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All Journal JURNAL ISTEK JOIN (Jurnal Online Informatika)
Ichsan Taufik
Jurusan Teknik Informatika, Fakultas Sains dan Teknologi Universitas Islam Negeri Sunan Gunung Djati Bandung
Computer Science & IT

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APLIKASI DIAGNOSA GANGGUAN KEPRIBADIAN 345 (Studi Kasus : Fakultas Psikologi Universitas Islam Negeri Sunan Gunung Djati Bandung) Ichsan Taufik
JURNAL ISTEK Vol 8, No 2 (2014): ISTEK
Publisher : JURNAL ISTEK

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Aplikasi ini dibangun sebagai alat bantu dengan didasarkan pada kebutuhan seorang psikolog/psikiater maupun orang-orang yang berkerja di area psikologi abnormal dalam mendiagnosa klien yang menderita gangguan kepribadian secara lebih cepat dan efisien. Arsitektur dari sistem ini terdiri dari Knowledge Base, Inference Engine, User Interface, Knowledge Acquisition Facility. Knowledge Base memuat jenis gangguan kepribadian, simptom, dan kriteria tiap jenis gangguan kepribadian tersebut. Sedangkan inference engine diimplementasikan dengan metode forward chaining. Proses diagnosis aplikasi ini adalah melalui penginputan simptom (gejala) yang diderita klien oleh seorang psikolog ke dalam sistem, dan selanjutnya hasil diagnosa didapatkan melalui penelusuran aturan yang ada antara lain dengan perhitungan jumlah simptom yang memenuhi syarat minimal sebuah jenis gangguan kepribadian.
Klasifikasi Terjemahan Ayat Al-Quran Tentang Ilmu Sains Menggunakan Algoritma Decision Tree Berbasis Mobile Devi Setiawati; Ichsan Taufik; Jumadi Jumadi; Wildan Budiawan Zulfikar
JOIN (Jurnal Online Informatika) Vol 1 No 1 (2016)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v1i1.7

Abstract

The number of verses of the Quran contained in the Qur'an, encouraging people to look for a way to get the exact clause in a short time. The science is an important knowledge, as Muslims we are obliged to study it with the Al-Quran as a guide. So that's how we get the verse about the science of the Quran with a quick, efficient and practical with a mobile application. Decision tree is a predictive model using a tree or hierarchical structure, this method can support mobile applications to be created. Because based decision very complex and global in the Quran, can be transformed into more simple and specific. C4.5 algorithm is a decision tree induction algorithm and is suitable to perform the classification process. The results of the percentage of successful applications created by using a decision tree that is 75.73%. From these results is known that the algorithm C4.5 and decision tree reasonably is well used in the classification process.
Klasifikasi Terjemahan Ayat Al-Quran Tentang Ilmu Sains Menggunakan Algoritma Decision Tree Berbasis Mobile Devi Setiawati; Ichsan Taufik; Jumadi Jumadi; Wildan Budiawan Zulfikar
JOIN (Jurnal Online Informatika) Vol 1 No 1 (2016)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v1i1.7

Abstract

The number of verses of the Quran contained in the Qur'an, encouraging people to look for a way to get the exact clause in a short time. The science is an important knowledge, as Muslims we are obliged to study it with the Al-Quran as a guide. So that's how we get the verse about the science of the Quran with a quick, efficient and practical with a mobile application. Decision tree is a predictive model using a tree or hierarchical structure, this method can support mobile applications to be created. Because based decision very complex and global in the Quran, can be transformed into more simple and specific. C4.5 algorithm is a decision tree induction algorithm and is suitable to perform the classification process. The results of the percentage of successful applications created by using a decision tree that is 75.73%. From these results is known that the algorithm C4.5 and decision tree reasonably is well used in the classification process.
Co-Authors Devi Setiawati Jumadi Jumadi Wildan Budiawan Zulfikar