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Perancangan Sistem Informasi Dokumen P44(Hasil Putusan) Berbasis Web Studi Kasus Kejaksaan Negeri Deli Serdang Ryo Vikri Alif; Muhammad Reza Alhafiz; M. Fakhriza
Journal Of Informatics And Busisnes Vol. 1 No. 4 (2024): Januari - Maret
Publisher : CV. ITTC INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jibs.v1i4.589

Abstract

The development of information technology has become a necessity in optimizing the management of legal documents, especially P44 documents (judgment results). The success of a legal institution depends greatly on its ability to manage and access legal documents, including the results of P44 decisions, quickly and accurately. The process of managing P44 documents at the Deli Serdang District Prosecutor's Office still faces various obstacles. Therefore, there is a need for solutions that can improve the quality of managing P44 documents. Based on these problems, a web-based p44 (decision result) document information system was created. This research uses a Research and Development (RnD) approach with the aim of designing and developing electronic mail. With this system, it is hoped that it can increase accessibility, efficiency and security in managing P44 documents and support the operational performance of the Deli Serdang District Prosecutor's Office as a whole.
Penerapan Logika Fuzzy Tsukamoto Sebagai Sistem Pendukung Keputusan Penentuan Mata Kuliah Pilihan Mahasiswa Ilmu Komputer XYZ Muhammad Reza Alhafiz; Sriani
JURNAL RISET KOMPUTER (JURIKOM) Vol. 13 No. 1 (2026): Februari 2026
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v13i1.9453

Abstract

The selection of elective courses poses a challenge for Computer Science students at XYZ University because it influences competency development, while objective decision-making guidance remains limited. This study aims to develop a web-based decision support system to recommend specialization elective courses using the Fuzzy Tsukamoto method. Data were collected through questionnaires from students in semesters five to seven and processed into four input variables: Robotics, Mathematics, Programming, and Analysis. Each variable was modeled into three fuzzy sets (Weak, Moderate, Strong) using trapezoidal membership functions and processed through IF–THEN rule-based inference with a total of 162 rules. Output values were obtained through weighted average defuzzification to generate course recommendations. System testing was conducted by comparing system outputs with manual calculations and evaluated using the Mean Absolute Percentage Error (MAPE). The results showed a MAPE value of approximately ±0.1096%, indicating that the implementation of the Tsukamoto method in the system is consistent with manual calculations. This study contributes to providing a structured and objective decision support system to assist students in determining elective courses based on their competencies.