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Implementasi Metode Dempster-Shafer dalam Mendiagnosis Kelainan Neurologis Berdasarkan Perbedaan Onset Nyeri Intam, Rezki Nurul Jariah S.; Sasmita; Nasrullah, Asmaul Husna; Budiarti, Nur Azizah Eka; Surianto, Dewi Fatmasari
Jurnal Telematika Vol. 19 No. 1 (2024)
Publisher : Yayasan Petra Harapan Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61769/telematika.v19i1.673

Abstract

Penyakit pada otak, seperti stroke, tumor, Alzheimer, dan epilepsi, adalah kondisi serius yang memerlukan diagnosis yang akurat karena otak mengendalikan berbagai fungsi vital tubuh. Gangguan pada otak dapat berdampak fatal sehingga deteksi dini sangat penting. Namun, diagnosis penyakit neurologis sangat kompleks. Di Indonesia jumlah ahli neurologi terbatas dengan sebagian besar ahli berpusat di Pulau Jawa. Oleh karena itu, pada penelitian ini bertujuan membuat sistem pakar menggunakan metode Dempster-Shafer dalam mendiagnosis 7 jenis penyakit neurologis berdasarkan 24 gejala dan 2 onset nyeri yang dirasakan. Onset nyeri ditandai dengan nyeri yang datang tiba-tiba dan perlahan. Tahapan penelitian meliputi identifikasi masalah, pengumpulan data, implementasi metode, perancangan dan pengujian sistem, serta evaluasi hasil. Hasil pengujian sistem menunjukkan akurasi 84% dengan 21 dari 25 kasus sesuai dengan diagnosis pakar. Meskipun terdapat beberapa ketidaksesuaian, metode Dempster-Shafer terbukti handal dan berpotensi dikarenakan menghasilkan akurasi yang cukup tinggi sehingga mampu membantu ahli neurologi dalam proses diagnostik, terutama di Indonesia.
The Determination of Electronic Goods Inventory at Rahmah Store Using the Fuzzy Tsukamoto Method Jannah, Ghina Raodatul; Bittara, Andi Ghizzania Sirih; Udin, Alvin Mas; Nasrullah, Asmaul Husna; Adiba, Fhatiah
Media of Computer Science Vol. 1 No. 2 (2024): December 2024
Publisher : CV. Digital Innovation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69616/mcs.v1i2.204

Abstract

Toko Rahmah is faced with the challenge of determining the optimal inventory of electronic goods to avoid excess or shortage of inventory. The uncertainty of demand and large sales often leads to inefficient inventory management. This study aims to apply the Tsukamoto fuzzy method in determining the optimal inventory of electronic goods at Toko Rahmah. Using this method will increase the accuracy of managing inventory and reduce the risk of excess or shortage of inventory. Therefore, in this study, the Tsukamoto fuzzy method is used to model and overcome the uncertainty of electronic goods inventory. Sales and demand data serve as output to the fuzzy system. The steps taken include forming a fuzzy set, applying fuzzy rules, and performing defuzzification to get an output value that is used as an inventory quantity recommendation. The results of this study were tested using 2 ways, namely using the Netbeans application system and using excel. These two ways are done to see how accurate or suitable the results obtained are. The accuracy results show that the average accuracy is 0.41 from 22 existing data, which is where the system is able to provide fairly accurate recommendations in determining the inventory of goods at Toko Rahmah. This method reduces the risk of excess or shortage of inventory and increases efficiency in managing inventory.
Recommendation of Assistant Lecturer for Advanced Programming Course using Fuzzy Tahani Amaliah, Annisa Shela; Sulmadani, Fitriah; Khaida, Fatihah; Adiba, Fhatiah; Nasrullah, Asmaul Husna; Munawir, Munawir
Media of Computer Science Vol. 2 No. 1 (2025): June 2025
Publisher : CV. Digital Innovation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69616/mcs.v2i1.224

Abstract

The recruitment of teaching assistants for certain courses is a regular activity conducted during specific periods to meet the needs of teaching and learning both inside and outside the classroom. The main objective of the recruitment is to obtain the best teaching assistants who can perform their duties optimally. However, selecting teaching assistants based solely on grades and GPA without considering other criteria is ineffective and subjective. This research proposes the use of the Fuzzy Tahani method in a recommendation system to select teaching assistants for the Advanced Programming course. The aim is to develop a recommendation system for selecting teaching assistants using the Fuzzy Tahani method and to improve objectivity and accuracy in the decision-making process for selecting teaching assistants by considering four criteria: grades, recommendations, availability, and students' GPA. This recommendation system approach is necessary to minimize subjectivity and ensure that the selected teaching assistants can effectively carry out their duties. The result obtained is a recommendation system for selecting teaching assistants, where there is a high level of accuracy between the system's results and the calculation results in Excel, with a difference of 0.00 between them.