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Journal : Jurnal Inotera

Information System for Operational Goods Management at the Career Guidance and Entrepreneurship Center Malikussaleh University Rizki Suwanda; Said Fadlan Anshari; Wardina Ningsih
Jurnal Inotera Vol. 9 No. 1 (2024): January-June 2024
Publisher : LPPM Politeknik Aceh Selatan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31572/inotera.Vol9.Iss1.2024.ID324

Abstract

Managing operational goods manually leads to slow and inefficient work performance, hence the design and implementation of an information system that can efficiently manage operational goods needs to be done in a structured manner and work optimally. Analysis of operational goods needs is conducted through observation and interviews with relevant parties to discuss the problems faced and identify the required features. Some key features implemented in this system include complaint management for operational goods needs, which can be managed and utilized for effective procurement or requests for goods according to requirements. This system is designed using the PHP programming language with the Codeigniter framework and MySQL database for database management. With this system in place, it is expected to assist in the more effective and systematic management of operational goods needs at the Career Guidance and Entrepreneurship Center of Malikussaleh University.
Analysis of the Application the Promethee Method in Determining Work Partners at the Central Statistics Agency of Central Aceh Regency Ayu Rosmala, Ayu Rosmala; Muchlis Abdul Muthalib, Muchlis Abdul Muthalib; Rizki Suwanda
Jurnal Inotera Vol. 9 No. 2 (2024): July - December 2024
Publisher : LPPM Politeknik Aceh Selatan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31572/inotera.Vol9.Iss2.2024.ID369

Abstract

The selection of partners at the Central Statistics Agency of Central Aceh Regency faces challenges because manual selection methods are considered inefficient and inaccurate. Therefore, this study aims to improve the accuracy and efficiency of the selection process by applying the Promethee (Preference Ranking Organization Method for Enrichment Evaluations) method. This method is used as a multi-criteria decision-making technique and is implemented using the Python programming language for automatic and real-time data processing. The data used comes from the 2024 partner recruitment process at the Central Statistics Agency of Central Aceh Regency, consisting of candidates who have met the administrative requirements. The validity of the promethee method is tested through the calculation of an error percentage that reaches 10%, demonstrating the method's ability to filter partners according to the established criteria. In conclusion, the application of the promethee method has been proven to improve the efficiency and accuracy of the partner selection process, where the Python-based system developed can reduce the time and effort required in decision-making while producing more valid and reliable partner recommendations.
Implementation of the Forward Chaining Method in Identifying Study Programs Based on Students Interests and Talents Raudhatul Fazira; Bustami; Rizki Suwanda
Jurnal Inotera Vol. 10 No. 2 (2025): July - December 2025
Publisher : LPPM Politeknik Aceh Selatan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31572/inotera.Vol10.Iss2.2025.ID481

Abstract

This study aims to develop a decision support system (DSS) based on the Forward Chaining method to assist prospective students in selecting a study program that aligns with their interests, talents, and abilities. The system is designed to analyze 34 facts related to the respondents' interests and talents using predefined Rules, generating program recommendations in the form of rankings based on suitability weights. Testing was conducted with 100 respondents, one of whom, named Najmil Ula, was recommended to choose the Chemical Engineering program with a suitability weight of 2,3 or 26.44%, based on fulfilled facts such as an interest in understand in physics and love doing an experiment. Additionally, the system provided alternative recommendations, such as Informatics Engineering and Arcitecture, with lower suitability levels. These results demonstrate that the system can provide relevant and objective recommendation, making it an effective tool to support prospective students in selecting study programs that match their potential.