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All Journal Faktor Exacta JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Bulletin of Computer Science Research Abdi Jurnal Publikasi Journal of Artificial Intelligence and Digital Business OKTAL : Jurnal Ilmu Komputer dan Sains
Nurhasanah Nurhasanah
Universitas Pamulang
Astronomy Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Social Sciences Other

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Perancangan Sistem Pendukung Keputusan Untuk Menilai Kesiapan Siswa TK Dalam Masuk Sekolah Dasar Menggunakan Metode SAW Di TK Nurul Jannah Agung Firmansyah; Nurhasanah
OKTAL : Jurnal Ilmu Komputer dan Sains Vol 5 No 02 (2026): OKTAL : Jurnal Ilmu Komputer Dan Sains
Publisher : CV. Multi Kreasi Media

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Abstract

The process of assessing kindergarten students' readiness for elementary school at Nurul Jannah Kindergarten is still done manually, resulting in subjective and inconsistent results. This study aims to develop a web-based Decision Support System (DSS) using the Simple Additive Weighting (SAW) method to help teachers assess student readiness objectively and measurably. The system was developed using Extreme Programming (XP). This system uses five assessment criteria, which are then calculated through a process of normalization, weighting, and ranking. Implementation results indicate that the developed DSS produces more accurate, faster, and easier-to-understand assessments than manual methods, and assists teachers in determining student eligibility recommendations for elementary school entry
Sistem Pendukung Keputusan Pemilihan Supplier Terbaik Menggunakan AHP dan TOPSIS Ahmad Noval Ramadhan; Nurhasanah
OKTAL : Jurnal Ilmu Komputer dan Sains Vol 5 No 07 (2026): OKTAL : Jurnal Ilmu Komputer Dan Sains (INPRESS)
Publisher : CV. Multi Kreasi Media

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Abstract

Grocery retail continuity depends strongly on how a store selects suppliers. At Toko Sembako Basuki, assessment is still manual and personal, so ranking trails are hard to re-audit. A web Decision Support System was therefore built by combining Analytical Hierarchy Process (AHP) for criterion weighting and the TOPSIS method for ordering alternatives near an ideal solution. The stack is PHP Native, MySQL, Bootstrap, and TCPDF. Five aspects are scored: price as cost, plus product quality, delivery punctuality, service quality, and payment tenor as benefit. Verification uses Black Box Testing, White Box Testing, manual arithmetic cross check, and User Acceptance Testing. AHP remains consistent (Consistency Ratio 0.0391) and product quality leads with weight 0.5215. TOPSIS puts Supplier Sembako on top (Vi = 1.0000). Hence AHP–TOPSIS reduces subjectivity in supplier selection. 
Implementasi Sistem Pendukung Keputusan Prioritas Pengaduan Warga Menggunakan Metode TOPSIS Guruh Aji Saputra; Nurhasanah
OKTAL : Jurnal Ilmu Komputer dan Sains Vol 5 No 07 (2026): OKTAL : Jurnal Ilmu Komputer Dan Sains (INPRESS)
Publisher : CV. Multi Kreasi Media

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Abstract

Prioritizing residents' complaints is an essential aspect of improving the effectiveness of residential community management. At De Fatmawati Housing Estate, the prioritization process is still performed manually, making it difficult for administrators to determine which complaints should be addressed first when multiple reports are submitted simultaneously. This study implements a web-based Decision Support System (DSS) by applying the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method to support a more objective complaint prioritization process. The system was developed using the Agile Development methodology, while research data were collected through observation, interviews, and literature review. Complaint prioritization was conducted based on six evaluation criteria: urgency level, impact, complaint frequency, resource availability, handling cost, and complaint submission time. The implementation results demonstrate that the proposed system is capable of generating complaint priority rankings based on TOPSIS preference values, thereby supporting a more objective, transparent, and efficient decision-making process. Furthermore, the system provides an effective approach to addressing challenges in complaint prioritization while improving the overall effectiveness of complaint management within the residential community
Implementasi dan Evaluasi Performa Algoritma Naïve Bayes dalam Deteksi Dini Penyakit Diabetes Nurhasanah Nurhasanah; Nilovar Asyiah; Rahmawati Rahmawati
Bulletin of Computer Science Research Vol. 6 No. 4 (2026): June 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v6i4.1159

Abstract

Diabetes mellitus is one of the most prevalent chronic diseases worldwide and requires early detection to reduce the risk of severe complications through timely intervention. This study aims to implement and evaluate the performance of the Naïve Bayes algorithm in supporting the early detection of diabetes based on patients' health data. The study employed the Pima Indians Diabetes Dataset, consisting of 768 patient records with eight input attributes and one output attribute. During the preprocessing stage, zero values in physiological attributes were treated as missing values and replaced using the median of each respective attribute, followed by data consistency checking and dataset partitioning using the 80:20 split validation method. Model performance was evaluated using a confusion matrix with four performance metrics: accuracy, precision, recall, and F1-score. The experimental results showed that the Naïve Bayes algorithm achieved an accuracy of 88.31%, precision of 87.80%, recall of 90.00%, and an F1-score of 88.89%. These findings indicate that the proposed model performs well in classifying diabetes risk. The implementation of the model in a web-based application is expected to assist healthcare professionals and the general public as an early screening tool to support preliminary decision-making before comprehensive medical examination.
Penerapan Metode Naïve Bayes Pada Pengaruh Penggunaan Gadget Terhadap Nilai Siswa Sekolah Dasar Nurhalimah Nurhalimah; Nurhasanah Nurhasanah
Faktor Exacta Vol 18, No 1 (2025)
Publisher : LPPM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/faktorexacta.v18i1.27183

Abstract

Saat ini, penggunaan gadget telah menjadi bagian dari kehidupan sehari-hari, termasuk bagi siswa sekolah dasar. Gadget sering digunakan untuk menunjang proses pembelajaran, namun penggunaan yang berlebihan dan tidak terkontrol dapat berdampak negatif terhadap prestasi akademik siswa. Penelitian ini bertujuan untuk menganalisis pengaruh penggunaan gadget terhadap nilai akademik siswa sekolah dasar dengan menerapkan metode Naïve Bayes sebagai teknik klasifikasi. Metode Naïve Bayes digunakan untuk mengklasifikasikan data berdasarkan beberapa variabel, yaitu durasi penggunaan gadget, jenis aktivitas dengan gadget, dan pola belajar siswa. Hasil penelitian menunjukkan bahwa siswa yang menggunakan gadget dengan durasi yang terkontrol dan untuk ak-tivitas edukatif cenderung memiliki nilai akademik lebih tinggi dibandingkan dengan mereka yang menggunakan gadget secara berlebihan untuk hiburan. Selain itu, pola belajar yang lebih ter-struktur, seperti belajar secara mandiri atau dengan bimbingan, ber-kontribusi positif terhadap prestasi akademik siswa. Penelitian ini memberikan wawasan mengenai pentingnya pengawasan dan pengelolaan penggunaan gadget bagi siswa sekolah dasar. Dengan adanya hasil ini, diharapkan orang tua dan pendidik dapat lebih bijak dalam mengarahkan penggunaan gadget agar lebih optimal dalam mendukung proses pembelajaran.
IMPLEMENTASI WEBSITE SEDERHANA MENGGUNAKAN HTML DAN CSS SEBAGAI MEDIA INFORMASI DIGITAL SISWA MTS PONDOK PESANTREN IBNU UMAR TAHFIDZ BOARDING SCHOOL Nurhasanah; Laveryl Zavi Pratama; Noval Ilyas Immaduddin; Salim Nur Rohman; Raditya Prima; Marten Ricno Imuly; Muhamad Arul Ardiansyah; Adi Riskiyanto; Muhamad Rafif Fadilah Ratama; Rayhan Rizki Wijaya
Abdi Jurnal Publikasi Vol. 4 No. 5 (2026): Mei
Publisher : Abdi Jurnal Publikasi

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Abstract

Basic website development learning is an essential skill in the digital era, particularly for junior secondary school students. This Community Service Program (PKM) aims to implement simple website development learning using HTML and CSS as a digital information medium for students of MTS Pondok Pesantren Ibnu Umar Tahfidz Boarding School. The program was conducted through basic material delivery, website design introduction, and hands-on practice. An educative-participatory approach was applied by actively involving students in the learning process. Data were collected through observation and documentation. The results indicate improvements in students’ understanding of basic website concepts, technical skills, and learning motivation toward digital technology. This program demonstrates that practice-based simple website development learning is effective in supporting students’ digital literacy and can serve as a technology-based learning model in schools.
Implementasi dan Optimalisasi Metode Naive Bayes Dalam Sistem Deteksi Dini Penyakit Tiroid Nurhasanah Nurhasanah; Nilovar Asyiah; Okta Irawati
Journal of Information System Research (JOSH) Vol 6 No 4 (2025): July 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i4.7940

Abstract

This study aims to develop an early detection system for thyroid disease using the Naive Bayes algorithm. The dataset used is the Thyroid Disease Dataset from the UCI Machine Learning Repository, consisting of thousands of patient records. Prior to model training, the data undergoes preprocessing steps such as handling missing values, numerical normalization, and categorical encoding. The classification process involves calculating the prior probability, likelihood, and posterior probability for each class: normal, hypothyroid, and hyperthyroid. The system also presents the probability percentage for each class as an automated diagnosis result. Model accuracy is evaluated using a Confusion Matrix, achieving an accuracy score of 98.01% on the test data. These results indicate that the proposed approach can effectively and accurately classify thyroid conditions for early diagnosis purposes.
Analisis Peforma Algoritma Kompresi Huffman, LZW, BZIP2, Zstandard dan Brotli dalam Efisiensi Penyimpanan Data dan Transfer Data Okta Irawati; Nurhasanah Nurhasanah; Siti Fatul Zahrani; Ayu Talenta Lumbantoruan
RIGGS: Journal of Artificial Intelligence and Digital Business Vol. 4 No. 2 (2025): Mei - Juli
Publisher : Prodi Bisnis Digital Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/riggs.v4i2.1396

Abstract

Penelitian ini bertujuan untuk mengevaluasi performa beberapa algoritma kompresi data dalam kaitannya dengan efisiensi penyimpanan dan kecepatan transfer data. Fokus utama terletak pada perbandingan antara efisiensi hasil kompresi, durasi proses kompresi-dekompresi, serta dampaknya terhadap waktu pengiriman data. Untuk mendukung analisis, digunakan teori dasar dari teknik kompresi seperti algoritma JPEG, Discrete Cosine Transform (DCT), dan Huffman Coding yang sering digunakan dalam pengolahan gambar digital.Data diperoleh melalui uji coba terhadap berbagai jenis file gambar digital (JPG, TIFF, GIF), kemudian dianalisis secara kualitatif dengan meninjau rasio kompresi, durasi proses, serta pengaruh karakteristik data terhadap efektivitas kompresi. Hasil analisis menunjukkan bahwa pemilihan algoritma yang sesuai (contohnya, adaptasi JPEG pada file non-JPG) dapat meningkatkan efisiensi ruang simpan hingga 40% dan mempercepat pengiriman data. Namun, efektivitas setiap algoritma sangat bergantung pada tingkat redundansi dan jenis format file yang digunakan.
Co-Authors Adi Riskiyanto Agung Firmansyah Ahmad Noval Ramadhan Ayu Talenta Lumbantoruan Guruh Aji Saputra Laveryl Zavi Pratama Marten Ricno Imuly Muhamad Arul Ardiansyah Muhamad Rafif Fadilah Ratama Nilovar Asyiah Noval Ilyas Immaduddin Nurhalimah Nurhalimah Okta Irawati Raditya Prima Rahmawati Rahmawati Rayhan Rizki Wijaya Salim Nur Rohman Siti Fatul Zahrani