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All Journal JOIV : International Journal on Informatics Visualization Sinkron : Jurnal dan Penelitian Teknik Informatika Creative Information Technology Journal Techno Nusa Mandiri : Journal of Computing and Information Technology JURNAL ILMIAH INFORMATIKA JurTI (JURNAL TEKNOLOGI INFORMASI) Martabe : Jurnal Pengabdian Kepada Masyarakat Krea-TIF: Jurnal Teknik Informatika CSRID (Computer Science Research and Its Development Journal) Informasi Interaktif CCIT (Creative Communication and Innovative Technology) Journal Indonesian Journal of Business Intelligence (IJUBI) IJIIS: International Journal of Informatics and Information Systems Jurnal Pembelajaran Pemberdayaan Masyarakat (JP2M) Management and Sustainable Development Journal Journal of Applied Data Sciences International Journal of Computer and Information System (IJCIS) Jurnal Pengabdian Kepada Masyarakat Patikala Journal Computer Science and Informatic Systems : J-Cosys Jurnal Ilmiah Edutic : Pendidikan dan Informatika Jurnal Informatika: Jurnal Pengembangan IT ABDIKOM
Musthofa Galih Pradana
Universitas Pembangunan Nasional Veteran Jakarta
Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Library & Information Science Social Sciences

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Journal : CCIT (Creative Communication and Innovative Technology) Journal

 1 
Perancangan Sistem Pakar Untuk Mendiagnosa Penyakit Diabetes Mellitus Menggunakan Metode Certainty Factor Design Expert System for Diagnosing Diabetes Mellitus Using Certainty Factor Method Musthofa Galih Pradana; Bondan Wahyu Pamekas; Kusrini Kusrini
CCIT Journal Vol 11 No 2 (2018): CCIT JOURNAL
Publisher : Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (425.849 KB) | DOI: 10.33050/ccit.v11i2.586

Abstract

Diabetes mellitus is a chronic metabolic disorder caused by the pancreas that does not produce enough insulin, so the body works to be disturbed. But by knowing the symptoms that exist, prevention of diabetes mellitus disease can be done as early as possible with the help of expert systems.One method of expert system used to diagnose symptoms of Diabetes Mellitus is Certainty Factor. The process undertaken in this research starts from literature studies, system design, system implementation and the last is testing the system. In the system design process is done by designing the database required by the expert system and also design the system interface design. After the design process is done then the next step is to implement the design into an expert system application. By using this method, the system gives results of possible symptoms experienced, presentation of beliefs, and treatment solutions based on the facts and the value of confidence given by users in filling out questions that have been given by the system.The results of this system are used to help medical personnel and patients in order to identify the symptoms of diabetes mellitus
Performance Analysis of Tree-Based Algorithms in Predicting Employee Attrition Musthofa Galih Pradana; I Wayan Rangga Pinastawa; Nurhuda Maulana; Wahit Desta Prastowo
CCIT Journal Vol 16 No 2 (2023): CCIT JOURNAL
Publisher : Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/ccit.v16i2.2580

Abstract

Based on data throughout 2022, there have been many reductions in employees both globally and Indonesia. The reduction was made due to adjustments with developments to keep the business afloat in increasingly fierce competition. However, reducing the number of employees is not an easy decision to make. This decision can have an impact on many aspects of the development and course of a business or company. To make a decision especially related to the aspect of termination of employment, it is necessary to consider carefully and thoroughly. Assessment and decision-making cannot be based on just one aspect, other aspects need to be seen to be taken into consideration. Additional aspects that can be selected to strengthen decision-making can be taken from the data. Data will not have any value without processing it with various approaches, one of which is the prediction process. Starting from the data, the prediction results will be more appropriate to make a decision. This study made a comparison of 3 decision tree algorithms, and produced a comparison of the three methods in terms of accuracy. The results of this study are the best accuracy for each algorithm C.45 = 83.44; Random Forests = 85.85; LMT = 88.29 with a linear precision value, and the best algorithm model with the highest accuracy is the Logistic Model Tree (LMT) algorithm.
Co-Authors Adhien Kenya Anima Estetikha Andri Pramuntadi Anni Alvionita Simanjuntak Budi, Ryan Setya Dema Mathias Lumban Tobing Devira Ayu Martini, Ni Putu Dhina Puspasari Wijaya, Dhina Puspasari Dyah Listianing Tyas, Dyah Listianing Emha Taufiq Luthfi Fandli Supandi Gutama, Deden Hardan Ha, Hoang Thi Henki Bayu Seta I Wayan Rangga Pinastawa Izzety, Aurel Jayanta Kaharuddin Kharisma Wiati Gusti Khoironi, Khoironi Khoirunnisa, Hilda Kusrini Kusrini Kusrini Kusrini Kusrini Kusrini Mu, Jesselyn Muhamad Ridwan Muhammad Adrezo Muthia Zahrah, Nada Neny Rosmawarni Nindy Irzavika Niqotaini, Zatin Nurcahyo, Azriel Christian Nurhajar Anugraha Nurhuda Maulana Nurul Afifah Arifuddin Nyamiati, Retno Dwi Pamekas, Bondan Wahyu Prananto, Muhammad Teguh Pujo Hari Saputro Radinal Setyadinsa Rangga Saputra Ridlo Muttaqien Ridwan Raafi'udin Rifka Dwi Amalia Rifqi Hammad Rusiyono, Ruwet Setiawan, Deandra Satriyo Wahit Desta Prastowo Wari, Valtrizt Khalifah Wiryanto, Fadhli Suko Yulianto Mustaqim Yusuf Hendra Pratama