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All Journal Tadris: Jurnal keguruan dan Ilmu Tarbiyah Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal INSYPRO (Information System and Processing) Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Digital Zone: Jurnal Teknologi Informasi dan Komunikasi JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Journal of Soft Computing Exploration Online Learning in Educational Research Internet of Things and Artificial Intelligence Journal Teknovokasi : Jurnal Pengabdian Masyarakat Jurnal Pengabdian Masyarakat Jurnal Kemitraan Responsif untuk Aksi Inovatif dan Pengabdian Masyarakat Journal of Deep Learning, Computer Vision and Digital Image Processing Jurnal Sipakatau: Inovasi Pengabdian Masyarakat Jurnal MediaTIK Media of Computer Science
Adiba, Fhatiah
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Humanities Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Library & Information Science Social Sciences Other

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Journal : Media of Computer Science

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Enhanced Laptop Recommendation System Using Tsukamoto Fuzzy Logic Nasrullah, Asmaul Husnah; Adiba, Fhatiah; Anastasia, Tezza; Farghina, Syakira Ayma; Akbar, Muh.
Media of Computer Science Vol. 1 No. 1 (2024): June 2024
Publisher : CV. Digital Innovation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69616/mcs.v1i1.186

Abstract

One of the most popular and rapidly growing needs among the general public is laptops. Currently, there are many types of laptops with varying features, and not everyone knows the advantages and disadvantages of each type. The purpose of this research is to develop and build a Fuzzy inference system that applies the Tsukamoto method. This is to address issues in providing unclear or inaccurate services to customers during the laptop sales process. By developing a recommendation system that can provide guidance or suggestions in purchasing a laptop based on interest and needs in searching for references, and the type of laptop that meets the criteria. The decision to purchase a laptop uses parameters such as screen size, RAM capacity, SSD capacity, and price. The implementation of the Fuzzy Tsukamoto method for providing laptop purchase recommendations is able to give good recommendations.
Evaluation Of Fuzzy C-Means Method For District Clustering Nasrullah, Asmaul Husnah; Fajar, Andi Muhammad; Taufiq, Muhammad Aqsha; Rahmat, Nuzulul; 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.v1i2.203

Abstract

This study analyses the use of Fuzzy C-Means algorithm to cluster districts in South Sulawesi based on the education level of the population. Two distinct groups were found with several districts falling into each group after 17 iterations to reach the optimal solution. The clustering results were visualised with a point spread graph. The Fuzzy C-Means algorithm was executed using Python with certain parameters. The research aims to improve the quality of education with proper resource allocation and identification of districts based on the highest education. The data used includes education indicators and district minimum wage. The results are expected to provide input for a more targeted education policy in South Sulawesi. Fuzzy C-Means algorithm is effective for analysing and clustering education data in education policy decision making.
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.
A Decision Support Model for Scholarship Recipient Selection Based on Tsukamoto Fuzzy Logic Muhtadi; Aksa, Muhammad; Naoval, Ahmad; Adiba, Fhatiah; Nasurllah, Asmaul Husna
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.v2i1.225

Abstract

This study proposes a decision support model for scholarship recipient selection based on the Tsukamoto fuzzy logic method to overcome the inefficiencies and subjectivity inherent in manual selection processes. The model incorporates three key criteria: Grade Point Average (GPA), parents’ income, and number of dependents. Experiments were conducted using a dataset of 25 students obtained from a public Kaggle repository. The model employs fuzzification, rule formulation, and defuzzification to compute a final decision score for each applicant. The experimental results demonstrate that the proposed model achieves an accuracy rate of 92%, indicating its effectiveness in supporting objective and efficient scholarship selection decisions.
Co-Authors Abdul Wahid Afdhaliyah, Mukhlishah Aglaia, Alifya Nuraisyar Akbar, Muh. Aksa, Muhammad Amaliah, Annisa Shela Amukune, Stephen Anastasia, Tezza Andani, Andi Ferry Adlian Tri Andi Akram Nur Risal Andi Baso Kaswar Andi Baso Kaswar Arifiyanti, Fitria Asmaul Husnah Nasrullah Awaluddin, Muh. Ghazali Azis, Putri Alysia Baso, Fadhlirrahman Bittara, Andi Ghizzania Sirih DARMATASIA, DARMATASIA Dewi Fatmarani Surianto Edy, Marwan Ramdhany Fajar, Andi Muhammad Fardan, Muhammad Farghina, Syakira Ayma Fathahillah Fathahillah Febriansyah Ramadhan, Haekal Firdaus Firdaus Hasnining, Ayu Husna Nasrullah, Asmaul Jannah, Ghina Raodatul Jumadi Mabe Parenreng Kartika, A.Amalia Khaida, Fatihah Kurnia Prima Putra Lapendy, Jessica Crisfin Lia, Resky Amalia Liku, Antika Diana M. Miftach Fakhri Makmur, Haerunnisya Maolani, Muh. Alfi Muhammad Fajar B Muhammad Yahya Muhtadi Muliadi Munawir Munawir Naoval, Ahmad Nasrullah, Asmaul Husna Nasrullah, Asmaul Husnah Nasurllah, Asmaul Husna Nasurullah, Asmaul Husna NFH, Alifya Nida Rifqi, Ainun Nurfitri, Andi Aisyah Parenreng, Jumadi M. Prasetya, Muhammad Fahril Qadri, Zul Rahmat, Nuzulul Ramli, Abdur Rahman Resky, Andi Aulia Cahyana Rivai, Andi Tenri Ola Salsabila, Azizah Sanatang Soeharto Soeharto Sulmadani, Fitriah Syahbani, Dimas Syair, Andi Irfandiari Syair Syukur, Pramudya Asoka Tahir, Muhlis Taufiq, Muhammad Aqsha Tenriola, Andi Udin, Alvin Mas Wahyuni , Maya Sari Wardani, Ayu Tri Wardani, Ayu Tri Wardani WULANDARI