Fuzzy Expert System for Decission Support to Diagnosis Leukemia
Leukemia is a cancer of the blood and bone marrow. In leukemia, the bone marrow produces too many abnormal white blood cells. These abnormal cells cannot fight infections well and can displace healthy blood cells, which can cause anemia and bleeding. In this study, a fuzzy method will be implemented...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Pusat Penelitian dan Pengabdian Masyarakat (P3M), Politeknik Negeri Cilacap
2025-06-01
|
| Series: | Journal of Innovation Information Technology and Application |
| Subjects: | |
| Online Access: | https://ejournal.pnc.ac.id/index.php/jinita/article/view/2349 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850086123324309504 |
|---|---|
| author | Linda Perdana Wanti Nur Wachid Adi Prasetya Zahrun Nafisa Rahmat Mulyadi Muhammad Ramadani |
| author_facet | Linda Perdana Wanti Nur Wachid Adi Prasetya Zahrun Nafisa Rahmat Mulyadi Muhammad Ramadani |
| author_sort | Linda Perdana Wanti |
| collection | DOAJ |
| description | Leukemia is a cancer of the blood and bone marrow. In leukemia, the bone marrow produces too many abnormal white blood cells. These abnormal cells cannot fight infections well and can displace healthy blood cells, which can cause anemia and bleeding. In this study, a fuzzy method will be implemented to diagnose leukemia and the results will later be compared with expert diagnoses. Fuzzy logic was chosen because it allows for degrees of truth between 0 (completely false) and 1 (completely true) and it is suitable for situations where human expertise relies on experience and judgment rather than fixed rules. Fuzzy systems can analyze large amounts of data quickly, thereby accelerating the diagnosis and decision-making process, especially when used in medical decision support systems. This study produced a leukemia diagnosis accuracy of 88.83% when compared with the results of expert diagnoses using the same symptom and sample data. |
| format | Article |
| id | doaj-art-79288aff3c8042d5bed07558d46ab4a2 |
| institution | DOAJ |
| issn | 2716-0858 2715-9248 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Pusat Penelitian dan Pengabdian Masyarakat (P3M), Politeknik Negeri Cilacap |
| record_format | Article |
| series | Journal of Innovation Information Technology and Application |
| spelling | doaj-art-79288aff3c8042d5bed07558d46ab4a22025-08-20T02:43:33ZengPusat Penelitian dan Pengabdian Masyarakat (P3M), Politeknik Negeri CilacapJournal of Innovation Information Technology and Application2716-08582715-92482025-06-0171263410.35970/jinita.v7i1.23491485Fuzzy Expert System for Decission Support to Diagnosis LeukemiaLinda Perdana Wanti0Nur Wachid Adi Prasetya1Zahrun Nafisa2Rahmat Mulyadi3Muhammad Ramadani4Politeknik Negeri CilacapPoliteknik Negeri CilacapPoliteknik Negeri CilacapPoliteknik Negeri CilacapPoliteknik Negeri CilacapLeukemia is a cancer of the blood and bone marrow. In leukemia, the bone marrow produces too many abnormal white blood cells. These abnormal cells cannot fight infections well and can displace healthy blood cells, which can cause anemia and bleeding. In this study, a fuzzy method will be implemented to diagnose leukemia and the results will later be compared with expert diagnoses. Fuzzy logic was chosen because it allows for degrees of truth between 0 (completely false) and 1 (completely true) and it is suitable for situations where human expertise relies on experience and judgment rather than fixed rules. Fuzzy systems can analyze large amounts of data quickly, thereby accelerating the diagnosis and decision-making process, especially when used in medical decision support systems. This study produced a leukemia diagnosis accuracy of 88.83% when compared with the results of expert diagnoses using the same symptom and sample data.https://ejournal.pnc.ac.id/index.php/jinita/article/view/2349fuzzy logicaldiagnosisdecission supportleukemiaexpert system |
| spellingShingle | Linda Perdana Wanti Nur Wachid Adi Prasetya Zahrun Nafisa Rahmat Mulyadi Muhammad Ramadani Fuzzy Expert System for Decission Support to Diagnosis Leukemia Journal of Innovation Information Technology and Application fuzzy logical diagnosis decission support leukemia expert system |
| title | Fuzzy Expert System for Decission Support to Diagnosis Leukemia |
| title_full | Fuzzy Expert System for Decission Support to Diagnosis Leukemia |
| title_fullStr | Fuzzy Expert System for Decission Support to Diagnosis Leukemia |
| title_full_unstemmed | Fuzzy Expert System for Decission Support to Diagnosis Leukemia |
| title_short | Fuzzy Expert System for Decission Support to Diagnosis Leukemia |
| title_sort | fuzzy expert system for decission support to diagnosis leukemia |
| topic | fuzzy logical diagnosis decission support leukemia expert system |
| url | https://ejournal.pnc.ac.id/index.php/jinita/article/view/2349 |
| work_keys_str_mv | AT lindaperdanawanti fuzzyexpertsystemfordecissionsupporttodiagnosisleukemia AT nurwachidadiprasetya fuzzyexpertsystemfordecissionsupporttodiagnosisleukemia AT zahrunnafisa fuzzyexpertsystemfordecissionsupporttodiagnosisleukemia AT rahmatmulyadi fuzzyexpertsystemfordecissionsupporttodiagnosisleukemia AT muhammadramadani fuzzyexpertsystemfordecissionsupporttodiagnosisleukemia |