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Sitti Arni
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Jurnal Informatika Progres
Published by STMIK PROFESIONAL MAKASSAR
ISSN : 20868359     EISSN : 2797622X     DOI : https://doi.org/10.56708/progres.v14i1.300
Core Subject : Science,
Computer Science & IT
Jurnal Informatika Progres merupakan jurnal Blind Peer-Review yang dikelola secara profesional dan diterbitkan oleh P3M STMIK Profesional Makassar dalam upaya membantu peneliti, akademisi, dan praktisi untuk mempublikasikan hasil penelitiannya. Jurnal ini didedikasikan untuk publikasi hasil penelitian dalam bidang yang memuat artikel tentang Teknologi, Komunikasi, Informasi dan Komputer. Terbit dua kali setiap tahun, 2 nomor 1 volume, yaitu pada bulan April dan September. Semua publikasi di Jurnal Informatika Progres ini bersifat akses terbuka yang memungkinkan artikel tersedia secara online tanpa berlangganan apapun.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 9 Documents
 1 
Search results for , issue "Vol 17 No 1 (2025): April" : 9 Documents clear
IMPLEMENTASI ALGORITMA YOLO UNTUK MENDETEKSI JENIS TANAMAN HIAS BERBASIS ANDROID Soekarta, Rendra; Aras, Suhardi; Rahman, Muh Fadhil
PROGRESS Vol 17 No 1 (2025): April
Publisher : P3M STMIK Profesional Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56708/progres.v17i1.456

Abstract

Ornamental plants possess high aesthetic value and environmental benefits, yet identifying their species often poses a challenge, especially for beginners. This study aims to develop an Android-based application employing the You Only Look Once version 8 (YOLOv8) algorithm to detect ornamental plant species through leaf images in real-time. The dataset comprises 1,096 images of ornamental plant leaves, including snake plant (Sansevieria), aloe vera (Aloe vera), and coral cactus (Cereus peruvianus). The data were annotated using bounding box techniques, and the model was trained on Google Colab with an 80:20 split between training and testing datasets. The training resulted in an accuracy rate of 96% based on the mean Average Precision (mAP) metric. The application was developed using Android Studio with a user-friendly interface, enabling real-time detection on Android devices with a minimum RAM specification of 3 GB. Application testing involved black-box testing to ensure functionality and usability testing with 31 respondents, revealing a user satisfaction rate of 87%. Some challenges encountered included the impact of lighting on detection accuracy and result variability across different devices. This study contributes to the utilization of artificial intelligence technology for biodiversity education and supports environmental conservation efforts
IMPLEMENTASI SISTEM PENDAFTARAN SISWA BARU BERBASIS WEB MENGGUNAKAN ALGORITMA SAW DI SANGGAR KEGIATAN BELAJAR UJUNG PANDANG Sarumpaet, Calvin Bonar; Fajri, Hidayatul; Baharuddin, Suardi Hi
PROGRESS Vol 17 No 1 (2025): April
Publisher : P3M STMIK Profesional Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56708/progres.v17i1.464

Abstract

The new student registration process at Sanggar Kegiatan Belajar (SKB) Ujung Pandang was previously conducted manually, resulting in several issues such as data processing delays, file accumulation, and lack of transparency in selection. This study aims to develop a web-based registration information system integrated with the Simple Additive Weighting (SAW) algorithm to enhance the efficiency and objectivity of the selection process. The system was developed using the Waterfall model and implemented using PHP and MySQL-based web technology. The implementation results show that the system can automate registration and selection in real-time. The SAW algorithm effectively produces objective participant rankings based on criteria such as exam scores, age, and domicile. Evaluation indicates that the system improves selection speed, result accuracy, and facilitates data management for users. It can be concluded that this system provides significant benefits for both SKB administrators and applicants and is relevant in supporting the digital transformation of non-formal education.
ANALISIS PERAMALAN KLAIM TABUNGAN HARI TUA MENGGUNAKAN METODE ARIMA PADA PT. ASABRI CABANG MAKASSAR Issan; Pagasing, Indri Mita; Harmin, Andi; Arni, Sitti
PROGRESS Vol 17 No 1 (2025): April
Publisher : P3M STMIK Profesional Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56708/progres.v17i1.424

Abstract

The Autoregressive Integrated Moving Average (ARIMA) method was used in this study to forecast the number of Old Age Savings (THT) insurance claims at PT ASABRI (Persero) Makassar Branch. The data used consisted of 37 monthly observations of THT claims from May 2022 to May 2025. The model identification results indicate that the ARIMA (1,1,0) model is appropriate, with a p-value <0.05 and residuals similar to white noise. This forecast was made for June to December 2025. According to the Mean Absolute Percentage Error (MAPE) value of 17,7123%, this model has a fairly high level of accuracy. It is hoped that the results of this study will assist businesses in making financial decisions and strategic planning.
IMPLEMENTASI ALGORITMA APRIORI UNTUK ANALISIS PERSEDIAAN MATERIAL DI WAREHOUSE PT. TELKOM AKSES MAKASSAR Wal Ikram, Dzul Jalali; Sadrin, Ahmad Rifai; Moeis, Dikwan; Rosnani
PROGRESS Vol 17 No 1 (2025): April
Publisher : P3M STMIK Profesional Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56708/progres.v17i1.453

Abstract

This research aims to implement Apriori algorithm for data mining in material inventory management at PT. Telkom Akses Makassar. Apriori algorithm identifies frequent itemsets and generates association rules from transaction data to optimize warehouse stock management. The methodology includes data collection through observation, interviews, and historical transaction datasets. Data processing uses Apriori to calculate support, confidence, and lift metrics. The results indicate that frequent item combinations can improve planning accuracy and reduce stockouts. A web-based application, Material Analyzer, was developed for analysis and visualization, featuring dashboard, analysis, history, and visualization modules. This study contributes practically by supporting logistics decision-making and theoretically by expanding data mining applications in inventory systems.
IMPLEMENTASI APLIKASI TUR VIRTUAL 360 BERBASIS VIRTUAL REALITY UNTUK PENGENALAN KAMPUS UNITAMA Muhajirin; Rahman Nasir, Khaidir; Annah; Nugroho, Muhammad Syarif
PROGRESS Vol 17 No 1 (2025): April
Publisher : P3M STMIK Profesional Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56708/progres.v17i1.481

Abstract

This research focuses on the development of an Android-based virtual tour application to introduce the facilities and infrastructure of Universitas Teknologi Akba Makassar (UNITAMA) using Virtual Reality (VR) technology and the 360-degree panoramic image method. The objective of this study is to create an interactive medium for students, prospective new students, and their parents to access detailed information about the campus environment. The research employs the Multimedia Development Life Cycle (MDLC) method, consisting of concept, design, material collection, assembly, testing, and distribution. Testing results using the Blackbox method showed that the application functions properly, while user experience evaluation recorded an average score above 91%, with clarity achieving the highest score of 98.3%. This indicates that the application is effective as a digital campus introduction medium and provides an interactive and realistic experience..
PERBANDINGAN KINERJA K-NEAREST NEIGHBORS DAN CONVOLUTIONAL NEURAL NETWORK UNTUK KLASIFIKASI CITRA KONDISI PERMUKAAN JALAN Jong, Fenny; Handhayani, Teny
PROGRESS Vol 17 No 1 (2025): April
Publisher : P3M STMIK Profesional Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56708/progres.v17i1.426

Abstract

Improving road infrastructure quality is an important aspect of transportation development and road user safety. Automatically assessing road surface conditions can accelerate maintenance and repair efforts. This study compares two classification methods, K-Nearest Neighbors (KNN) and Convolutional Neural Network (CNN), to evaluate road surface conditions based on digital images. Texture features are extracted using the Gray Level Co-occurrence Matrix (GLCM), including Contrast, Homogeneity, Energy, and others, to enhance the classification accuracy in KNN, while feature extraction and classification in CNN are performed automatically. The dataset used in this research consists of 1500 images of road surfaces with three different conditions: smooth, cracked, and potholes. Each condition contains 500 images with a resolution of 300x300 pixels. The results show that the KNN algorithm achieves an accuracy of 57.2%, while CNN demonstrates the best performance with an accuracy of 93.8%. for 80% training data and 20% testing data
PREDIKSI HARGA DAGING SAPI DI KOTA JAKARTA PUSAT MENGGUNAKAN LSTM DAN GRU Adithya Putra, Farhan; Handhayani, Teny
PROGRESS Vol 17 No 1 (2025): April
Publisher : P3M STMIK Profesional Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56708/progres.v17i1.438

Abstract

This study analyzes the performance of two algorithms, Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU), in predicting data from the PIHPS website, focusing on beef commodity prices. The dataset was divided into two proportions: 80:20 and 70:30, and evaluated using Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and coefficient of determination (R²). The experimental results showed that GRU with 128 units and a 70:30 proportion achieved the best performance, with metrics of MAE at 170, RMSE at 390.2889, and R² at 0.902. The goal of this research is to determine the most suitable algorithm and unit configuration for this dataset. Future research is expected to integrate additional data with more complex models to improve prediction accuracy.
USER INTERFACE TESTING SEBAGAI LANGKAH MEMINIMALISIR RISIKO DIGITALISASI SARANA PRASARANA SEKOLAH Tasdik, Komarudin; Al-Adawiyah, Anggia Rabiyah; Subeno, Bambang
PROGRESS Vol 17 No 1 (2025): April
Publisher : P3M STMIK Profesional Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56708/progres.v17i1.451

Abstract

User Interface (UI) design is one of the current specialized jobs so that there are special vacancies for the profession of UI designer. Along with this phenomenon, there are still schools that do not have a mobile application to facilitate their management, including asset data management. This study aims to add references on UI design along with how to test the design that can be implemented by programmers more easily. The design testing process is carried out using usability testing. Usability measurements are carried out on three parameters, namely effectiveness, efficiency, and satisfaction. The results obtained that as one of the solution recommendations, a mobile prototype was designed with the main features including the Borrow Page and Asset Borrowing Form. From the results of testing the prototype, the results obtained that the prototype that had been created obtained an Effectiveness aspect value of 100%, Efficiency of 0.152 goals/sec, and a SUS Score of 92 (Best Imaginable)
PENERAPAN METODE SMART DALAM PEMILIHAN PERPUSTAKAAN TINGKAT SMP TERBAIK DI KOTA MAKASSAR Jaylani, Ichsan; Rivan, Muhammad Fitrah; Harmin, Andi; Yadi, Asri
PROGRESS Vol 17 No 1 (2025): April
Publisher : P3M STMIK Profesional Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56708/progres.v17i1.470

Abstract

The library plays a crucial role in supporting education and literacy. However, determining the best library in Makassar, particularly at the junior high school level, remains challenging due to various qualitative factors. This research applies the Simple Multi Attribute Rating Technique (SMART) method to evaluate and rank libraries objectively based on seven criteria: book collection, facilities, service, accessibility, innovation and technology, literacy activities, and cleanliness and safety. Data was collected through observations, questionnaires, and interviews across selected libraries in Makassar. The system developed provides a decision support tool that calculates weighted scores and recommends the best-performing library. Results show that SMART effectively delivers transparent and structured decision-making to support library quality assessment and policy recommendations.

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