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All Journal Infotek : Jurnal Informatika dan Teknologi ABSYARA: Jurnal Pengabdian Pada Masyarakat
Intan Komala Dewi Patwari
Universitas Hamzanwadi
Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Earth & Planetary Sciences Education Engineering Environmental Science Library & Information Science Mathematics Other

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Komparasi Metode Klasifikasi Data Mining Decision Tree dan Naïve Bayes Untuk Prediksi Penyakit Diabetes Permana, Baiq Andriska Candra; Patwari, Intan Komala Dewi
Infotek : Jurnal Informatika dan Teknologi Vol 4, No 1 (2021): Infotek : Jurnal Informatika dan Teknologi
Publisher : Fakultas Teknik Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (819.743 KB)

Abstract

Diabetes is a group of metabolic diseases which is indicated by the occurrence of hyperglycemia caused by abnormalities in insulin secretion in the body. Many deaths are caused by diabetes, if this disease is not treated immediately, diabetes can cause damage to other organs such as blindness, stores, heart problem and even kidney problem. A best method is needed in classifying diabetes in order to detect diabetes early. Research related to the classification of diabetes using several calcification methods has been done before. In this study, two classification methods were compared, namely decision tree and naïve Bayes. Measurement methods were carried out through cross validation. The results obtained from this study are the best algorithms among the two algorithms to determine diabetes sufferers
Komparasi Metode Klasifikasi Data Mining Decision Tree dan Naïve Bayes Untuk Prediksi Penyakit Diabetes Baiq Andriska Candra Permana; Intan Komala Dewi Patwari
Infotek: Jurnal Informatika dan Teknologi Vol 4, No 1 (2021): Infotek : Jurnal Informatika dan Teknologi
Publisher : Fakultas Teknik Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (819.743 KB) | DOI: 10.29408/jit.v4i1.2994

Abstract

Diabetes is a group of metabolic diseases which is indicated by the occurrence of hyperglycemia caused by abnormalities in insulin secretion in the body. Many deaths are caused by diabetes, if this disease is not treated immediately, diabetes can cause damage to other organs such as blindness, stores, heart problem and even kidney problem. A best method is needed in classifying diabetes in order to detect diabetes early. Research related to the classification of diabetes using several calcification methods has been done before. In this study, two classification methods were compared, namely decision tree and naïve Bayes. Measurement methods were carried out through cross validation. The results obtained from this study are the best algorithms among the two algorithms to determine diabetes sufferers
Pelatihan aplikasi komputer santri MDQH (Ma’had Darul Qur’an wal-Hadits) Almajidiah Asy-Syafi’ah NWDI-Pancor Taufik Akbar; Ahwan Ahmadi; Hadian Mandala Putra; M Nuzuluddin; Intan Komala Dewi Patwari; Alimudin Alimudin
ABSYARA: Jurnal Pengabdian Pada Masayarakat Vol 4 No 1 (2023): ABSYARA: Jurnal Pengabdian Pada Masyarakat
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/ab.v4i1.18926

Abstract

In public perception, religious scholars (Ulama) serve as highly trusted sources of information, particularly within Indonesian society. Therefore, it is imperative to ensure that Ulama possesses adequate digital literacy to convey accurate and reliable information. This study aims to provide computer training to the students (santri) of Ma'had MQDH NW Pancor, enabling them to master relevant computer technologies and applications. The training primarily focuses on internet literacy and Microsoft Office applications, employing a combination of lectures and hands-on practice. Ten participants from various levels of study were involved in the program, which took place at Laboratory 1, Faculty of Engineering, Hamzanwadi University. The results of the training revealed that 57.1% of the participants expressed high satisfaction levels, while 71.4% reported an increase in their understanding after completing the training. In conclusion, this computer training program has demonstrated positive benefits in enhancing the digital comprehension and skills of the students, preparing them to tackle digital challenges in the future.
Co-Authors Ahwan Ahmadi Alimudin Alimudin Baiq Andriska Candra Permana M. Nuzuluddin Putra, Hadian Mandala