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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Jurnal Teknologi Informasi dan Ilmu Komputer Informatika Mulawarman: Jurnal Ilmiah Ilmu Komputer JURNAL REKAYASA TEKNOLOGI INFORMASI Prosiding SAKTI (Seminar Ilmu Komputer dan Teknologi Informasi) Jurnal Intake : Jurnal Penelitian Ilmu Teknik dan Terapan Sains, Aplikasi, Komputasi dan Teknologi Informasi Journal of Computer Science and Engineering (JCSE) PLAKAT : Jurnal Pelayanan Kepada Masyarakat
Fahrul Agus
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Aerospace Engineering Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Mechanical Engineering Social Sciences

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Journal : Journal of Computer Science and Engineering (JCSE)

 1 
Comparison of Moora and Waspas Methods for Recommendations of Cayenne Pepper Seeds Wardani, Agus Tri; Hamdani, Hamdani; Agus, Fahrul
Journal of Computer Science and Engineering (JCSE) Vol 5, No 2: August (2024)
Publisher : ICSE (Institute of Computer Sciences and Engineering)

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Multiple Criteria Decision Making (MCDM) encompasses several methodologies, including MOORA and WASPAS. These strategies demonstrate unique approaches and produce varying results. The main aim of this work is to provide a comparative analysis of the MOORA and WASPAS procedures. To achieve this objective, we conduct a detailed analysis that specifically examines five parameters related to cayenne pepper seeds: prospective crop yields, optimal harvesting time, recommended conditions for highland cultivation, weight of 1000 seeds, and plant height. The study utilizes the sensitivity test approach in a comparative analysis framework to ascertain the superior method. The computations using both the MOORA and WASPAS methods determine that the Bisi Hp 35 (A3) alternative is the best choice. This alternative has a MOORA preference value of 0.1463, while the WASPAS approach gives it a preference value of 0.8374. Next, we perform a sensitivity test by increasing the weight criteria for each criterion by 0.5 and 1. The sensitivity analysis indicates that the MOORA approach has a level of 380, whereas the WASPAS method has a level of 376. The data suggest that the MOORA method is more effective than the WASPAS method when it comes to making recommendations for cayenne pepper seeds.
Expert System for Early Detection of High-Risk Pregnancy Conditions Using Certainty Factor and Forward Chaining Methods Agus, Fahrul; Vadlisky, Febria Dwi; Hamdani, Hamdani
Journal of Computer Science and Engineering (JCSE) Vol 6, No 1: February (2025)
Publisher : ICSE (Institute of Computer Sciences and Engineering)

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The maternal mortality rate is the proportion of deaths that occur during pregnancy due to disorders that specifically impact the uterus. Experts attribute the high number to a lack of knowledge and delays in its management. Samarinda, located in East Kalimantan, has the second highest mortality rate, following Kutai Kartanegara. Hence, the implementation of an early detection system is important to effectively address this issue. The objective of this study is to develop an expert system that utilizes the certainty factor technique to identify high-risk factors in pregnant women before delivery. This study identified three high-risk conditions in pregnant women: preeclampsia, gestational diabetes mellitus (GDM), and constipation. There are a total of 22 symptoms associated with each condition, and for each disease, there are three distinct treatment options available. An expert in the field of obstetrics and gynecology provided the research data. The research yields an expert system that demonstrates accuracy by comparing 10 test data sets from both human experts and computing systems. The system achieved a 90% accuracy rate. Through the use of an expert system methodology, we expect this system to be a valuable resource for pregnant women and healthcare professionals seeking early detection of high-risk diseases in pregnant women.
Co-Authors A., Amelia Alfirama, Dandhi Noufal Arifin, Iswanto AW., Sawung Awang Harsa Kridalaksana Dedy Cahyadi Dedy Fuadi, Dedy Dyna Marisa Khairina Gifari, Okta Ihza Gusfiannur Hamdani . Hamdani Hamdani Haviluddin Haviluddin Heliza Rahmania Hatta, Heliza Rahmania Hendra Saputra Indah Fitri Astuti, Indah Fitri Ismail Ismail Jimi, Jimi Kamil, Zanu Alfandi kusnandar kusnandar Mahendra Putra, Gubtha Mahfud Iman Muhamad Azhari Nasution, Ali Napiah Nasution, Annio Indah Lestari Putra, Gubtha Mahendra Rahmania Hatta, Heliza Ramadiani - Rosmasari Rosmasari, Rosmasari S., Wardana Septya Maharani, Septya Sulfika, Ega Taruk, Medi Vadlisky, Febria Dwi Wardani, Agus Tri Wiwik Anisiyah Yona Widya Sabrina Suprihatini Yunizar Fahmi Badron, Yunizar Fahmi