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All Journal Jurnal Edukasi dan Penelitian Informatika (JEPIN) International Journal of Law Reconstruction Jurnal Pendidikan Informatika dan Sains JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Al-Khidmah CYBERNETICS BULETIN AL-RIBAATH JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) GERVASI: Jurnal Pengabdian kepada Masyarakat Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Progresif: Jurnal Ilmiah Komputer JUSTINDO (Jurnal Sistem dan Teknologi Informasi Indonesia) Jurnal Teknika Jurnal Abdi Insani JIKA (Jurnal Informatika) Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) JUTECH : Journal Education and Technology JUSTIN (Jurnal Sistem dan Teknologi Informasi) Joutica : Journal of Informatic Unisla Journal of Artificial Intelligence and Engineering Applications (JAIEA) Jurnal Riset Rumpun Ilmu Teknik (JURRITEK) Kohesi: Jurnal Sains dan Teknologi SmartComp Jurnal Informatika Polinema (JIP) Journal of Multidiscipline and Collaboration Research JUSTINDO (Jurnal Sistem dan Teknologi Informasi Indonesia)
Alkadri, Syarifah Putri Agustini
Universitas Muhammadiyah Pontianak
Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering 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 Energy Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Physics Public Health Social Sciences Other

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Classification of Fetal Health Using the K-Nearest Neighbor Method and the Relieff Feature Selection Method Anita; Asrul Abdullah; Syarifah Putri Agustini Alkadri
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 4 No. 2 (2025): February 2025
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v4i2.794

Abstract

Understanding fetal health early can reduce risks to the pregnancy and the womb. Identifying correlations among factors influencing fetal well-being helps medical professionals clarify key impacts. Quantified relationships between features and labels also guide future research. This study focuses on three aspects: evaluating KNN model performance with and without ReliefF feature selection, analyzing the impact of feature removal, and assessing ReliefF's ability to identify critical features for fetal health classification.The research begins by framing fetal health classification as a supervised machine learning task using labeled datasets. A cardiotocographic dataset from the UCI Machine Learning Repository supports data collection. Initial analysis identifies data types and detects outliers, followed by preprocessing, feature selection, and KNN model training. Model testing uses metrics such as accuracy and recall. Results show the KNN model with ReliefF features achieves an accuracy of 0.896. Testing a pruned model by removing high-importance features slightly reduces accuracy to 0.866. These findings confirm ReliefF's effectiveness in identifying essential features and optimizing model efficiency without compromising quality. This study underscores ReliefF's role in improving KNN performance for fetal health classification.
New Employee Selection System using WP and SAW Methods Based on Web at PT Lanang Agro Bersatu Ria Sapitri; Syarifah Putri Agustini Alkadri; Putri Yuli Utami
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 4 No. 2 (2025): February 2025
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v4i2.808

Abstract

Employees are valuable assets for a company, requiring careful selection based on educational background and experience to ensure proper placement and avoid issues. At PT Lanang Agro Bersatu, the selection process involves approximately 30 candidates monthly. This study developed a web-based employee selection system using the Weighted Product (WP) and Simple Additive Weighting (SAW) methods. The system aims to calculate weight values for criteria such as Education, Work Experience, Age, Health, GPA, Academic Tests, and Psychological Tests, providing accurate rankings to simplify decision-making. The top candidate, Khusnul Wasillah, achieved the highest preference value of 0.1563, calculated through combined SAW and WP methods. System testing using black box and equivalence partitioning methods showed 100% accuracy.
Decision Support System for Selection of Achieving Students Using MetDecision Support System for Selection of Achieving Students Using Method Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) Web Based Isra Pebrianti; Syarifah Putri Agustini Alkadri; Asrul Abdullah
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 4 No. 2 (2025): February 2025
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v4i2.829

Abstract

The selection of outstanding students identifies the best students based on grades and achievements to recommend them for college entrance. This process often encounters challenges due to numerous determining factors, leading to potential biases in decision-making. A Decision Support System (DSS) helps address this by utilizing data and decision models to resolve structured and unstructured problems. This study applies the MOORA (Multi-Objective Optimization on the basis of Ratio Analysis) method, using criteria such as attendance, attitude scores, knowledge and skills component values, extracurricular/organizational involvement, and achievements. The DSS identified 40 outstanding students at SMA Negeri 1 Tayan Hulu, with the highest preference score of 0.0819 achieved by Indah Prasetyaning Tias. Functional testing was conducted using the black-box method with Equivalence Partitioning, and accuracy testing through MAPE showed a calculation accuracy rate of 2.79%.
MEMBANGUN KREATIVITAS DAN KETERAMPILAN DIGITAL MENGGUNAKAN PLATFORM GAMIFIKASI MENGGUNAKAN WORLDWALL DAN KAHOOT Alkadri, Syarifah Putri Agustini; Muhammad Dwi Ramadhianto
GERVASI: Jurnal Pengabdian kepada Masyarakat Vol. 9 No. 1 (2025): GERVASI: Jurnal Pengabdian Kepada Masyarakat
Publisher : LPPM IKIP PGRI Pontianak

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31571/gervasi.v9i1.8823

Abstract

Pembelajaran di SMP Muhammadiyah 2 Pontianak menghadapi tantangan berupa minimnya pemanfaatan teknologi, materi yang monoton, dan rendahnya partisipasi siswa. Solusi yang ditawarkan adalah penggunaan game edukasi berbasis platform gamifikasi seperti kahoot dan wordwall yang bertujuan meningkatkan kreativitas dan keterampilan digital guru dalam mengembangkan media pembelajaran interaktif. Metode yang digunakan adalah community development melalui lima tahap: perencanaan, tindakan, observasi dan evaluasi, refleksi, serta persiapan luaran. Hasil menunjukkan peningkatan pemahaman guru sebesar 75% dan menghasilkan media pembelajaran sebagai luaran. Penggunaan game edukasi terbukti efektif dalam menciptakan ekosistem belajar yang kreatif dan menyenangkan.
PENGAMANAN DATA MENGGUNAKAN VIGENERE CIPHER DAN TABEL ASCII BERBASIS WEB Ajmi, Nur Dzakiyyah; Sucipto, Sucipto; Alkadri, Syarifah Putri Agustini
Jurnal Informatika Vol 9, No 2 (2025): JIKA (Jurnal Informatika)
Publisher : University of Muhammadiyah Tangerang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31000/jika.v9i2.13527

Abstract

Penyalahgunaan informasi merupakan salah satu dampak negatif dari perkembangan teknologi yang berkembang pesat saat ini, oleh karena itu perlu dilakukan pengamanan informasi agar tidak dapat diakses oleh orang-orang yang tidak bertanggung jawab. Kriptografi merupakan ilmu yang mempelajari tentang penyandian data dan pengamanan data. Salah satu cara agar data informasi tersebut aman dan terhindar dari pembobolan adalah dengan memberikan password pada file data. Pada penelitian ini akan menggunakan algoritma vigenere cipher pada proses enkripsi. Namun, algoritma Vigenere Cipher merupakan algoritma klasik yang dimana pada metode algoritma klasik ini telah banyak diketahui oleh cryptanalysis yaitu algoritma yang terlalu sederhana. Untuk menghindari hal tersebut, penelitian ini akan memodifikasi algoritma Vigenere Cipher dengan Algoritma ASCII. Dengan demikian, hasil modifikasi penggabungan dua algoritma tersebut dapat memberikan keamanan pada file data dan membuat ciphertext semakin sulit untuk dibobol. Hasil yang akan dicapai dari penelitian ini adalah terciptanya sebuah web yang dapat menyandikan data dan informasi.
Analisis sentimen climate change menggunakan support vector machine Utami, Putri Yuli; Alkadri, Syarifah Putri Agustini; Otafyani, Mega
Jurnal Pendidikan Informatika dan Sains Vol. 14 No. 1 (2025): Jurnal Pendidikan Informatika dan Sains
Publisher : IKIP PGRI Pontianak

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31571/saintek.v14i1.8674

Abstract

Perubahan iklim adalah isu global dengan dampak signifikan pada berbagai aspek kehidupan. Tujuan penelitian ini melakukan analisis sentimen terhadap data publik dan mengevaluasi performa model dalam klasifikasi analisis sentimen. Jumlah data teks terkait isu ini terus meningkat, sehingga text mining menjadi pendekatan penting untuk menganalisis data secara mendalam. Algoritma seperti Support Vector Machine (SVM) memberikan solusi inovatif untuk klasifikasi dokumen dan analisis sentimen dalam domain ini. Tahapan penelitian dimulai dari pengumpulan data, pengelolaan data, pre-processing data, pembobotan kata (TF-IDF), analisis sentimen dengan model Support vector machine, serta evaluasi hasil. Support Vector Machine  dengan rasio 80:20  menunjukkan performa lebih tinggi dengan akurasi 0,88, precision (weighted avg) 0,89, recall (weighted avg) 0,88, Nilai K= 10, F1-score (weighted avg) 0,88, ROC-AUC 0,99 menunjukkan kinerja model baik.
Implementasi Information Retrieval System Aksesibilitas Buku di Perpustakaan dengan Metode Dice Similarity Vika Ummu Hani; Syarifah Putri Agustini Alkadri; Rachmat Wahid Saleh Insani
JURAL RISET RUMPUN ILMU TEKNIK Vol. 4 No. 1 (2025): April : Jurnal Riset Rumpun Ilmu Teknik
Publisher : Pusat riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jurritek.v4i1.4561

Abstract

The problem of accessibility and efficiency of book search is still a major challenge in school libraries, especially those that still rely on manual systems. This study aims to implement and test the effectiveness of an information retrieval system (IRS) based on the Dice Similarity method in the SMA Negeri 1 Siantan Library, West Kalimantan. The research method used is experimental descriptive quantitative, with data collection through observation, interviews, and documentation, as well as system testing on collection data and library user activities. The system was developed using the Laravel framework and MySQL database, and evaluated using precision and recall metrics. The results showed that the system has a Precision value of 100% and a variable Recall value, with the highest value of 66.66% and the lowest of 14.28%. The implementation of this system significantly speeds up the search process, minimizes recording errors, and increases user satisfaction. The findings recommend the adoption of Dice Similarity-based IRS as an applicable solution for school libraries in supporting literacy and easy access to information. The findings are expected to be a reference for the development of library information systems in educational environments with limited resources.
Klasifikasi Tingkat Kepuasan Pelayanan Pembuatan Paspor Menggunakan Algoritma Naïve Bayes Dini Oktaviani; Syarifah Putri Agustini Alkadri; Sucipto Sucipto
JURAL RISET RUMPUN ILMU TEKNIK Vol. 4 No. 1 (2025): April : Jurnal Riset Rumpun Ilmu Teknik
Publisher : Pusat riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jurritek.v4i1.4572

Abstract

This research is motivated by the importance of improving the quality of passport making services at the Pontianak City Immigration Office which still faces obstacles such as complicated procedures, limited quotas, lack of officer direction, and mismatches in passport collection schedules that cause public dissatisfaction. This research aims to classify the level of satisfaction of passport making services using the Naïve Bayes algorithm, measure classification accuracy, and develop a website-based system that helps evaluate and improve service quality effectively and efficiently. The method used is a quantitative approach with data collection through questionnaires, interviews, and direct observation of 205 respondents, then the data is processed using the Naïve Bayes algorithm which assumes independence between variables to classify satisfaction levels based on variables such as officer friendliness, officer ability, ease of procedure, and timeliness of service. The main findings show that the Naïve Bayes algorithm is able to classify satisfaction levels with 73% accuracy, 76% precision, 70% recall, and 73% F1-score, signaling the effectiveness of this method in identifying community satisfaction patterns. However, the results also indicate the need for improvement in user interface aspects and system responsiveness so that the system can be widely accepted and provide optimal benefits. The implication of this research is that the application of Naïve Bayes-based data mining methods can be an effective tool in evaluation and decision-making to improve the quality of public services, especially in the field of passport making, and encourage the development of interactive and empirical data-based public service information systems.
Penerapan Metode Certainty Factor Dalam Sistem Pakar Deteksi Kerusakan Truk Berbasis Android Hasim, Wahyudi; Syarifah Putri Agustini Alkadri
JUSTINDO (Jurnal Sistem dan Teknologi Informasi Indonesia) Vol. 8 No. 2 (2023): JUSTINDO
Publisher : Universitas Muhammadiyah Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32528/justindo.v8i2.771

Abstract

Perkembangan dunia otomotif hingga saat ini meningkat dengan pesat, salah satu jenis kendaraan yaitu truk Mitsubishi Canter. Masalah yang terjadi dalam menangani kerusakan pada kendaraan truk, seperti tidak adanya mekanik ditempat, jumlah bengkel dan mekanik yang terbatas, serta mekanik yang belum memiliki banyak pengalaman sering kali mekanik kesulitan dalam mentukan kerusakan yang terjadi pada kendaraan truk. Masalah ini menjadi perhatian karena dapat mempengaruhi kinerja truk dan merugikan pemilik truk. Dengan menerapkan metode certainty factor untuk perhitungan kemungkinan kerusakan berdasarkan gejala yang dipilih maka akan menerima hasil berupa kemungkinan terbesar kerusakan yang terjadi sehingga bisa mengetahui keruskan apa yang dialami pada kendaraanya. Hasil perhitungan ditampilkan berupa persentase kerusakan yang dihitung berdasarkan nilai MB dan MD yang telah ditetapkan oleh sistem.Aplikasi sistem Pakar ini dapat memberikan informasi kerusakan mendeteksi dan mengetahui kerusakan pada mesin truk Mitsubishi canter yang sedang menalami kerusakan, maka sistem pakar akan menampilkan hasil akhir berupa keterangan kerusakan, solusi perbaikan, sehingga mekanik atau pengguna bisa melakukan perbaikan sesuai masalah yang dialami.
Development of a Web-Based Thesis Repository for Information Technology Education Students Permana, Ryan; Alkadri, Syarifah Putri Agustini
Journal of Multidiscipline and Collaboration Research Vol. 2 No. 2 (2025)
Publisher : Yayasan Pendidikan dan Pengembangan Harapan Ananda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58740/jmcr.v2i2.625

Abstract

This study aims to develop a Web-Based Thesis Repository System for the Information Technology Education Study Program at Universitas PGRI Pontianak. The system was designed to address challenges in manual thesis archiving and limited accessibility for students seeking academic references. The research employed the Research and Development (R&D) approach using the ADDIE model, which includes five systematic stages: Analysis, Design, Development, Implementation, and Evaluation. Data were collected through expert validation and user feedback. The system provides key features such as user registration, secure login, thesis upload, metadata management, and advanced search functionality. Validation results from two product experts and one content expert indicated that the system achieved an average product score of 3.34 and a content score of 3.38, both categorized as “Good.” The findings demonstrate that the developed repository is feasible, efficient, and effective in managing digital thesis data while enhancing accessibility and transparency in academic information retrieval. This repository supports digital transformation in higher education by promoting sustainable knowledge management and improving research visibility. The system is recommended for broader implementation and future development through integration with institutional databases and cloud-based storage for enhanced scalability and security.
Co-Authors Acep Supriyanto Agustian Agustian Ajmi, Nur Dzakiyyah Alda Cendekia Siregar Alkhairi, Muhammad Ghozy Andalas Rivaldi Permana Anita Asrul Abdullah Barry Ceasar Octariadi Dila Adellia Dini Oktaviani Eko Julianto Fakhruzi, Izhan Hasim, Wahyudi Hazilina, Hazilina Heni Kriswanti Isra Pebrianti Istikoma Istikoma Kalsum, Dayang Nur Kristin Damay Asmara Masroni Maysa, Ade Medi, Medi Muhammad Dwi Ramadhianto Novianti Novianti Otafyani, Mega Putri Yuli Utami Rachmat Wahid Saleh Insani Ria Sapitri Rizka Amalia Rizky Wahyu Prasetio Ruhama, Ufi Ryan Permana Ryani Yulian Setiaji, Wanda Primadita Sucipto Sucipto Sucipto Sucipto Sucipto Sucipto Sucipto Sumirah Sumirah Sumirah Sumirah Utami, Putri Yuli vera vibiola Vika Ummu Hani Wahyu Nugroho Wiguna, Seftyan Yulrio Brianorman