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All Journal Jurnal Spektran Paduraksa : Jurnal Teknik Sipil Universitas Warmadewa Techno.Com: Jurnal Teknologi Informasi Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Potensi : Jurnal Sipil Politeknik Dinamisia: Jurnal Pengabdian Kepada Masyarakat SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan JPP IPTEK (Jurnal Pengabdian dan Penerapan IPTEK) Abdimas Umtas : Jurnal Pengabdian kepada Masyarakat GANEC SWARA Jurnal Teknik Sipil To Maega: Jurnal Pengabdian Masyarakat Abdi Dosen : Jurnal Pengabdian Pada Masyarakat INTEGRITAS : Jurnal Pengabdian Jurnal ABDINUS : Jurnal Pengabdian Nusantara Jurnal Pengabdian Masyarakat Teknik Bubungan Tinggi: Jurnal Pengabdian Masyarakat Jurnal Pengabdian Masyarakat Multidisiplin BERNAS: Jurnal Pengabdian Kepada Masyarakat Spektrum Sipil ABDI MOESTOPO: Jurnal Pengabdian pada Masyarakat TIERS Information Technology Journal Jurnal Ilmiah Telsinas Elektro, Sipil dan Teknik Informasi J-ABDIPAMAS (Jurnal Pengabdian Kepada Masyarakat) Reinforcement Review In Civil Engineering Studies and Management Archipelago: Jurnal Pengabdian Kepada Masyarakat Iain Ternate
Dewa Ayu Putu Adhiya Garini Putri
Universitas Pendidikan Nasional
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Journal : Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)

 1 
Sistem Pakar Menggunakan Metode Pembobotan Gejala Penyakit Mata Adie Wahyudi Oktavia Gama; Dewa Ayu Putu Adhiya Garini Putri
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 3 (2020): Juni 2020
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (453.059 KB) | DOI: 10.29207/resti.v4i3.1925

Abstract

The expert system is a branch of artificial intelligence that was developed to emulate an expert's ability to solve problems. Expert systems have been widely developed by many researchers in various fields, including the health field. Various methods have been applied to make a decision in the form of an early diagnose that is obtained accurately. This study begins with simple idea to develop an expert system which more accurate than previous research. This study applies a backward chaining method to trace the disease coupled with giving weight value to the symptoms for each eye disease. The backward chaining method works by selecting one of the diseases to explore the rules. After the disease is determined, the supporting symptoms with the highest weight of the disease will be displayed by the system to be answered by the user. Symptoms and eye diseases in this study are sourced from the eye disease reference book. The symptom weight value for each disease was obtained from giving questionnaires and direct interviews to the ophthalmologist. Giving weights value is done in order to get an early diagnosis more accurate. The early diagnosis that is obtained accurately will support the decision making for the next action that must be done. The results indicate how much the percentage of early diagnosis of eye disease that the patient may suffer based on the symptoms that are answered. The early diagnosis produced by the system is not a final decision, but rather will be used as a decision support to take further action.
Co-Authors Abe Pramuda Wardana Sudarta Adhi Kusuma Putra Adie Wahyudi Oktavia Gama Agus Ariana, I Komang Anak Agung Ayu Bintang Janandewi Anak Agung Gde Alit Wiradyatmika Anak Agung Putu Yoga Pratama Arnesia Udariani Budiarnaya, Putu Caroline Febriyanti Mengo Lengur Decky Cipta Indrashwara Devita Monica Dewa Ayu Susanti Dewi Dewa Gede Agung Juniawan Diah Yonita Bella Gede Agus Suryanatha Gede Aldian Pradila Samita Gede Humaswara Prathama Gusi Putu Lestara Permana Hayu Mas Wrespatiningsih I Gede Adi Pramesta I Gusti Ngurah Nyoman Wismantara I Komang Muliawan I Made Agus Ariawan I Made Oka Suryanata I P. Alit Suthanaya I Putu Agus Esta Hendrawan I Wayan Gede Darma Yoga I Wayan Sutama Ida Ayu Laksmi Nirmala Sari Ida Bagus Puniardhi Isabha Pidada Ida Bagus Suryabrata Insani Nurul Hayati Joao Ficher John Timotius Junieargo Kadek Devi Kalfika Anggria Wardani Kadek Dika Pramana Putra Kadek Prasilia Candra Dewi Ketut Antriksa Kornelisen Mario Kesin Herin Lelia Petronila Gusmao Freitas Made Abdi Wiguna Messias Da Costa Boavida Nabila Shintya Dewi Dewi Ni Kadek Lelyani Ni Luh Putu Sariani Ni Made Pamela Narindra Putri Ni Made Widyaningtyas Dwi Utami Ni Nengah Rupadi Kertiriasih Ni Nyoman Ayu Sariningsih Nilton Da Conceicao Marques Nuraga, Ketut Putu Ariawan Putu Christian Dita Nugraha Putu Galuh Gita Anindya Putri Ravika Nur Melinda Riyan Fadillah Roger Bastiano Lica-Lica Dias Marcal Vidya Shania Devi Wafid Azizah