, offering insights that are critical for service improvement. Previous research has explored the application of stacking ensemble methods, such as in the context of predicting depression among university students, to enhance prediction accuracy. However, these studies often do not explicitly detail the data acquisition process, leaving a gap in understanding the applicability of these methods to different domains. This research aims to bridge this gap by applying the stacking ensemble approach to improve the accuracy of sentiment classification in Playstore reviews, with a clear exposition of the data collection method. Utilizing Logistic Regression as the meta classifier, this methodology is executed in several stages. Initially, data was collected from user reviews of online loan applications on Google Playstore, ensuring transparency in the data acquisition process. The data is then classified using three basic models: Random Forest, Naive Bayes, and SVM. The outputs of these models serve as inputs to the Logistic Regression meta model. A comparison of each base model output with the meta model was subsequently carried out. The test results on the Playstore review dataset demonstrated an increase in accuracy, precision, recall, and F1 score compared to using a single model, achieving an accuracy of 87.05%, which surpasses Random Forest (85.6%), Naive Bayes (85.55%), and SVM (86.5%). This indicates the effectiveness of the stacking ensemble method in providing deeper and more accurate insights into user sentiment, overcoming the limitations of single models and previous research by explicitly addressing data acquisition methods.
Co-Authors - Sunardi Abdurrafi, Muhammad Falah Achmad Badjuri Achmad Badjuri ADAM, ALFUN Adi Suliantoro Agung Setyadi Agus Prasetyo Utomo Agustianto, Muchammad Lutfi Ahmad Ahfas Al Rasyid, Rio Alif Candra Pratama Alldie Refkrisnatta Alvin Chrismono Aminuyati Anggor, Ardie Septia Anggoro Teguh Adiyanto* Anisi, Yunus Arief Jananto Arif Sungkono Ariyani, Dewi Ayu Brian Krisnabel Budi Hartono Budi Hartono budi hartono Cahyani, Alya Takwarina Deva Ega Marinda Dewi Handayani Didit Iswantoro Dwi Agus Diartono Dwi Budi Santoso Dwi Budi Santoso Dwi Prakoso, Vikko Eddy Nurraharjo Edy Supriyanto Edy Winarno Endang Tjahjaningsih Endang Tjahjaningsih Endang Tjahjaningsih Eri Zuliarso Febriyan, Salma Eka Fitika Andraini Fitika Andraini Ginanjar, Muhammad Syukron Heribertus Yulianton Herina Dwi Nastiti Herny Februariyanti Imam Husni Al Amin Irawan, Pebry Irvan Ardiansyah Isworo Nugroho Joko Handoyo Mardi Siswo Utomo Much Aziz Muslim Muhammad Lutfi Mahasinul Akhlak Muji Sukur Munna, Aliyatul Nadzif, Mukhamad Abid Novita Mariana Nurdin, Alya Aulia Pambudi, Risma Priyanti, Esteria R. Soelistijadi Radyanto, Mohammad Riza Retnowati Retnowati Rina Candra Noor Santi Rusiyanto Rusiyanto, Rusiyanto safurrohman . Sari, Anisa Rachma Sri Isnowati Sunardi . Syahrorini, Syamsudduha Teguh Khristianto Veronica Lusiana Veronica Lusiana Wahyu Prasetyo Wismarini, Th Dwiati