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<![CDATA[ANALISIS SENTIMEN OPINI PUBLIK TERHADAP ATURAN PENGHAPUSAN KELAS BPJS PADA PLATFROM X MENGGUNAKAN MULTI-LAYER PERCEPTRON ]]>
<![CDATA[Ratu Bunga Prawesti Arie Salim]]>;
<![CDATA[Dwi Cahya Julia Kartikasari]]>;
<![CDATA[Muhammad Athoillah]]>;
<![CDATA[Hani Brilianti Rochmanto]]>
<![CDATA[ Seminar Nasional Hasil Riset dan Pengabdian Vol. 6 (2024): Seminar Nasional Hasil Riset dan Pengabdian (SNHRP) Ke 6 Tahun 2024 ]]>
Publisher : <![CDATA[LPPM Universitas PGRI Adi Buana ]]>
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<![CDATA[Analisis sentimen adalah bidang studi yang menganalisis opini dan sentimen seseorang terhadap suatu masalah. Penelitian ini menganalisis sentimen opini publik terhadap aturan penghapusan kelas BPJS yang akan diganti dengan KRIS menggunakan data dari platform X. Metode yang digunakan adalah Multi-Layer Perceptron (MLP), sebuah jenis neural network yang mampu menangani data kompleks dan hubungan non-linear. Fitur extraction dilakukan dengan Term Frequency – Inverse Document Frequency (TF-IDF), dan validasi menggunakan Confusion Matrix. Hasil penelitian menunjukkan bahwa model MLP mampu mengkategorikan sentimen dengan rata-rata akurasi 84.06%, menunjukkan efektivitas metode ini untuk analisis sentimen opini publik pada platform X. Kata kunci: Analisis sentimen; Multi-Layer Perceptron (MLP); Confusion Matrix]]>
<![CDATA[ANALISIS SENTIMEN ULASAN WHATSAPP DI GOOGLE PLAY STORE MENGGUNAKAN ALGORITMA SINGLE-LAYER PERCEPTRON (SLP) ]]>
<![CDATA[Pretesya Septiliani Syukur]]>;
<![CDATA[Izequela De Jesus Madeira]]>;
<![CDATA[Hani Brilianti Rochmanto]]>;
<![CDATA[Muhammad Athoillah]]>
<![CDATA[ Seminar Nasional Hasil Riset dan Pengabdian Vol. 6 (2024): Seminar Nasional Hasil Riset dan Pengabdian (SNHRP) Ke 6 Tahun 2024 ]]>
Publisher : <![CDATA[LPPM Universitas PGRI Adi Buana ]]>
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<![CDATA[Abstrak Di era digital ini, media sosial seperti WhatsApp, telah menjadi bagian penting dari kehidupan masyarakat modern di Indonesia. Popularitasnya menjadikan ulasan di Google Play Store sebagai sumber informasi berharga untuk memahami persepsi pengguna. Penelitian ini menganalisis sentimen ulasan WhatsApp menggunakan algoritma Single-Layer Perceptron (SLP). Dari 2000 ulasan yang dikumpulkan, 1700 digunakan setelah proses labeling dan pre-processing. Hasil menunjukkan bahwa model SLP memiliki rata-rata akurasi 76%, presisi 76%, recall 76%, dan f1-score 76%. Penelitian bertujuan memberikan kontribusi pada bidang analisis sentimen dengan menunjukkan efektivitas algoritma SLP dalam mengkategorikan sentimen ulasan pengguna aplikasi Whatsapp. Kata kunci: WhatsApp; Analisis Sentimen; Single-Layer Perceptron; Jaringan Syaraf Tiruan]]>
<![CDATA[Problematika Dan Tantangan Santri Di Era Revolusi Industri 5.0 ]]>
<![CDATA[Athoillah, Muhammad]]>;
<![CDATA[Darmaningrum, Khaerunnisa Tri]]>
<![CDATA[ FATAWA: Jurnal Pendidikan Agama Islam Vol. 3 No. 2 (2023): Juni ]]>
Publisher : <![CDATA[Program Studi Pendidikan Agama Islam ]]>
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DOI: 10.37812/fatawa.v3i2.1353
<![CDATA[In the current and future era of digital Society 5.0, Islamic boarding schools must also equip students with adequate technological information to support life. In this day and age, whether they like it or not, students will be exposed to the virtual world. The Era of Society 5.0 is an era where all technology cannot be separated from humans themselves. In this case, education has entered the Era of the Industrial Revolution 5.0, where the biggest era has entered the digital era. Currently, education in Islamic boarding schools is facing challenges that cannot be avoided along with the rapid development of technology. and students must be able to face how to keep up with technological developments and maintain the Islamic boarding school culture that has been tested in the Islamic boarding school journey. This research is analytical research that uses library research methods (Library Research). The research results include that changing the learning model from traditional textbooks to digital has become problematic for the world of Islamic boarding schools. This paradigm shift aims to abandon the academic and cultural traditions of Islamic boarding schools which are still preserved as Islamic boarding school identities. Islamic boarding schools must maintain their local identity (local wisdom) but must be globally competitive. There needs to be a change in the model of kiai and santri in Islamic boarding schools so that millennial students can become millennial students who can answer the challenges of the digital age.]]>
<![CDATA[PELATIHAN VISUALISASI DATA SEKOLAH SMK SEPULUH NOPEMBER SIDOARJO ]]>
<![CDATA[Athoillah, Muhammad]]>;
<![CDATA[Pramesti, Wara]]>;
<![CDATA[Lusyanti Gili, Ireni]]>;
<![CDATA[Findiariska, Yasmin]]>
<![CDATA[ Kanigara Vol 2 No 2 (2022): Kanigara ]]>
Publisher : <![CDATA[Universitas PGRI Adi Buana Surabaya ]]>
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DOI: 10.36456/kanigara.v2i2.5608
<![CDATA[As a form of scientific implementation in a proactive, consistent and sustainable manner in providing the maximum benefit to the community through the development of science, especially in the field of data science. The Statistics Study Program at PGRI Adi Buana University Surabaya in collaboration with the Institute for Research and Community Service (LPPM) at PGRI Adi Buana University Surabaya provided training on visualization of school data at SMK Sepuluh Nopember. This data visualization training is needed because of the school's need for the ability to process data properly so that the information conveyed by the data can be conveyed properly by the reader. The training activities were successfully carried out as seen from the evaluation results of the pre-test and post-test scores which increased significantly. In addition, the success of the activity can also be seen from the feedback of participants who want continuous training.]]>
<![CDATA[PELATIHAN KARYA TULIS ILMIAH BIDANG SAINS DATA BAGI GURU MADRASAH ALIYAH NEGERI (MAN) 2 NGANJUK ]]>
<![CDATA[Athoillah, Muhammad]]>;
<![CDATA[Fitriani, Fenny]]>
<![CDATA[ Kanigara Vol 4 No 1 (2024): Kanigara ]]>
Publisher : <![CDATA[Universitas PGRI Adi Buana Surabaya ]]>
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DOI: 10.36456/kanigara.v4i1.8535
<![CDATA[Scientific writing is not only a formal tool, but is an active step in exploring, processing and documenting knowledge in the field of data science. These skills are key in responding to business and social challenges that take advantage of abundant information. Therefore, the Training on Writing Scientific Papers in the Field of Data Science for MAN 2 Nganjuk teachers, which was organized by the Student Creativity Program Team (PKM) of PGRI Adi Buana University Surabaya, was based on the urgency to empower educators in conveying the concepts and application of data science . The training material includes basic data science concepts and practical guidance for writing scientific papers. Evaluation of participant satisfaction shows positive results, reflecting the effectiveness of the training and positive contribution to the development of science and technology in society.]]>
<![CDATA[Eksplorasi Data Sains dalam Pendidikan: Membuka Wawasan Baru untuk Siswa SMA ]]>
<![CDATA[Athoillah, Muhammad]]>;
<![CDATA[Rochmanto, Hani Brilianti]]>;
<![CDATA[Wae, Maria Yohana Vianey]]>;
<![CDATA[Rokhmania, Nina Anggraini Junet]]>
<![CDATA[ Journal of Community Service and Society Empowerment Том 3 № 01 (2025): Journal of Community Service and Society Empowerment ]]>
Publisher : <![CDATA[PT. Riset Press International ]]>
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DOI: 10.59653/jcsse.v3i01.1350
<![CDATA[Data science literacy is an important skill in the digital era, but high school students' understanding of this concept is still limited. This study aims to improve students' data science literacy through interactively designed training, including theory delivery and discussion sessions. This study was conducted in Surabaya involving 32 students from five partner schools. The research instruments included a pre-training questionnaire to measure the level of initial understanding, training materials in the form of presentations and educational case studies, and a post-training questionnaire to evaluate the results. The analysis was carried out quantitatively based on the results of the pre-test and post-test, and qualitatively through observation and discussion. The results showed a significant increase in student understanding, with the average post-test score increasing from 45% to 80%. Positive responses from students and teachers indicated that the case study-based training approach was relevant and effective. However, obstacles such as differences in student understanding levels and limited training duration were obstacles to implementation in maximizing knowledge for participants.]]>
<![CDATA[ANALISIS FAKTOR YANG MEMPENGARUHI KETEPATAN KELULUSAN MAHASISWA DENGAN ALGORITMA REGRESI LINEAR ]]>
<![CDATA[Putri, Rani Kurnia]]>;
<![CDATA[Athoillah, Muhammad]]>;
<![CDATA[Haqiqiyah, Arina]]>
<![CDATA[ Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Vol. 5 No. 2 (2024): Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistik ]]>
Publisher : <![CDATA[LPPM Universitas Bina Bangsa ]]>
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DOI: 10.46306/lb.v5i2.571
<![CDATA[Student graduation is an important achievement in higher education which reflects success in completing studies by fulfilling the requirements set by the university. Graduation accuracy, which refers to the extent to which students complete their study program according to the set target time, also has a crucial role in the world of education. In this context, analysis of the factors that influence the accuracy of student graduation becomes important. In this research, analysis was carried out using a linear regression algorithm to understand the factors that influence student graduation at PGRI Adi Buana University Surabaya. The results of the analysis show that the Cumulative Achievement Index (GPA), Class Type, and Program Studi (Prodi) variables have a significant influence on the accuracy of student graduation. The best regression model selected has a high level of accuracy, indicating its effectiveness in explaining the data. The conclusions from this analysis provide in-depth insight into the factors that influence student graduation as well as the suitability of the model in explaining this phenomenon]]>
<![CDATA[Peran Film Dilan 1990 dalam Membangun Imajinasi Wisata Kota Bandung Melalui Interaksi Tokoh Utama ]]>
<![CDATA[Recta Yogi Widi Astutik]]>;
<![CDATA[Tava Julia Putri]]>;
<![CDATA[Muhammad Athoillah]]>;
<![CDATA[Muhammad Shofaul Fahmi Priyono]]>;
<![CDATA[Ariel Dimas Hidayatullah]]>;
<![CDATA[Arsih Amalia Chandra Permata6]]>;
<![CDATA[Wiyata Wiyata]]>
<![CDATA[ Filosofi : Publikasi Ilmu Komunikasi, Desain, Seni Budaya Vol. 2 No. 2 (2025): Mei : Filosofi : Publikasi Ilmu Komunikasi, Desain, Seni Budaya ]]>
Publisher : <![CDATA[Asosiasi Seni Desain dan Komunikasi Visual Indonesia ]]>
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DOI: 10.62383/filosofi.v2i2.680
<![CDATA[This research explores the role of the film Dilan 1990 in shaping the tourism imagination of Bandung through the interaction of its main characters and the representation of urban space within the narrative. Employing a descriptive qualitative approach with semiotic analysis and cultural representation theory, the research examines how visual and narrative elements in the film influence audience perceptions of Bandung as a cultural and nostalgic tourist destination. The findings reveal that Dilan 1990 successfully reconstructs collective memory of 1990s Bandung through cultural symbols, youth communication styles, and the depiction of urban spaces such as schools, streets, and city landmarks like Gedung Merdeka and Jalan Asia Afrika. The interpersonal communication between Dilan and Milea enhances the emotional depth and appeal of these urban settings, embedding them within a romantic narrative that resonates with viewers. This representation fosters an emotional connection between the audience and the locations portrayed, contributing to the emergence of film-induced tourism. The study concludes that film can serve as an effective medium for promoting cultural tourism, while also emphasizing the importance of interpersonal communication in enhancing tourism appeal through emotional and symbolic engagement.]]>
<![CDATA[PENGUASAAN NEGARA TERHADAP SUMBER DAYA DALAM PANDANGAN ISLAM ]]>
<![CDATA[Ibrohim, Muhammad]]>;
<![CDATA[Athoillah, Muhammad]]>
<![CDATA[ Syariah: Journal of Fiqh Studies Vol 1 No 2 (2023): Syariah: Journal of Fiqh Studies ]]>
Publisher : <![CDATA[Bidang Penelitian Dan Penulisan Karya Ilmiah (bp2ki) Ma'had Aly Lirboyo ]]>
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DOI: 10.61570/syariah.v1i2.34
<![CDATA[The Right to Control the State (HMN) as stated in Article 33 of the 1945 Constitution is the juridical basis that regulates state power over natural and artificial resources. Through this research, the author describes the views of Salaf Islamic boarding school literature on the use of state resources and HMN to explore their conformity with Islamic teachings. This research method uses library research with a deductive approach. As a result of this research, the author concluded that in the view of Salaf Islamic boarding school literature, state resources are a blessing from Allah SWT. give it to all the people. This favor must be used to realize the common good and must not be monopolized. In the view of Salaf Islamic boarding school literature, HMN is also considered a manifestation of the government's obligation to manage state resources to create benefits for all people. Based on this conclusion, the assumption that HMN violates Islamic teachings is incorrect. However, the government must always strive for the benefit of managing state resources, including delegating its power to the private sector.]]>
<![CDATA[Study Comparison Deep Learning and Support Vector Machine for Face Mask Detection ]]>
<![CDATA[Putri, Rani Kurnia]]>;
<![CDATA[Athoillah*, Muhammad]]>
<![CDATA[ Aceh International Journal of Science and Technology Vol 14, No 1 (2025): April 2025 ]]>
Publisher : <![CDATA[Graduate School of Universitas Syiah Kuala ]]>
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DOI: 10.13170/aijst.14.1.32109
<![CDATA[Deep Learning (DL) and Support Vector Machine (SVM) was used for a plethora number of researches lately. Deep Learning works by representing data in layers of learning layers so that the representation becomes more meaningful, and Support Vector Machine tries to find the hyperplane that maximizes the margin between the hyperplane and the closest data points from each class so that the classification becomes more accurate. Both algorithms have proven to be powerful tools for any classification problem specially to classify or identify image patterns. However, the performance of machine learning algorithms can be affected by any factor, thus sometimes we found several algorithms that are generally known to be powerful, even showing unsatisfactory results. The purpose of this study is to compare the ability of classification methods Deep Learning and Support Vector Machine to detect face mask. Face mask detection has gained significant attention and importance in the context of public health and safety, particularly during the COVID-19 pandemic. The study revealed that Deep Learning algorithm performed better than the Support Vector Machine Algorithm and showed excellent performance in all four metrics. In particular, the Deep Learning algorithm achieved an average Sensitivity/Recall rate of 92%, a Specificity rate of 95.44%, a Precision rate of 95.28%, and an Accuracy rate of 93.72%.]]>
