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All Journal Kajian Pendidikan & Akuntansi Indonesia JURNAL SISTEM INFORMASI BISNIS Jurnal Teliska Jurnal Pengajaran MIPA Biota: Jurnal Ilmiah Ilmu-Ilmu Hayati PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Pendidikan Matematika Prosiding SNATIF Nurani: Jurnal Kajian Syariah dan Masyarakat Global Medical and Health Communication ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Jurnal Ampere ITEj (Information Technology Engineering Journals) PAUDIA: JURNAL PENELITIAN DALAM BIDANG PENDIDIKAN ANAK USIA DINI JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING IT JOURNAL RESEARCH AND DEVELOPMENT Indonesian Journal of Artificial Intelligence and Data Mining JOURNAL OF APPLIED INFORMATICS AND COMPUTING Journal of Teaching and Learning in Elementary Education Jurnal Ekonomi Integra Biosaintifika: Journal of Biology & Biology Education Martabe : Jurnal Pengabdian Kepada Masyarakat Jurnal Teknologi Sistem Informasi dan Aplikasi Jurnal RESISTOR (Rekayasa Sistem Komputer) JURIKOM (Jurnal Riset Komputer) MIND (Multimedia Artificial Intelligent Networking Database) Journal AMALIAH: JURNAL PENGABDIAN KEPADA MASYARAKAT EDUMATIC: Jurnal Pendidikan Informatika Building of Informatics, Technology and Science Jurnal Ilmiah Permas: Jurnal Ilmiah STIKES Kendal Jurnal Idiomatik: Jurnal Pendidikan Bahasa dan Sastra Indonesia Community Development Journal: Jurnal Pengabdian Masyarakat Indonesian Journal of Global Health research JOURNAL LA MEDIHEALTICO Jurnal Perak Malahayati : Pengabdian Kepada Masyarakat Journal of Technology and Informatics (JoTI) INDONESIAN JOURNAL OF HEALTH Jurnal Hukum Jurisdictie Jurnal Kesehatan Abdurrahman Innovative: Journal Of Social Science Research SJEE (Scientific Journals of Economic Education) PMSDU Jurnal Multidisipliner Kapalamada Wistara: Jurnal Pendidikan Bahasa dan Sastra Al-Hijrah: Journal of Islamic Economics and Banking IEB: Journal of Islamic Economics and Business
Aryanti Aryanti
Centre for Isotopes and Radiation Application, BATAN, Indonesia
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Public Health Social Sciences Veterinary Other

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Journal : Building of Informatics, Technology and Science

 1 
Implementasi Algoritma SVM Non-Linear Pada Klasifikasi Analisis Sentimen Perkembangan AI di Sektor Pendidikan Putri, Alda Nabila; Aryanti, Aryanti; Soim, Sopian
Building of Informatics, Technology and Science (BITS) Vol 6 No 2 (2024): September 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

As technology advances, the utilization of the X platform or formerly Twitter is expanding, allowing users to exchange opinions on various topics including the transformative impact of AI in the Education sector. While AI has great potential in revolutionizing the quality and accessibility of education, it can also bring potential challenges, such as over-reliance on technology. Sentiment analysis is a computational approach to identify, extract, and classify sentiments, opinions, and emotions expressed in text. To examine the problem, this research implements a Non-Linear Support Vector Machine model to analyze sentiment about AI in the education sector. This study built four SVM models with different kernel functions, namely linear, RBF, Polynomial, and Sigmoid kernels. By utilizing 3,000 tweet data collected from platform X by scraping technique, the SVM model with polynomial kernel succeeded in becoming the best model, with accuracy, precision, recall and f1-score values of 92%. This model was able to classify 52.9% of the tweet data with positive sentiment and 47.1% of the tweet data with negative sentiment, which shows that in general, users of platform X tend to have a positive sentiment towards the development of AI in the education sector.
Implementasi Metode Fuzzy Sugeno dalam Aplikasi Mobile untuk Analisis Kinerja Sistem Antrian Puskesmas Harahap, Adhelia Febriasari; Aryanti, Aryanti; Anugraha, Nurhajar
Building of Informatics, Technology and Science (BITS) Vol 6 No 2 (2024): September 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i2.5562

Abstract

The registration process at health centers often faces efficiency issues, causing inconvenience for patients and reducing service productivity. Puskesmas is one such health facility that faces long queue problems almost every day, impacting the quality of service. This study aims to design and develop a health center queuing system based on the Internet of Things (IoT), allowing online registration through a mobile application based on Android and more efficient ticket acquisition. The Fuzzy Sugeno method is applied to evaluate and improve the performance of the queuing system. This application also provides notifications to patients about the time to enter the targeted clinic, thereby reducing waiting times and preventing loss of queue numbers. The implementation of the Fuzzy Sugeno method at Puskesmas has shown significant results in various service aspects. The average patient waiting time decreased from 90 minutes to 40 minutes, reflecting a reduction of 55.6%. Patient satisfaction increased from 3.2 to 4.5 on a scale of 5, or by 40.6%. Registration efficiency improved, with the time required decreasing from 10 minutes to 4 minutes per patient, resulting in a 60% increase in efficiency. Additionally, the service capacity increased, with the number of patients served per day rising from 70 to 100 patients, indicating an increase of 42.8%. The implementation of this technology has succeeded in creating more responsive, effective, and productive health services at Puskesmas, providing a positive impact on the community as a whole.
Deteksi URL Phishing Menggunakan Natural Language Processing Dan Support Vector Machine Berbasis Machine Learning Nabila, Nabila; Hesti, Emilia; Aryanti, Aryanti
Building of Informatics, Technology and Science (BITS) Vol 7 No 1 (2025): June (2025)
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v7i1.7443

Abstract

Phishing represents a significant danger in cybersecurity, using malicious URLs to mislead users into revealing critical information. This research seeks to create a phishing URL detection model using machine learning via the integration of structural URL feature extraction, Natural Language Processing (NLP) methodologies, and the Support Vector Machine (SVM) classification algorithm. Indicators of phishing trends are derived from features such as URL length, the quantity of dots, and slashes, while URL content is quantified as numerical vectors using Term Frequency-Inverse Document Frequency (TF-IDF). All characteristics are subsequently integrated as input into a support vector machine model with a linear kernel for classification. The evaluation results from the classification report indicate that the integration of TF-IDF and linear kernel SVM achieves optimal performance, with 90% accuracy, 92% precision, 89% recall, and 90% F1-score. Conversely, the confusion matrix reveals 90.29% accuracy, 91.66% precision, 88.62% recall, and 90.12% F1-score. This study primarily contributes by integrating NLP and SVM into a unified adaptive phishing detection model via the amalgamation of structural and textual aspects of URLs. This strategy facilitates enhanced phishing detection relative to techniques reliant only on manual characteristics. This model, unlike other research that concentrated on particular instances or excluded NLP, is engineered to identify many categories of phishing URLs broadly, hence enhancing its relevance in tackling the dynamic nature of assaults.
Co-Authors AA Sudharmawan, AA Adhi Nugraha Agung, Muhammad Zakuan Agustini, Anisa 'A Aini, Apriyanti Akifah Fakhira, Dhia Al Hafiizh, Erwin Ali Akbar Alimuddin, Tri Herdian Syah Aliudin Aliudin, Aliudin Andoko Andoko, Andoko ANDREANSYAH, DIMAS Angelina, Fifteen Anggraini, Nur Septi Anugrah, Aninditya Putri Aprilia, Nadya APRILIANI, DEFINA Ar-Rassya, M.Nabil Asrafi, Ibnu Asriyadi Asriyadi Basri, Syamsuriana Ciksadan, Ciksadan Daeng Kanang, Indah Lestari Daviana, Feriska Putri Desiana, Lidia Desvi Wahyuni Djakfar, Yunizir DWI RAMADHANI Dwiyanti, Julita Dyah Utari Yusa Wardhani Efridani Lubis Elliya, Rahma Emilia Hesti Endri, Jon Epriyani, Merita Ernawati Ernawati Fadli, Irwan Fahrezi, M. Vilza Raihan Fahrozy, Dimas Iqbal Farrel Akbar, Jonathan Fatin, Muhammad Hanif Fazarrudin, Muhammad Febriyanti, Valentina Fitrawahyudi, Fitrawahyudi FITRIYANTI, RAMADHINA Gibtiah Gibtiah H., Rahmawati Haksa, Febrina Rosadah Halimatussa'diyah, R.A. Halimatussa’diyah, R. A. Handoko, Ridwan Harahap, Adhelia Febriasari Hilda Hilda Ikhthison Mekongga Imansyah, Muhammad Ince Nasrullah Indah Dwi Sartika Intan Handayani, Sri Irma Salamah Iryani, Nanda Ishak Ishak Ismail Suardi Wekke Ita Dwimahyani K, Umi Rohmayati Kartika Sari, Enda Kasmawati Khaerani, Khaerani Khairunnisa Khairunnisa Kurniyanti, Novia Kyara, Fatia Salsabilla Laila, Nazmy Noor Lamdayani, Rinda Larasati, Woro Endah Lindawati , Lindawati Lindawati Lindawati Lubis, Abdillah Luna Pasha, Kayla Makmun, Armanto Malinda, Threa Maya, Sri Meike Rachmawati Meitasari, Vina Meitasari, Vina Melati, Rina Mia, Salmia Mustaziri Nabila, Nabila Nasrullah, Ince Nesyana, Nesyana Novelasari, Novelasari Noviansyah, Noer Ramadhon Nurhadiva, Siti Salwa Nurhajar Anugraha Nuzirwan Acang Palpa, Clara Alcahya Permadi, Yan Pramawati, Anita Purwani, Rani Putri, Alda Nabila Putri, Chairunnissa Putri, Nurhaliza Aulia Putri, Vivi Dwi PUTRI, WULAN ZAHRA Rachmania, Rachmania Rahmi Rahmi Ramayanti, Tariza Putri Resti Ardiansyah, Noval Retno Wulandari Rilyani, Rilyani Rini Anggeriani Rini Marwati Riska Wandini, Riska Riswandi, Akmal Rizka, Mahda Robian, Rian Rohmad Adi Yulianto Rosyada, Rosyada Sabila Utami, Meisyah Sakti, Irma Saleh, Ahmad Muzawwir Samsul Anam, Samsul Saputri, Kirana Assyifa Sari, Diah Novita Sari, Lia Dian Sari, Yona Sarjana Sarjana Setiawati Setiawati Silvia, Eka Sitti Aisyah Sopian Soim Sopian Soim, Sopian Suci, Yuni Selvita Sugeng Santoso Suryanti, Yuli Sutedja, Lenny Syafitri, Dhea Syamsiar, Syamsiar Tely, Aristo Tiara Fatrin Titin Apriyani Tri Muji Ermayanti Trismiana, Eka Triyoso, Triyoso Umari, zuul fitriani Utami, Pertiwi Nurul Wibowo, Muhamad Arya Al Ghifari Wida Purbaningsih Wijaya, Tommy Tanu Wijayanti, Adhika Wulandari, Afifah Yordan Hasan, Yordan Yulia Hapsari Yulia Haryono Zhafarina, Imas Ning