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All Journal Biospecies Biotika: Jurnal Ilmiah Biologi AL KAUNIYAH AL-TA´LIM Al-`Ulum Potensia Jurnal Wilayah dan Lingkungan Sriwijaya University Learning and Education International Conference Indonesian Journal of Educational Research (IJER) Pendas mahakam : jurnal pendidikan dan pembelajaran Sekolah Dasar Jurnal Penelitian Pendidikan IPA (JPPIPA) Journal of Environment and Sustainability Indonesian Journal of Islamic Educational Management Biosfer: Jurnal Pendidikan Biologi Jurnal SOLMA Jurnal Biologi Tropis Pendas : Jurnah Ilmiah Pendidikan Dasar Diklabio: Jurnal Pendidikan dan Pembelajaran Biologi Biosel: Biologi Science and Education Jurnal Biolokus: Jurnal Penelitian Pendidikan Biologi dan Biologi Jurnal BIOEDUIN : Program Studi Pendidikan Biologi Jurnal Ecolab JURNAL PENDIDIKAN TAMBUSAI JURTEKSI At-Ta'lim : Media Informasi Pendidikan Islam Al-Ta'lim Jurnal Biotek Jurnal Pendidikan dan Konseling Jurnal Pembelajaran dan Biologi Nukleus Jurnal Informatika dan Rekayasa Perangkat Lunak Jendela Pendidikan Bioscientist : Jurnal Ilmiah Biologi SECONDARY : Jurnal Inovasi Pendidikan Menengah (JIPM) ELEMENTARY : Jurnal Inovasi Pendidikan Dasar TEACHING : Jurnal Inovasi Keguruan dan Ilmu Pendidikan MANAJERIAL: Jurnal Inovasi Manajemen dan Supervisi Pendidikan Indo-MathEdu Intellectuals Journal Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI) International Journal of Education and Teaching Zone Takuana: Jurnal Pendidikan, Sains, dan Humaniora Jurnal Teknik Informatika dan Teknologi Informasi Al-Irsyad: Journal of Education Science IDARAH : Jurnal Pendidikan dan Kependidikan Innovative: Journal Of Social Science Research Jurnal Sistem Informasi dan Manajemen JUPEMA Biodik: Jurnal Ilmiah Pendidikan Biologi EDUCATIONAL: Jurnal Inovasi Pendidikan dan Pengajaran Asian Journal of Science Education Indonesian Journal of Science and Education Jurnal Biosilampari: Jurnal Biologi At-Ta'lim : Media Informasi Pendidikan Islam
Try Susanti
UIN Sulthan Thaha Saifuddin Jambi
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Energy Engineering Environmental Science Immunology & microbiology Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Physics Public Health Social Sciences Other

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Journal : JURTEKSI

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ANALYSIS OF PUBLIC OPINION SENTIMENT REGARDING POLICE INSTITUTIONS BASED ON TWITTER USING THE SUPPORT VECTOR MACHINE (SVM) METHOD Sirojudin, Said Ahmad; Susanti, Try; Aribangsa, Mhd Theo
JURTEKSI (Jurnal Teknologi dan Sistem Informasi) Vol 11, No 1 (2024): Desember 2024
Publisher : Universitas Royal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurteksi.v11i1.3234

Abstract

Abstract: Twitter occupies the top position of the most popular social media platform in Indonesia. Police and other related issues were the subject of much discussion. The aim of this research is to analyze public sentiment towards the National Police Agency using Twitter with the support vector machine method. The research started by crawling Twitter data. The data contains a total of 6,925 entries for three keywords. Next, we move on to the preprocessing stage consisting of (cleaning, case folding, tokenization, and filtering). Next is the tf-idf feature extraction stage, finally the classification and evaluation stage. The results of manual data inspection (73:27) showed accuracy of 70.66%, precision of 70.68%, and recall of 99.76%. Testing the second data (82:18), found accuracy 86%, precision 86.21%, recall 99.71%. The results of manual data checking (82:18) showed accuracy of 70.66%, precision of 70.68%, recall of 99.76%. Testing the second data (82:18), found accuracy 86%, precision 86.21%, recall 99.71%. From the data system testing results (80:20), accuracy was 87.55%, positive precision 87.53%, negative precision 88.24%, positive recall 99.48%, and negative recall. the rate is 99.48.% – The result is 21.43%. Data testing results (60:40) showed accuracy of 86.89%, positive precision of 86.84%, negative precision of 88.46%, positive recall of 99.61%, and negative recall of 16.43%. Single test data validation system (80:20), accuracy 87.55, overall test cross validation system (k fold 5 accuracy) 86.673%. Keywords: data mining;police agencies;support vector machines Abstrak: Twitter menduduki posisi teratas platform media sosial terpopuler di Indonesia. Polisi dan masalah terkait lainnya menjadi pokok bahasan banyak pembicaraan. Tujuan penelitian ini untuk menganalisis sentimen masyarakat terhadap Badan Kepolisian Nasional menggunakan Twitter dengan  metode support vector machine. Penelitian dimulai dengan  crawling  data Twitter. Data memuat total 6.925 entri dari tiga kata kunci. Selanjutnya beralih ke tahap preprocessing terdiri dari (pembersihan, pelipatan kasus, tokenisasi, dan pemfilteran). Selanjutnya tahap ekstraksi fitur tf-idf, terakhir tahap klasifikasi dan evaluasi. Hasil pemeriksaan data manual (73:27) menunjukkan akurasi 70,66%, presisi 70,68%, dan recall 99,76%. Menguji data kedua (82:18), menemukan akurasi 86%, presisi 86,21%, recall 99,71%. Hasil pemeriksaan data secara manual (82:18) menunjukkan akurasi 70,66%, presisi 70,68%, recall 99,76%. Menguji data kedua (82:18), menemukan akurasi 86%, presisi 86,21%, recall 99,71%. Dari hasil pengujian sistem data (80:20), akurasi 87,55%, presisi positif 87,53%, presisi negatif 88,24%, recall positif 99,48%, dan recall negatif. tarifnya adalah 99,48.% – Hasilnya 21,43%. Hasil pengujian data (60:40) menunjukkan akurasi 86,89%, presisi positif 86,84%, presisi negatif 88,46%, recall positif 99,61%, dan recall negatif 16,43%. Uji tunggal sistem validasi data (80:20), akurasi 87,55, uji keseluruhan sistem validasi silang  (akurasi k fold 5) 86,673%. Kata Kunci: data mining;instansi kepolisian;mesin vektor pendukung
ANALYSIS OF PUBLIC OPINION SENTIMENT REGARDING POLICE INSTITUTIONS BASED ON TWITTER USING THE SUPPORT VECTOR MACHINE (SVM) METHOD Sirojudin, Said Ahmad; Susanti, Try; Aribangsa, Mhd Theo
JURTEKSI (jurnal Teknologi dan Sistem Informasi) Vol. 11 No. 1 (2024): Desember 2024
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Royal Kisaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurteksi.v11i1.3234

Abstract

Abstract: Twitter occupies the top position of the most popular social media platform in Indonesia. Police and other related issues were the subject of much discussion. The aim of this research is to analyze public sentiment towards the National Police Agency using Twitter with the support vector machine method. The research started by crawling Twitter data. The data contains a total of 6,925 entries for three keywords. Next, we move on to the preprocessing stage consisting of (cleaning, case folding, tokenization, and filtering). Next is the tf-idf feature extraction stage, finally the classification and evaluation stage. The results of manual data inspection (73:27) showed accuracy of 70.66%, precision of 70.68%, and recall of 99.76%. Testing the second data (82:18), found accuracy 86%, precision 86.21%, recall 99.71%. The results of manual data checking (82:18) showed accuracy of 70.66%, precision of 70.68%, recall of 99.76%. Testing the second data (82:18), found accuracy 86%, precision 86.21%, recall 99.71%. From the data system testing results (80:20), accuracy was 87.55%, positive precision 87.53%, negative precision 88.24%, positive recall 99.48%, and negative recall. the rate is 99.48.% – The result is 21.43%. Data testing results (60:40) showed accuracy of 86.89%, positive precision of 86.84%, negative precision of 88.46%, positive recall of 99.61%, and negative recall of 16.43%. Single test data validation system (80:20), accuracy 87.55, overall test cross validation system (k fold 5 accuracy) 86.673%. Keywords: data mining;police agencies;support vector machines Abstrak: Twitter menduduki posisi teratas platform media sosial terpopuler di Indonesia. Polisi dan masalah terkait lainnya menjadi pokok bahasan banyak pembicaraan. Tujuan penelitian ini untuk menganalisis sentimen masyarakat terhadap Badan Kepolisian Nasional menggunakan Twitter dengan  metode support vector machine. Penelitian dimulai dengan  crawling  data Twitter. Data memuat total 6.925 entri dari tiga kata kunci. Selanjutnya beralih ke tahap preprocessing terdiri dari (pembersihan, pelipatan kasus, tokenisasi, dan pemfilteran). Selanjutnya tahap ekstraksi fitur tf-idf, terakhir tahap klasifikasi dan evaluasi. Hasil pemeriksaan data manual (73:27) menunjukkan akurasi 70,66%, presisi 70,68%, dan recall 99,76%. Menguji data kedua (82:18), menemukan akurasi 86%, presisi 86,21%, recall 99,71%. Hasil pemeriksaan data secara manual (82:18) menunjukkan akurasi 70,66%, presisi 70,68%, recall 99,76%. Menguji data kedua (82:18), menemukan akurasi 86%, presisi 86,21%, recall 99,71%. Dari hasil pengujian sistem data (80:20), akurasi 87,55%, presisi positif 87,53%, presisi negatif 88,24%, recall positif 99,48%, dan recall negatif. tarifnya adalah 99,48.% – Hasilnya 21,43%. Hasil pengujian data (60:40) menunjukkan akurasi 86,89%, presisi positif 86,84%, presisi negatif 88,46%, recall positif 99,61%, dan recall negatif 16,43%. Uji tunggal sistem validasi data (80:20), akurasi 87,55, uji keseluruhan sistem validasi silang  (akurasi k fold 5) 86,673%. Kata Kunci: data mining;instansi kepolisian;mesin vektor pendukung
Co-Authors Abul Walid Ahmad Zukron Alfikri Aini Qomariah Manurung Aisya, Afrawita Aisyah Aisyah Alamsyahbani Alamsyahbani Ali Murtadlo Almansyawwi, Muhammad Amini, Anafika Andesmora, Evan Andi Asari Anggraini, Wilu Tama Anggriani, Latusi Angraini, Rini Anita Anita Annisa, Rahma Ansari, Desi Apriani Yuyun Saputri Apriyanti, Mia Arfan Arfan Aribangsa, Mhd Theo Arif Ma’rufi Asvio, Nova Aulia Zafira Ziddan Badariah Badariah Badariah Badariah Badariah Badariah Baidilham, Baidilham Boby Syefrinando Chaniago, Fransisko Dahlia Dahlia Darma Putra Darma Putra Dasryannisa, Natijahurrohmah Deby Naila Dermawan, Julian Dewi Ulandari Diandara Oryza Diandara Oryza Dori Fitria Dwi Gusfarenie Elza Efdiningsih Eva Gusmira Faadila, Ayu Fahlevi, Dimas Fanisa, Fanisa Nurul Azizah farida farida Fathurrahman Rizky Fifi Murniasari Firamitha, Firamitha FIRMAN, ARHAM JUNAIDI Firmansyah, Rizqi Fristya Safitri, Alfina Gudje Hidayat, Defri Gusriani, Nanda Hamdan Hamdan Hanura Febriani Hidayat Hidayat Hidayat Hidayat IBARRA, FLORANTE P Imam Arifa’illah Syaiful Huda Indra Solihin Indrawata Wardhana Istikhomah, Anggini Istiqomah, Wahdatul Jessica Dasba Kurniawan KASMINI Khimalaya, Anifia Kholid Musyaddad Liana Fitriany Lily Nur Indah Sari M Husaini M. Adib Mubarak M. Syahran Jailani Ma'rufi, Arif Maddu, Nur Mila Mahardika, Rd. Nizar Diky Malini, Scendy Nawa Manurung, Aini Qomariah Mardiana Mardiana Martinis Yamin Marzuki Arsyad, Marzuki Maulia, Wirani Maulidi, Taufiqurrohman Maulina, Alfika Cahya Meri Suriyani Muhammad Ahmad Muhammad Sehan Muhammad Yusuf Muhammad Yusup Muhammad Zainuddin Nawi Mursida Mursida, Mursida Musa Mutamassikin, Mutamassikin Nabila Azzahra Nabila, Nabila Naldianti, Dila Natalia, Desfaur Ningsih, Tri Nining Nuraida Nining Nuraida Ni’mah, Ulfatun Novita sari Nur Aziszah, Selvia Nurdiansyah, Muhammad Ferdy Nurfadillah Nurfadillah Nurlinda Nurlinda Onia , Saifaldin Idris Oryza, Diandara Panthosa, Fitra Dwi PEPI MIRDAYANTI Permata, Aldes Cyntia Pramono, M. Agung Pratama, Akbar Gilang Prihatini, Nurul Primarani, Nabila Risa Purnama Purnama Putri, Arliana Fadillah Rahimah, Rahimah Rahmat Hidayat Rahmat Hidayat Rahmatuddini, Nurmiza Rahmi Putri Wirman Ramadhani, Yeni Riany, Hesti Riftiyanti Savitri Rika Aprianiwati Rini Warti Riri Rahmawati Rita Simatupang Rizki Khairati Rizky, Taufik Rahman Rohim, Fahmi Roihan, Muhammad Rulitawati, Rulitawati RUSMINI Sabrina Fitria Salahuddin Santini, Syarifa Aini Surnita Saputra, Jihan Saputri, Keken Nova Riswani Sari, Anggun Permata Sari, Defita Permata Sari, Meydina Kartika Sembiring, Dian Arisandy Eka Putra Sepriano Sepriano Setyawati, Ria Shabri Putra Wirman Shafna Dewi Silvia, Anggun Siregar, Fadly Shalsabil Sirojudin, Said Ahmad Sonendra, Kharendyawati Sri Wahyuni Suci Fitriani, Suci Suci Lestari Suraida Suraida Suraida Suraida Suraida Syafira, Friska Ananda Syafitrah, Dian Tessya Yunita Siregar Tiara Nova Sari Titi Muntasaro Tristianingrum, Indah Try Susanti Ulandari, Eva Yasin Vandri Ahmad Isnaini VANDRI AHMAD ISNAINI Wardani, Miki Wati, Ayu Widya Wiji Utami Wiji Utami, Wiji Wira Tama, Rima Yusrotul Aini Zailanti, Nova Zulkarnain, Nanda Karan zuriati, suci