Garuda - Garba Rujukan Digital

Penjadwalan Mata Kuliah Otomatis Menggunakan Algoritma Late Acceptance Hill-Climbing Hyper-Heuristics dengan Domain Permasalahan ITC Cut Alna Fadhilla
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 3 No. 3 (2024): September 2024
Publisher : LKP Unity Academy

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70340/jirsi.v3i3.168

The International Timetabling Competition is an international scheduling competition that aims to motivate further research on scheduling issues especially in scheduling in the field of education. In the world of education, scheduling problems have become a topic that is often encountered. One of the scheduling problems found in higher education is scheduling courses. Course scheduling is conducted routinely at the beginning of each semester, in scheduling must pay attention to the allocation of resources contained in the university. Scheduling is a long process, it is because in allocating resources in a scheduling problem must pay attention to various aspects or limits that have been set in order to get optimal results. This problem is classified as a Non-Polynomial hard problem, where there is no exact algorithm to solve it in a polynomial time. In the preparation of this final project subject scheduling is done using a tabu search algorithm - simulated annealing hyper-heuristics. The dataset used is a dataset obtained from the 2019 International Timetabling Competition. The results of this final project are java-based automatic scheduling applications which are expected to help solve problems related to scheduling subjects more optimally, and solutions that are produced competitive with benchmark algorithms.

Perancangan Sistem Informasi untuk Pengelolaan Tindakan Administratif Keimigrasian terhadap Warga Negara Asing pada Kantor Imigrasi Intan Saravina; Cut Alna Fadhilla
Governance IT Adoption and Technology Advance Vol. 1 No. 1 (2026)
Publisher : Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25124/govita.v1i1.10036

The development of information technology has encouraged government institutions to improve the effectiveness and transparency of public services, including in the field of immigration. The Class II Immigration Office in Langsa plays an important role in the supervision and enforcement of immigration law against foreign nationals through the implementation of Immigration Administrative Actions (IAA). However, the previous management of IAA data was still carried out manually, which often resulted in delays and errors in recording and reporting processes. To address these issues, a web-based Immigration Administrative Action Information System was designed and developed using the Prototype Model methodology. The system was built using the PHP programming language, MySQL as the database, and implemented on a local XAMPP server. The implementation results indicate that the system is able to facilitate officers in inputting, managing, and compiling reports of administrative actions against foreign nationals in a fast and integrated manner. The simple user interface allows users to operate the system easily without requiring special training. The Class II Immigration Office in Langsa assessed the system as effective in improving administrative efficiency and supporting the digitalization of immigration services. The system is expected to be further developed by incorporating enhanced security features and automated report printing to sustainably support immigration operations.

Optimized Land Surface Low Point Detection Using the D8 Algorithm in a Geographic Information System (GIS) Framework Khairul Muttaqin; Novianda Novianda; Ahmad Ihsan; Dea Ayuni Putri; Cut Alna Fadhilla; Chichi Rizka Gunawan; Chicha Rizka Gunawan; Jefril Rahmadoni
Jurnal Testing dan Implementasi Sistem Informasi Vol. 4 No. 1 (2026): Jurnal Testing dan Implementasi Sistem Informasi
Publisher : Lembaga Riset dan Inovasi Almatani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55583/jtisi.v4i1.2205

Hydrological analysis in urban areas often suffers from inaccuracies in Digital Elevation Model (DEM) interpretation, especially in detecting micro-depressions and small-scale surface flow patterns. Previous studies typically relied solely on the automatic D8 algorithm in GIS without manual verification, resulting in flow directions that do not fully represent actual surface conditions. This study aims to compare manual D8-based flow direction calculations with automatic ArcGIS processing using DEMNAS data for Langsa City. The DEM (8.1 m resolution) underwent sink filling, hydrological conditioning, slope and aspect processing, followed by field validation using GPS measurements. The results show that the manual method identified 23 flow paths, whereas ArcGIS detected only 11. The differences stem mainly from micro-topographic variations that the automatic algorithm failed to capture in flat areas or anthropogenically modified surfaces. Field validation confirmed that 8 of the 11 ArcGIS-derived paths matched the actual drainage patterns, while the additional manual paths better represented subtle elevation gradients.This research contributes by offering a systematic comparison between manual and automatic D8 approaches, highlighting the importance of manual verification in low-slope urban terrains. The findings are valuable for micro-scale flood mitigation planning and urban surface hydrology analysis.

Optimized Land Surface Low Point Detection Using the D8 Algorithm in a Geographic Information System (GIS) Framework Khairul Muttaqin; Novianda Novianda; Ahmad Ihsan; Dea Ayuni Putri; Cut Alna Fadhilla; Chichi Rizka Gunawan; Chicha Rizka Gunawan; Jefril Rahmadoni
Jurnal Testing dan Implementasi Sistem Informasi Vol. 4 No. 1 (2026): Jurnal Testing dan Implementasi Sistem Informasi
Publisher : Lembaga Riset dan Inovasi Almatani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55583/jtisi.v4i1.2205

Hydrological analysis in urban areas often suffers from inaccuracies in Digital Elevation Model (DEM) interpretation, especially in detecting micro-depressions and small-scale surface flow patterns. Previous studies typically relied solely on the automatic D8 algorithm in GIS without manual verification, resulting in flow directions that do not fully represent actual surface conditions. This study aims to compare manual D8-based flow direction calculations with automatic ArcGIS processing using DEMNAS data for Langsa City. The DEM (8.1 m resolution) underwent sink filling, hydrological conditioning, slope and aspect processing, followed by field validation using GPS measurements. The results show that the manual method identified 23 flow paths, whereas ArcGIS detected only 11. The differences stem mainly from micro-topographic variations that the automatic algorithm failed to capture in flat areas or anthropogenically modified surfaces. Field validation confirmed that 8 of the 11 ArcGIS-derived paths matched the actual drainage patterns, while the additional manual paths better represented subtle elevation gradients.This research contributes by offering a systematic comparison between manual and automatic D8 approaches, highlighting the importance of manual verification in low-slope urban terrains. The findings are valuable for micro-scale flood mitigation planning and urban surface hydrology analysis.

Deteksi Penyakit Mata Menggunakan Algoritma Region Growing Chicha Rizka Gunawan; Mahara Bengi; Chichi Rizka Gunawan; Cut Alna Fadhilla
Algoritma: Jurnal Ilmu Komputer dan Informatika Vol 9, No 2 (2025): November 2025
Publisher : Universitas Islam Negeri Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/algoritma.v9i2.27908

Medical image processing is a data manipulation process aimed at producing new images with improved quality. The primary objective of medical image processing is to obtain information, perform screening procedures, and support disease diagnosis, one of which is eye diseases. Nodules, as one of the indications of eye diseases, are generally analyzed visually by physicians. This study develops an algorithm to detect nodules in eye CT scan images based on the morphological characteristics of nodules, which are generally circular in shape. The experimental results show that the nodule area can be calculated based on the number of pixels forming the nodule region. In several image slices, the nodule area cannot be detected due to the condition where the nodule is attached to other parts of the eye. The developed algorithm is capable of detecting nodules in multiple eye CT scan slices and calculating the nodule area in each image slice. Therefore, the proposed nodule detection algorithm is expected to assist physicians in diagnosing eye diseases more accurately and objectively. Keywords: Detection, Region Growing, Eye Disease, Medical Image Processing, Nodule

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