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All Journal Jurnal Teknologi Informasi dan Komunikasi
Haq, Haris Nizhomul
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Computer Science & IT Control & Systems Engineering

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SISTEM INFORMASI TUNJANGAN PENDAPATAN KEPEGAWAI DI KANTOR KECAMATAN MENGGUNAKAN FRAMEWORK CODEIGNITER Selviani, Rima; Haq, Haris Nizhomul; Sobari, Dicky Iskandar
Jurnal Teknologi Informasi dan Komunikasi Vol 17 No 1 (2024): April
Publisher : STMIK Subang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47561/a.v17i1.256

Abstract

In the current era of technological advancements, the demand for information has significantly risen across various facets of life. The Employee Income Allowance Information System (TPP) implemented at the Subang Sub-District Office encompasses comprehensive data, including employee profiles, attendance records, TPP reports, and employee assessments. This system facilitates employees in efficiently accessing and reviewing attendance and TPP report data. The implementation is carried out using CodeIgniter, PHP, and MySQL technologies.
Evaluasi Performa Naïve Bayes dan CART pada Klasifikasi Kualitas Tahu Nugraha, Luthfy Akmal; Jupriyanto, Jupriyanto; Haq, Haris Nizhomul; Wijaya, Anderias Eko; Ahmad, Hermansyah Nur
Jurnal Teknologi Informasi dan Komunikasi Vol 18 No 2 (2025): October
Publisher : STMIK Subang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47561/jtik.v18i2.328

Abstract

To remain competitive in the global market, tofu producers must ensure consistent product quality. Sumber Barokah Tofu Factory, a longstanding supplier of high-nutrient tofu, faces challenges in maintaining quality throughout the production process. This study compares the performance of Naïve Bayes and Classification and Regression Trees (CART) algorithms in classifying tofu quality using a dataset collected from a factory, which contains both high-quality and low-quality tofu samples. The research methodology encompasses problem identification, data collection, preprocessing, classification, validation, evaluation, and conclusion. Cross-validation was employed for model validation, and confusion matrices were utilised to assess precision, recall, and F1-score. Experimental results indicate that Naïve Bayes achieved an Accruracy of 91%, precision of 100%, recall of 85%, and F1-score of 92%, while CART achieved an Accruracy of 86%, precision of 70%, recall of 100%, and F1-score of 82%. These results suggest that Naïve Bayes is more suitable for classifying tofu quality in this context.
Co-Authors Ahmad, Hermansyah Nur Anderias Eko Wijaya Jupriyanto Jupriyanto, Jupriyanto Nugraha, Luthfy Akmal Selviani, Rima Sobari, Dicky Iskandar