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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 156 Documents
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PREDIKSI PEMAKAIAN AIR BULANAN DI PDAM KECAMATAN TAMALATE MENGGUNAKAN METODE AUTOREGRESSIVE INTEGRATED MOVING AVERAGE (ARIMA) Syarifuddin, Nur Annisa; Wahyuni, Titin; Faisal, Muhammad; Syafaat, Muhammad; Syamsuri, Andi Makbul; AM Hayat, Muhyiddin; Anas, Andi Lukman
PROGRESS Vol 17 No 2 (2025): September
Publisher : P3M STMIK Profesional Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56708/progres.v17i2.471

Abstract

Water consumption forecasting is a crucial aspect of efficient water resource management, particularly in urban areas with increasing demand. This study aims to predict the monthly water usage volume at the PDAM of Tamalate District using the Autoregressive Integrated Moving Average (ARIMA) method. The dataset consists of historical water usage data from January 2022 to December 2024, totaling 36 monthly observations. The analysis process includes stationarity testing using the Augmented Dickey-Fuller (ADF) test, model parameter identification through ACF and PACF plots, and performance evaluation using MAE, RMSE, and MAPE metrics. The results show that the best-performing model is ARIMA, which demonstrates high prediction accuracy, with a MAE of 26,049.80 m³, RMSE of 37,459.00 m³, and MAPE of 4.12%. This model is capable of generating predictions close to actual values and can be relied upon as a basis for PDAM’s water distribution planning. It is expected that this research will contribute to data-driven decision-making and support digital transformation in the public service sector.
IMPLEMENTASI MODEL BUSINESS TO BUSINESS PADA PEMASARAN PRODUK JAMU MENGGUNAKAN FRAMEWORK LARAVEL Dwi Wahyuda, Arya; Sembiring , Boni Oktaviana; Aulia Rahmah, Sabrina
PROGRESS Vol 17 No 2 (2025): September
Publisher : P3M STMIK Profesional Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56708/progres.v17i2.472

Abstract

The advancement of digital technology presents great opportunities for business actors to enhance their competitiveness through more efficient marketing strategies. This study aims to implement the Business to Business (B2B) model in the marketing of traditional herbal products by Jamu Dapoer Niswah using the Laravel Framework and the Agile method. The system developed is a web-based platform with core features such as business partner registration, product catalog, ordering, order tracking, and contract management. The Agile method was chosen for its flexibility in responding to changing user needs through iterative development. This study adopts an iterative approach consisting of planning, implementation, testing, documentation, deployment, and maintenance stages. The implementation results show that the system is capable of accelerating the ordering process, improving transaction accuracy, and expanding the partner market reach. System testing was conducted using the black-box method and showed that all features function as intended. With this system, the marketing and distribution processes of herbal products can be carried out in a more structured and efficient manner, accessible to business partners at any time. This system is expected to become a digital solution that supports B2B marketing transformation in the traditional business sector.
IMPLEMENTASI HYBRID LEXICON-BASED DAN SVM UNTUK KLASIFIKASI ANALISIS SENTIMEN TERHADAP PELATIHAN BBPSDMP KOMINFO MAKASSAR Alam, Nur; Faisal, Muhammad; Bakti, Rizki Yusliana; Syafaat, Muhammad; Syamsuri, Andi Makbul; AM Hayat, Muhyiddin; Anas, Andi Lukman
PROGRESS Vol 17 No 2 (2025): September
Publisher : P3M STMIK Profesional Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56708/progres.v17i2.473

Abstract

The evaluation of government training programs is often hindered by manual analysis of unstructured qualitative feedback, making the process inefficient and subjective. This study aims to implement and evaluate a sentiment classification model using a hybrid Lexicon-Based and Support Vector Machine approach to analyze participants’ perceptions of the Vocational School Graduate Academy training organized by BBPSDMP Kominfo Makassar, as well as to compare the performance of a standard SVM model with a model optimized using Particle Swarm Optimization. This quantitative research employs 2,313 unstructured review data, which undergo text preprocessing, initial lexicon-based labeling, and TF-IDF feature extraction before being classified using an SVM with an RBF kernel. The results show that the SVM model optimized with PSO consistently outperforms the standard model across all four evaluation aspects, with the most significant accuracy improvement observed in the instructor category from 84.71% to 89.02% and in the assessor category reaching 91.46%. PSO optimization has proven effective in enhancing the model’s ability to identify negative sentiments, which represent the minority class. The hybrid approach with PSO optimization is capable of producing a more accurate and balanced classification system, with practical implications as an objective automated evaluation tool.
PENERAPAN ALGORITMA K-NEAREST NEIGHBOR DALAM ANALISIS PEMINJAMAN BARANG PADA DIVISI INVENTARIS TVRI MAKASSAR Risal; Danuputri, Chyquitha; Darniati; AM Hayat, Muhyiddin
PROGRESS Vol 17 No 2 (2025): September
Publisher : P3M STMIK Profesional Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56708/progres.v17i2.474

Abstract

Inventory management in the TVRI Makassar Inventory Division is inefficient due to the lack of a predictive system, hampering proactive asset requirement planning. This study aims to apply the K-Nearest Neighbor (KNN) algorithm to analyze historical borrowing patterns, predict demand for goods three months in advance, and evaluate model accuracy. Using a quantitative approach, this study implements a systematic machine learning workflow, including data preprocessing, temporal feature engineering, class imbalance handling using the Synthetic Minority Over-sampling Technique (SMOTE), and hyperparameter optimization using GridSearchCV. The results show that the optimized KNN model achieved an overall accuracy of 80.18%, significantly outperforming the baseline model. Key findings revealed that the model's performance is contextual, with very high reliability (F1-Score > 0.95) on frequently borrowed assets, and is able to identify strong temporal demand patterns. It is concluded that KNN is effective for segmented inventory demand prediction and has the potential to serve as a basis for TVRI Makassar to adopt a proactive, data-driven inventory management strategy, enabling more efficient resource allocation.
IMPLEMENTASI METODE PROTOTYPE PADA SISTEM PAYMENT GATEWAY UNTUK SEPATU KOTAMA Najmi Hendri Lubis, Nadhira; Hidayati Sinaga, Tantri
PROGRESS Vol 17 No 2 (2025): September
Publisher : P3M STMIK Profesional Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56708/progres.v17i2.475

Abstract

Digital era nowadays, online payment systems have become an essential component in supporting transaction efficiency, especially for enterpreneur such as Toko Sepatu Kotama. The store's current manual payment process causes several issues, including delayed confirmations, risk of data entry errors, and a lack of convenience for customers. Therefore, this study aims to develop a web-based payment gateway system that is secure, efficient, and easy to use. The development method used is the prototype model, which enables iterative processes involving users to ensure that the system meets actual needs. The system is built using the Laravel framework and MySQL, and integrated with Midtrans as the payment service provider. The interface is designed to be responsive for both desktop and mobile devices.Testing using Black Box Testing shows that all main features function properly, including registration, login, order placement, checkout, and payment processing. Admins can also effectively manage products, orders, and sales reports. The system's advantages include real-time payment notifications and direct integration with Midtrans. The system has proven to improve operational efficiency and user convenience. Future development may include automatic shipping tracking, multilingual support, and more diverse payment options such as credit cards and installment plans. It is also recommended to conduct broader user testing to gain more representative feedback from the market.
IMPLEMENTASI WEBGIS UNTUK NAVIGASI RUTE DAN MONITORING HYDRANT PEMADAM KEBAKARAN DI KOTA MEDAN Afriansyah, Rizky; Sinaga, Tantri Hidayati
PROGRESS Vol 17 No 2 (2025): September
Publisher : P3M STMIK Profesional Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56708/progres.v17i2.476

Abstract

Firefighting operations in Medan City still face significant challenges in locating and monitoring the condition of fire Hydrants: out of 118 Hydrant points, only 23 are documented as operational and just 6 are fully functional. This study aims to design and implement a web‑based WebGIS for the fastest route navigation to the nearest Hydrant and real‑time Hydrant condition Monitoring, employing an iterative Prototype methodology. The system is built using PHP & MySQL on the backend, Leaflet.js for interactive mapping and Routing, and AJAX for seamless data Updates. Functional testing (black‑box) confirms all modules Admin Login, Hydrant CRUD, “Nearest Hydrant” Routing, status Updates, and map Refresh operate as expected with average AJAX response times of 0.3 - 0.5 seconds and map load times under 1.5 seconds for 200 points. Field accuracy tests reveal a coordinate deviation of ± 3 meters, while Hydrant search time is reduced from an average of 2 minutes manually to approximately 15 seconds digitally. The responsive interface supports both desktop and mobile access, optimally serving Admin and Field Officer needs. Thus, the system demonstrably enhances firefighting response efficiency and Hydrant data accuracy in Medan City.
PENGEMBANGAN APLIKASI SMARTSCHOOL BERBASIS WEB UNTUK ADMINISTRASI SEKOLAH DASAR DENGAN AGILE SCRUM Ramdhani, Rizky Budi; Zakir, Ahmad
PROGRESS Vol 17 No 2 (2025): September
Publisher : P3M STMIK Profesional Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56708/progres.v17i2.478

Abstract

The development of information technology has encouraged many educational institutions to adopt digital systems in order to improve the efficiency and accuracy of school administration management. However, at SD Qurratu A’yun, administrative processes such as recording student data, teacher data, and financial transactions are still carried out manually, leading to various problems such as data loss, reporting delays, and inconsistent information. Based on a case study at SD Qurratu A’yun, a web-based school administration information system was developed as a digital solution. The system was designed using the Agile method with a Scrum approach, enabling iterative development that is responsive to user needs. The development process involved several stages: product backlog planning, Sprint planning, Sprint backlog development, daily Scrum meetings, Sprint review, and Sprint retrospective. The system is equipped with key features such as teacher, student, and class data management, transaction type management, cash transactions, and financial reports accessible by academic year. System testing showed that the developed solution successfully improved data organization, accelerated reporting processes, and provided ease of access to information in real time for administrators, treasurers, and principals. By applying the Agile (Scrum) method and building a web-based system, this research provides an optimal solution to the challenges of manual administration at SD Qurratu A’yun. The system not only streamlines workflows but also supports the sustainability of school operations in a more efficient and structured manner.
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..
IMPLEMENTASI METODE HYBRID FUZZY JARO WINKLER DAN COSINE SIMILARITY PADA SISTEM PENCARIAN AYAT AL-QURAN BERBASIS TRANSLITERASI LATIN Tahir, Gempar Perkasa; Habi Talib, Emil Agusalim; Rachman, Fahrim Irhamna
PROGRESS Vol 17 No 2 (2025): September
Publisher : P3M STMIK Profesional Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56708/progres.v17i2.482

Abstract

This research addresses the challenge of retrieving Qur’anic verses in Latin transliteration, which is hindered by the absence of a standardized orthography, leading to diverse spelling variations. The study aims to design and implement a hybrid information retrieval system that integrates Fuzzy Jaro-Winkler for lexical similarity and Cosine Similarity on fine-tuned DistilBERT embeddings for semantic relevance. The system workflow begins with preprocessing and normalization of the dataset, followed by initial candidate selection using Jaro-Winkler, and final reranking through semantic similarity scoring. Evaluation was conducted using black-box testing across scenarios including ideal queries, spelling variations, incomplete queries, and varying query lengths. Results show high accuracy for ideal (96%) and varied spelling queries (92%), with performance improving as query length increases, reaching 96% for four-word queries. The hybrid approach effectively bridges lexical and semantic gaps, outperforming single-method baselines, and demonstrates robustness in handling non-standard transliteration in Qur’anic text retrieval.
IMPLEMENTASI HYBRID CNN, FACIAL LANDMARK DAN LIVENESS DETECTION PADA SISTEM ABSENSI WAJAH Akbar DB, Andi Muhammad; Faisal, Muhammad; AM Hayat, Muhyiddin
PROGRESS Vol 17 No 2 (2025): September
Publisher : P3M STMIK Profesional Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56708/progres.v17i2.483

Abstract

This paper presents the implementation of a hybrid approach for face recognition attendance systems, combining Convolutional Neural Network (CNN), facial landmark detection, and liveness detection. The CNN model extracts facial features for identity recognition, while facial landmark detection captures dynamic movements such as eye blinking and mouth motion. Liveness detection ensures system robustness against spoofing attempts including photo and video replay. The system was developed using Python with OpenCV, MediaPipe, and TensorFlow, and tested under multiple spoofing scenarios. Results show a detection accuracy of 95.5%, with real-time performance and resilience against common spoofing threats.

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