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Permatasari, Hanifah
Universitas Duta Bangsa Surakarta
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Medicine & Pharmacology Physics Public Health Social Sciences Other

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Klasifikasi Ancaman Keamanan Siber Menggunakan Algoritma Naive Bayes Irwan Budianto; Nurchim Nurchim; Hanifah Permatasari
IJAI (Indonesian Journal of Applied Informatics) Vol 9, No 2 (2025)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/ijai.v9i2.104668

Abstract

Abstrak : Saat ini keamanan siber menjadi permasalahan utama didalam tata kelola keamanan informasi Pemerintah Daerah. Untuk mencegah terjadinya kerugian akibat serangan siber maka perlu dilakukan identifikasi dan klasifikasi terhadap ancaman siber secara cepat dan akurat. Sehingga diperlukan sebuah system untuk mengklasifikasikan ancaman siber yang terjadi. Penelitian ini adalah membangun sistem klasifikasi ancaman keamanan siber menggunakan algoritma Naive Bayes sehingga dapat dilakukan analisis data ancaman secara efektif dan mengklasifikasikan jenis ancaman dengan akurasi yang tinggi. Metode yang digunakan adalah pengumpulan dataset terkait log aktifitas serangan yang terekam di aplikasi Wazuh. Selanjutnya dilakukan preprocessing data untuk mendapatkan atribut yang sesuai dengan kebutuhan sistem. Penerapan algoritma Naive Bayes digunakan sebagai metode klasifikasi berdasarkan probabilitas atribut terhadap kategori ancaman. Hasil penelitian menunjukkan bahwa algoritma Naive Bayes mampu mengklasifikasikan ancaman keamanan siber dengan akurasi yang baik, sehingga dari system yang dibangun dapat ditentukan bahwa serangan yang terjadi pada area sistem operasi server atau aplikasi web serta mampu memberikan dukungan pengambilan keputusan yang lebih cepat dalam mitigasi serangan. Hasil pengujian menunjukkan performa yang sangat baik dari model Naive Bayes pada kedua kelas yaitu presisi=0.98, recall=1, f1-score=0.99, support=57.===================================================Abstract :Currently, cybersecurity is a major problem in the governance of regional government information security. To prevent losses due to cyber attacks, it is necessary to identify and classify cyber threats quickly and accurately. So a system is needed to classify cyber threats that occur. This study is to build a cybersecurity threat classification system using the Naive Bayes algorithm so that threat data analysis can be carried out effectively and classify types of threats with a high level of accuracy. The method used is collecting datasets related to attack activity logs recorded in the Wazuh application. Furthermore, data preprocessing is carried out to obtain attributes that match system needs. The Naive Bayes algorithm is implemented as a classification technique that evaluates the probability of attributes relative to threat categories. The findings indicate that this algorithm effectively categorizes cybersecurity threats with high accuracy. Consequently, the developed system can identify whether an attack targets the server operating system or the web application, while also enabling faster decision-making to support attack mitigation. The Naive Bayes model performs exceptionally well in both classes according to the test results, with precision=0.98, recall=1, f1-score=0.99, and support=57.
Sistem Pakar Dengan Metode Certainty Factor Untuk Mengetahui Gaya Belajar Anak Usia Dini Areta Reza Pradana; Hanifah Permatasari; Afu Ichsan Pradana
IJAI (Indonesian Journal of Applied Informatics) Vol 10, No 1 (2025)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/ijai.v10i1.103964

Abstract

Abstrak : Gaya belajar merupakan aspek penting dalam proses pembelajaran, terutama bagi anak usia dini yang berada pada tahap awal perkembangan kognitif. Identifikasi gaya belajar yang tepat dapat membantu pendidik dan orang tua dalam merancang metode pengajaran yang sesuai. Anak usia dini (0 - 6 tahun) masih berada dalam fase perkembangan awal, baik dari segi kognitif, motorik, bahasa, maupun sosial-emosional. Mereka belum mampu mengungkapkan preferensi belajar secara jelas, sehingga sulit untuk mengidentifikasi gaya belajarnya secara tepat. Penelitian ini bertujuan untuk menganalisis, merancang, dan membangun sistem p|ak|ar deng|an metode Cert|ainty F|actor untuk menget|ahui g|ay|a bel|aj|ar |an|ak usi|a dini. Sistem p|ak|ar b|aikny|a dilengk|api deng|an sebu|ah metode y|ang d|ap|at memberi nil|ai kep|asti|an p|ad|a output d|ari sebu|ah sistem, metode y|ang bis|a diter|apk|an d|al|am menghitung sebu|ah nil|ai ketid|akp|asti|an d|ari output sistem s|al|ah s|atuny|a |ad|al|ah metode CF (Cert|ainty F|actor). Deng|an metode CF ini penulis bis|a menentuk|an g|ay|a bel|aj|ar y|ang cocok untuk |an|ak usi|a dini. D|ari h|asil peneliti|an tersebut, metode Cert|ainty F|actor d|ap|at menghitung |at|au menentuk|an tingk|at su|atu nil|ai kep|asti|an d|ari g|ay|a bel|aj|ar |an|ak usi|a dini y|ang did|ap|at mel|alui seor|ang p|ak|ar. Sistem ini juga dapat digunakan sebagai media konsultasi mandiri, tanpa perlu keterlibatan langsung dari ahli psikologi pendidikan, sehingga lebih efisien dari segi waktu dan biaya. Berd|as|ark|an hasil penelitian terhadap salah satu gaya belajar pada anak, diperoleh nilai Certainty Factor (CF) sebagai berikut: gaya belajar visual 94,29%, auditori 94,10%, dan kinestetik 91,25%.==================================================Abstract : Learning style is an important aspect in the learning process, especially for early childhood who are in the early stages of cognitive development. Identifying the right learning style can help educators and parents in designing appropriate teaching methods. Early childhood (0 - 6 years) is still in the early developmental phase, both in terms of cognitive, motor, language, and social-emotional. They are not yet able to express their learning preferences clearly, making it difficult to identify their learning style precisely. This research aims to analyze, design, and build an expert system with the Certainty Factor method to determine the learning style of early childhood. An expert system should be equipped with a method that can give a certainty value to the output of a system, a method that can be applied in calculating an uncertainty value of system output is the CF (Certainty Factor) method. With this CF method, the author can determine the learning style that is suitable for early childhood. From the results of this study, the Certainty Factor method can calculate or determine the level of a certainty value of an early childhood learning style obtained through an expert. This system can also be used as an independent consultation media, without the need for direct involvement from educational psychology experts, making it more efficient in terms of time and cost. Based on the results of research on one of the learning styles in children, the Certainty Factor (CF) value is obtained as follows: visual learning style 94.29%, auditory 94.10%, and kinesthetic 91.25%.
Web-Based Financial Information System at Digimizu Digital Management Titin Listiani; Eko Purwanto; Hanifah Permatasari
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 1 (2025): APRIL 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i1.3329

Abstract

Digimizu Digital Management specializes in Software and Photography as well as Digital Content while delivering on-demand services. The company operates without a computerized information system for managing both transactions and financial reports. The company handles orders manually via WhatsApp or face-to-face interactions while transaction records are kept on paper and within Microsoft Excel files. Data loss becomes possible alongside human errors and inaccurate reporting while real-time data access and monitoring face constraints. The company needs a web-based financial information system which should combine transaction automation with customer data management functions alongside quick and accurate financial report generation. The development of the financial information system utilizes the SDLC method with the Waterfall model and system weaknesses analysis through the PIECES method with UML (Unified Modeling Language) support. This system implementation will bring efficiency to Digimizu Digital Management's business procedures while decreasing errors in recording and enabling real-time financial activity tracking which will enhance overall company performance.
User Centered Design Approach for Developing a Health Monitoring System for Posyandu Okta Ramma Saputri; Hanifah Permatasari; Vihi Atina
bit-Tech Vol. 8 No. 1 (2025): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i1.2737

Abstract

Indonesia continues to report high maternal and infant mortality rates, underscoring the urgent need for effective community-based health information systems, particularly in rural areas served by Posyandu (Integrated Health Service Posts). Despite their crucial role in primary healthcare delivery, many Posyandu still rely on manual data recording, resulting in fragmented documentation, delayed health risk detection, and inefficient decision-making processes. This study adopts a design research approach, utilizing the User-Centered Design (UCD) methodology to develop a web-based health monitoring system tailored for non-technical users, specifically Posyandu cadres in Dukuh Village, Boyolali Regency. The UCD process involved four iterative stages: understanding the user context, specifying user requirements, designing high-fidelity interface prototypes using Figma, and conducting usability evaluation through the System Usability Scale (SUS). The developed prototype includes key features such as digital patient data entry, real-time health examination input, visual health monitoring graphs, and automatic report generation by category and period. Usability testing was conducted with five Posyandu cadres who participated in defined usage scenarios and completed the SUS questionnaire. The resulting average SUS score was 84, categorized as “Excellent,” indicating that the system is intuitive, accessible, and efficient for users with limited technological experience. These findings demonstrate that the UCD approach effectively aligns system functionality with user needs, enhancing usability and supporting timely, data-driven health service decisions. This model offers significant potential for scalability and adaptation in other Posyandu settings, contributing to more integrated and responsive public health interventions at the village level.
Co-Authors Abdul Rohim Bayu Aji Prayogo Abdullah Sajad Aditya Gema Pratama Aditya Rachman Putra Afu Ichsan Pradana Agustina Niken Laraswati Agustina Srirahayu Ahmad Khairul Adi Aldova Herbryan Putra Alfisal Punjung Kurniawan Amad Tri Yanto Andi Saputro Andika Pratama Ardiansyah, Muhammad Irfan Areta Reza Pradana Arif Wicaksono Septyanto Arif Wicaksono Septyanto Armeta Eka Putri Wibowo Artdelia Pingkan Salsabilla Artdelia Pingkan Salsabilla Atina, Vihi Atmojo, Fernando Winantya Bagas Setiadi Bahrul Aziz Rifai Bangun Prajadi Cipto Utomo Berlian Agustina, Anggun Brian Bagus Apriansah Cikal Fauziah Fatin Sawitri Cipto Utomo, Bangun Prajadi Claudia Swastikawati Dear Whizkid Aziiz Deleviar, Angky Fay Dewangga Ranggi Wiku Didik Kurniawan Dinda Amelia Galuh Puspita Sari Dinda Rizky Asmara Dwi Hartanti Dwi Hartanti Dwi Prasetiyo Dwi Septieni Dwika Nur Arifin Eka Arya Saputra Eka Wijanarka Satata Putra Eko Purwanto Eko Purwanto Eko Purwanto Erlang Bagus Sadewa Faiq Muhammad, Nibras Fany Kusuma Dewi Farida Surya Jati Fatimah Naim Azahara Faulinda Ely Nastiti Febrianti, Krisna Fitriana Sekar Kinasih Ghani Ardiesta, Alif Gian, Habib Nur Habib Nur Gian Hanif Nur Ahmad Hanif Sangga Paramanandi Hany Arya Wardhany Hartanti, Dwi Hasanah, Herliyani Henokh Lugo Hariyanto Hidayatullah, Muhamad Ichsan Ichsan Pradana, Afu Ika Putri Pujianti Indah Nofikasari Inta Oktaviani Intan Oktaviani Irawan, Ridwan Dwi Irwan Budianto Janah, Selvi Miftakhul Joel Adikurnia Purnama Kukuh Supriyanto Kuncorowati, Dewi Liana Trihardianingsih Linda Kusuma Dewi Ma'ruf Nur Muhammad Maharani, Tiara Putri Maulindar, Joni Mochamad Saefudin Moh. Muhtarom Mohd, Farahwahida Muhamad Ilhamsyah Amara Ramadana Muhammad Alwan Nurdin Muhammad Exsa Nugroho Muhammad Hashfi Rafid Muttaqin Muhammad Khovivul Anam Muhtarom, Moh Nafaria Rohmandani Ni’mal ‘Abdu, Aghni Rizqi Nibras Faiq Muhammad Novita Widyasari Nur Indahsari, Reggie Nurchim Nurchim Nurchim Nurchim Nurlita, Catarina Ivanda Nurmalitasari Nurmalitasari Okta Ramma Saputri Otami Amalina Pipin Widyaningsih Pradana, Afu Ichsan Pramono Pramono Purwanto, Eko Putri Wibowo, Armeta Eka Rahadian, Dwiki Rasya Raihan Abdurrahim Al Ayyubi Ramadhan, Chandra Randis Wahyuni Rani Elsa Putri Ricky Eko Novianto Rico Yoga Pradana Ridho, Taufik Rini, Selfia Yustika Riyan Hidayah Robi Wariyanto Abdullah Rudi Susanto Sabar Sularno Salsabila Nurul Afifah Saputro, Khoirul Adi Saputro Sebastian, Angga Sejati, Ariya Putra Setiadi, Bagas Setiawan, Stevania Shandra Isti Kharisma Auliya Alamsyah Sigit Gunawan Siti Fatimah Siti Munawaroh Sofa Marwati Sri Mahardhika Pratiwi Sri Sumarlinda Srirahay, Agustina Stevania Frederica F.S Stevania Setiawan Sukma, Cahyaning Arum Surya Jati, Farida Syawaludin, M Ainur Telaga Nabila Putri Riyanto Titin Listiani Toni Iksanudin Tri Wulandari, Rahmawati Desi Triyono Triyono Triyono Triyono Triyono Utomo, Bangun Prajadi Cipto Vanya Tabitha Wahyu Cahya Adi Putra Wahyudi Wahyudi Wanda Fadillah Wibowo, Anita Carolina Yogi Setyawan Putra Pratama Yuda Abi Bagaskara Zeno Candragufa Muria