cover
Contact Name
Yosep Septiana
Contact Email
yseptiana@itg.ac.id
Phone
+6282124588750
Journal Mail Official
algoritma@itg.ac.id
Editorial Address
Jl. Mayor Syamsu No.1, Jayaraga, Kec. Tarogong Kidul, Kabupaten Garut, Jawa Barat 44151
Location
Kab. garut,
Jawa barat
INDONESIA
Jurnal Algoritma
ISSN : 14123622     EISSN : 23027339     DOI : https://doi.org/10.33364/algoritma
Core Subject : Science,
Jurnal Algoritma merupakan jurnal yang digunakan untuk mempublikasikan hasil penelitian dalam bidang Teknologi Informasi (TI), Sistem Informasi (SI), dan Rekayasa Perangkat Lunak (RPL), Multimedia (MM), dan Ilmu Komputer (Computer Science).
Articles 1,026 Documents
Rancang Bangun Sistem Pakar Penyakit Hydrocephalus Berbasis Web Sutedi, Ade; Baswardono, Wiyoga; Setiawan, Wawan
Jurnal Algoritma Vol 22 No 1 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-1.2056

Abstract

Hydrocephalus disease is a rare condition that generally occurs in children under 5 years old, although adults can also be affected. It is important to develop an expert system that can help diagnose, prevent and provide treatment solutions for this disease. This research uses the Expert System Development Life Cycle (ESDLC) methodology and forward chaining inference method, and conducts testing with Blackbox Testing. The result is an expert system that can diagnose early symptoms of hydrocephalus, offer prevention recommendations, and treatment solutions, thus helping patients detect this condition early and reducing costs and consultation time.
Implementasi Forward Chaining dan Certainty Factor pada Aplikasi Sistem Pakar Diagnosa Penyakit Kulit Wajah Nuraeni, Fitri; Fitriani, Leni; Yusuf , Alifa Witri Alfahira
Jurnal Algoritma Vol 22 No 1 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-1.2096

Abstract

Facial skin diseases are not life-threatening, but they can interfere with a person's quality of life. Like people with skin diseases, they are unable to carry out normal activities because they can interfere with the comfort of themselves and others. However, to be able to diagnose skin diseases, it is necessary to have the role of a skin disease expert. Meanwhile, the existence of skin disease experts is still relatively rare and even if they exist, they usually require costs and limited service time. Therefore, this research develops a web-based expert system to help diagnose facial skin diseases by utilizing forward chaining and certainty factor methods. The system was designed using the expert system development cycle, and involved two experts in knowledge acquisition. Test results on 20 cases showed an accuracy rate of 85%. This system can be an initial diagnosis tool when specialists are not available.
Perbandingan Model Prediksi Suhu Permukaan Laut Menggunakan Smoothing dan Long Short-Term Memory Arsanti, Yulia; Minsaris, La Ode Alam; Arifin, Wildan Aprizal
Jurnal Algoritma Vol 22 No 1 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-1.2113

Abstract

Sebagai negara kepulauan terbesar, Indonesia memiliki kekayaan maritim melimpah, termasuk Perairan Merak Banten, yang memiliki peran strategis dalam transportasi laut, perikanan, dan industri. Suhu permukaan laut (SPL) di wilayah ini memengaruhi ekosistem laut, produktivitas perikanan, serta perekonomian masyarakat. Penelitian sebelumnya umumnya menggunakan pendekatan statistik konvensional atau machine learning secara terpisah dalam memprediksi SPL, sehingga belum ada perbandingan langsung antara metode deep learning dan metode statistik dalam satu studi, sementara pengukuran SPL secara konvensional masih memiliki keterbatasan secara spasial dan temporal. Penelitian ini membandingkan performa model prediksi SPL dengan pendekatan deep learning menggunakan Long Short-Term Memory dan metode statistik smoothing eksponensial, yang belum diterapkan secara bersamaan dalam analisis SPL di Perairan Merak, Banten. Studi ini mengisi kesenjangan penelitian sebelumnya dengan mengevaluasi efektivitas kedua metode dalam memprediksi SPL. Data penelitian diperoleh dari citra satelit Aqua MODIS, yang memungkinkan analisis spasial lebih representatif. Dengan demikian, integrasi teknologi penginderaan jauh dan metode machine learning dalam model prediksi SPL diperlukan untuk meningkatkan akurasi dan efisiensi prediksi. Hasil penelitian menunjukkan bahwa model LSTM dengan parameter look_back 7 dan epoch 200 memberikan performa terbaik dengan nilai MAE 0,3798 dan RMSE 0,8970, sehingga lebih unggul dalam memprediksi pola jangka panjang. Sementara itu, smoothing eksponensial dengan damped trend True dan look_back 7 menghasilkan MAE 0,9052 dan RMSE 1,6771, lebih efektif untuk prediksi jangka pendek. Temuan ini menegaskan bahwa LSTM lebih akurat dalam menganalisis tren SPL jangka panjang, sedangkan smoothing eksponensial lebih sesuai untuk prediksi jangka pendek yang stabil, memberikan wawasan baru dalam pemilihan model prediksi SPL di perairan merak, Banten.
Pengembangan Aplikasi Pendaftaran Siswa Baru Berbasis Web Dengan React.Js dan Tailwind CSS Pamungkas, Ginda Dwi; Parwati, Yuli; Putranto, Banu Dwi
Jurnal Algoritma Vol 22 No 1 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-1.2135

Abstract

Kemajuan teknologi informasi telah membawa dampak signifikan dalam dunia pendidikan, termasuk proses administrasi seperti pendaftaran siswa baru. Penelitian ini bertujuan mengembangkan sistem pendaftaran siswa baru berbasis web menggunakan React.js dan Tailwind CSS untuk SMP Muhammadiyah Sumbang. Sistem ini dirancang untuk mengatasi masalah pendaftaran manual yang sering menimbulkan rawan kesalahan data, memakan waktu dan ketidaknyamanan bagi calon siswa. Metodologi pengembangan perangkat lunak diterapkan, termasuk analisis kebutuhan, perancangan sistem, implementasi dan pengujian menggunakan black-box, Evaluasi sistem dilakukan dengan metode PIECES untuk menilai aspek kerja, efisiensi dan layanan .Hasil pengujian dari penelitian ini menunjukan bahwa sistem ini berhasil mengurangi kesalahan input data, mempercepat waktu pendaftaran dari rata-rata waktu 10 – 15 menit menjadi 5 menit, dan meningkatkan efisiensi administrasi sekolah dari rekap data yang sebelumnya membutuhkan 3 hari sekarang dapat di selesaikan kurang dari 1 jam. Sistem ini mudah digunakan oleh calon siswa dan panitia sekolah dengan fitur yang responsif dan ramah pengguna. Penelitian ini memberikan kontribusi praktis sebagai model bagi sekolah yang ingin mengadopsi teknologi serupa untuk meningkatkan layanan administrasi secara digital.
Perancangan dan Pengembangan Sistem Pendukung Keputusan Guru Berprestasi Dengan Metode Simple Additive Weighting Sri Hastuti; Nirsal, Nirsal; Syafriadi
Jurnal Algoritma Vol 22 No 1 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-1.2141

Abstract

Penilaian terhadap guru berprestasi di SMK Negeri 2 Luwu Utara sering kali terhambat oleh subjektivitas dan ketidakteraturan data. Penelitian ini menggunakan metode Simple Additive Weighting (SAW) untuk mengatasi masalah tersebut. Tahapan penelitian mencakup identifikasi masalah, pengumpulan data, perancangan sistem berbasis web, implementasi metode SAW, dan pengujian sistem. Sistem ini menilai guru berprestasi berdasarkan empat kriteria utama: kompetensi pedagogik, kepribadian, sosial, dan profesional. Hasil penelitian menunjukkan bahwa implementasi metode SAW meningkatkan transparansi, efisiensi, dan akurasi dalam proses penilaian, sehingga mengurangi waktu yang dibutuhkan untuk pengambilan keputusan.
Rancang Bangun Sistem Presensi Face Recognition di Unit Pelaksana Teknis: Studi kasus Sekolah Dasar Negeri 184 Lumu-Lumu Nirsal, Nirsal; Amin, Muh.
Jurnal Algoritma Vol 22 No 1 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-1.2142

Abstract

Penelitian ini bertujuan untuk merancang dan membangun sistem presensi face recognition di UPT SDN I84 Lumu-Lumu. Penelitian menggunakan metode Research and Development (R&D) dengan pengembangan aplikasi berbasis model waterfall yang mencakup 5 tahap: Requirement, Design, Coding and Testing, Integration and Testing, serta Operation & Maintenance. Data dikumpulkan melalui observasi, wawancara, dan studi pustaka. Sistem ini dikembangkan menggunakan VS Code, Android Studio, Firebase, Flutter, Dart, Draw.io, dan Balsamiq Mockup, dengan model pengenalan wajah berbasis Convolutional Neural Network (CNN). Hasil validasi instrumen observasi menghasilkan nilai 82%, wawancara 84%, UML 82,5%, interface 83,5%, database 83,5%, pengujian black box 82,5% dan user/pengguna 84%.  Hasil validasi intrumen penilaian observasi UML 91%, interface 90%, database 87% hasil pengujian System Usability Scale SUS memperoleh hasil 88%. Berdasarkan hasil tersebut, aplikasi ini dinyatakan layak dan sesuai dengan kebutuhan yang diharapkan. Kontribusi penelitian ini penelitian ini terletak pada penerapan teknologi pengenalan wajah untuk meningkatkan efisiensi dan akurasi sistem presensi di lingkungan pendidikan.
Implementasi Metode Design Thinking Pada Perancangan UI/UX Aplikasi Pendaftaran Siswa Baru Berbasis Web Wibowo, Nurma Budi Santoso; Purwati, Yuli; Putranto, Banu Dwi
Jurnal Algoritma Vol 22 No 1 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-1.2153

Abstract

The New Student Admission (PPDB) process at SMP Muhammadiyah Sumbang has traditionally been conducted manually, leading to various issues such as administrative errors, complicated document submission, and limited information access for prospective students and parents. This study aims to design a web-based user interface (UI) and user experience (UX) to support a more efficient PPDB process. The method used is Design Thinking, consisting of five iterative stages: empathize, define, ideate, prototype, and testing. In the empathize stage, user needs were identified through interviews, revealing key issues such as the demand for a simple registration flow, document upload features, real-time status monitoring, and transparent fee details. These insights were used in the define stage to formulate user-centered solutions. During the ideate stage, user flows and wireframes were created to visualize the registration process and required features. The developed prototype was tested during the testing stage using the System Usability Scale (SUS) method. Testing with five respondents resulted in an average SUS score of 85, placing the application in the “good” category with an “excellent” level of acceptability. The prototype effectively addresses the challenges of manual registration, enhances time efficiency, and provides an optimal user experience. The attractive and intuitive UI/UX design also has the potential to improve the school's image in the community. With this design, the web-based PPDB system not only simplifies administrative processes but also offers a long-term, flexible, and adaptive solution to evolving user needs.
Evaluasi Keterlibatan Mahasiswa Dalam Lingkungan Pembelajaran Daring Menggunakan Natural Language Processing (NLP) dan Analisis Sentimen Hartantom, Budi; Yunita, Hilda Dwi; Fahurian, Fatimah; Dirayati, Fadhilah; Winarko, Triyugo; Marliana, Iin
Jurnal Algoritma Vol 22 No 1 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-1.2154

Abstract

This research aims to evaluate student engagement in online learning environments using Natural Language Processing (NLP) and sentiment analysis. The research method involves text analysis of student interactions on a Learning Management System (LMS) platform, including discussion forums, comments, and messages. NLP techniques were used to identify patterns of student engagement, while sentiment analysis assessed the emotions contained in the interactions, including positive, negative, or neutral sentiments. The results show that student engagement can be effectively measured through this analysis, as well as providing an overview of engagement patterns and the factors that influence them. The findings are expected to be used to improve the quality of online learning.
Penerapan Metode Indirect Approach Terhadap Software Monitoring Stunting Untuk Menghitung Cost Estimation Septiana, Fahmi Fadillah; Fikrillah, Hamzah Nurrifqi Fakhri
Jurnal Algoritma Vol 22 No 1 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-1.2157

Abstract

The success factor of a software development project is the accuracy of estimating and planning the activities to be carried out, estimating time, cost and quality. Project estimation and planning is required for software to monitor stunting. It is hoped that there is a concept that can calculate the estimated cost of this stunting monitoring software. Therefore, it is necessary to create a method that is able to find out these estimates. Then the function point analysis and use case point methods were chosen to measure and calculate the cost-estimation used as reference parameters at the stunting monitoring software development stage. As a result, an accurate estimate was obtained with the use case point method with the estimated results of 10 people designing and creating stunting monitoring software, then 500 man-hours which means 21 working days with a total cost of $20,000 or around Rp. 311,898,000, -. While the Function Point method obtained an FP value of 413.64, an effort value of 4,558,872 people/hour, and also an LOC of 21,923.
Real-Time data Integration dan Modeling Untuk Kebutuhan Business Intelligence Menggunakan Pendekatan Agile Rudi, Rudi Hartono
Jurnal Algoritma Vol 22 No 1 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-1.2159

Abstract

The purpose of this research is to explore how real-time data integration and adaptive modeling can support faster and more accurate data-driven decision making in a dynamic business environment. The Agile BI method allows organizations or companies to respond quickly to changing business needs through flexible iterative cycles. The results of this research show that the use of the Agile BI approach in real-time data integration can be developed by producing visual dashboard products for business analysis and decision-making needs. This research also provides practical advice related to strengthening technological infrastructure, increasing the capacity of human resources, and managing data security to support the implementation of Agile BI optimally.

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