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All Journal IKRA-ITH Informatika : Jurnal Komputer dan Informatika Mukhtabar: Journal of Medical Laboratory Technology
Nurhadi, Muhammad Ihsan
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Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Health Professions Immunology & microbiology

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Evaluation of Quality Indicators with Lean Six Sigma In Pre and Post Analytical Laboratories Nurhadi, Muhammad Ihsan; Ridwanna, Surya; Rinaldi, Sonny Feisal; Nurhayati, Betty
Mukhtabar Journal of Medical Laboratory Technology Vol 3 No 1 (2025): Mukhtabar: Journal of Medical Laboratory Technology (April 2024)
Publisher : LPPM STIKes Muhammadiyah Ciamis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52221/mjmlt.v3i1.795

Abstract

Background & Objective: Medical laboratories have an important role of 60-70% in diagnosis, patient monitoring, and prevention and treatment of diseases. Therefore, the laboratory must maintain and ensure the quality of service process. This study aims to determine the sigma value and identify waste in pre and post analytical in the laboratory, as well as determine Improvement proposals in order to reduce errors pre and post analytical laboratory. Method: This research design is descriptive study that Analyzes the process and quality indicators at pre and post analytical with the Lean Six Sigma approach, which is a combination of Lean methods that focus on eliminating waste and Six Sigma that focuses on eliminating defects. This research was conducted as a process Improvement effort with five Six Sigma work steps (DMAIC) and identified eight types of waste (DOWNTIME). Result: The results showed that the sigma value at pre and post analytical was 4.6 and 3.5 Sigma, and total sigma value for pre-post analytical was 4.3 Sigma so that both had not met the minimum target achievement of 5 Sigma (Excellent). There are two quality indicators that require improvement and enhancement including suitability of sample and TAT. The results also show that there are 4 wastes, consisting of 1 Defects, 1 Waiting, and 2 Not Utilizing Employees Knowledge. Conclusion: Proposed Improvements are then given so that all waste identified in this study can be minimized so that the achievement of sigma quality indicators can increase.
MEMBANGUN WEBSITE PEMBELAJARAN MATEMATIKA BERDASARKAN PREDIKSI GAYA BELAJAR SISWA PADA SDN KEBON MANGGIS 08 JAKARTA Nurhadi, Muhammad Ihsan; Thantawi, Ahmad Muhammad
IKRA-ITH Informatika : Jurnal Komputer dan Informatika Vol. 10 No. 2 (2026): IKRAITH-INFORMATIKA Vol 10 No 2 Juli 2026
Publisher : Fakultas Teknik Universitas Persada Indonesia YAI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37817/ikraith-informatika.v10i2.5453

Abstract

Penelitian ini mengembangkan sistem pembelajaran berbasis web yang adaptif untuk mengidentifikasigaya belajar siswa menggunakan algoritma Naïve Bayes. Sistem mengklasifikasikan siswa ke dalamtiga tipe gaya belajar: visual, auditori, dan kinestetik, berdasarkan jawaban kuesioner. Dengan teknikdata mining, sistem mempersonalisasi materi pembelajaran, meningkatkan keterlibatan dan pemahamansiswa dalam mata pelajaran matematika. Guru dapat mengunggah konten yang disesuaikan, sementarasiswa menerima materi sesuai preferensi belajar. Evaluasi menunjukkan bahwa pendekatan inimeningkatkan pemahaman siswa dan menyediakan solusi efisien untuk pendidikan di tingkat sekolahdasar. Penelitian ini menyoroti potensi data mining dalam menciptakan lingkungan pembelajaran yanginklusif dan efektif.
Co-Authors Nurhayati, Betty Ridwanna, Surya Rinaldi, Sonny Feisal Thantawi, Ahmad Muhammad