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Progresif: Jurnal Ilmiah Komputer
Published by Sekolah Tinggi Manajemen Informatika dan Komputer Banjarbaru
ISSN : 02163284     EISSN : 26850877     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering
Progresif: Jurnal Ilmiah Komputer adalah Jurnal Ilmiah bidang Komputer yang diterbitkan secara periodik dua nomor dalam satu tahun, yaitu pada bulan Februari dan Agustus. Redaksi Progresif: Jurnal Ilmiah Komputer menerima Artikel hasil penelitian atau atau artikel konseptual bidang Komputer.
Arjuna Subject : -
Articles 476 Documents
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Pengukuran Penerimaan Aplikasi BRImo Melalui Technology Acceptance Model di Kecamatan Banyubiru Al Rizal, Majid Ridho; Rahardja, Yani
Progresif: Jurnal Ilmiah Komputer Vol 21, No 2: Agustus 2025
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/progresif.v21i2.3160

Abstract

The digital transformation in banking services encourages people to shift to mobile banking, including the BRImo application. Nevertheless, adoption in Banyubiru District remains relatively low as many still rely on conventional transactions. This study aims to analyze BRImo acceptance using the Technology acceptance model (TAM) with variables Perceived Ease of Use (PEU), Perceived Usefulness (PU), Attitude Toward Using (ATU), and Behavioral Intention (BI). A quantitative survey involving 50 respondents was conducted, and the data were processed using Partial Least Square (PLS-SEM). The results indicate that PEU and ATU significantly influence BRImo acceptance, while PU has a positive but limited effect on BI. The findings conclude that ease of use and positive attitudes are the key factors driving rural communities to adopt BRImo mobile banking services.Keywords: BRImo; Mobile banking; Technology acceptance model; Partial Least Square (PLS-SEM); Banyubiru AbstrakTransformasi digital di sektor perbankan mendorong masyarakat untuk beralih ke layanan mobile banking, salah satunya aplikasi BRImo. Namun, tingkat pemanfaatan di Kecamatan Banyubiru masih rendah karena sebagian besar masyarakat lebih memilih transaksi manual. Penelitian ini bertujuan menganalisis penerimaan BRImo dengan menggunakan kerangka Technology acceptance model (TAM) yang melibatkan variabel Perceived Ease of Use (PEU), Perceived Usefulness (PU), Attitude Toward Using (ATU), dan Behavioral Intention (BI). Metode yang digunakan adalah survei kuantitatif dengan 50 responden, kemudian data diolah melalui Partial Least Square (PLS-SEM). Hasil menunjukkan bahwa PEU dan ATU berpengaruh signifikan terhadap penerimaan BRImo, sedangkan PU berpengaruh positif tetapi terbatas terhadap BI. Penelitian ini menyimpulkan bahwa kemudahan penggunaan dan sikap positif merupakan faktor kunci dalam mendorong masyarakat pedesaan untuk mengadopsi layanan mobile banking BRImo.Kata Kunci: BRImo; Mobile banking; Technology acceptance model; Partial Least Square (PLS-SEM); Banyubiru
Deteksi Keaslian Uang Rupiah Menggunakan Metode Canny Edge Detection dan K-Mean Clustering Fadila, Selvana; Abdullah, Dedy
Progresif: Jurnal Ilmiah Komputer Vol 21, No 2: Agustus 2025
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/progresif.v21i2.2922

Abstract

The escalating problem of counterfeit currency in various countries, primarily due to easy access to information on manufacturing methods and advancements in color printing technology, renders traditional '3D' identification methods less effective. This research aims to design an authenticity detection system for Rupiah banknotes using a digital image processing approach. This study utilized a total of 40 Rupiah banknote images as test objects, comprising 10 genuine and 10 counterfeit images for each of the Rp 50,000 and Rp 100,000 denominations. The methodology applied included image acquisition, conversion to grayscale, followed by image segmentation. This system integrates Canny Edge Detection to extract edge details and K-Means Clustering for image grouping. Key features analyzed were Aspect Ratio and Edge Density, which assist in differentiating between genuine and counterfeit banknotes. Test results indicate that the developed system could identify the authenticity of Rupiah banknotes with an average accuracy of 87.50%. This combined approach offers an effective solution for Rupiah banknote authentication.Keyword: Authenticity Rupiah Banknotes; Canny Edge Detection; K-Means Clustering; Aspect Ratio, Edge Density. AbstrakPermasalahan uang palsu yang terus meningkat di berbagai negara, terutama dengan kemudahan akses informasi dan teknologi pencetak warna, menjadikan metode identifikasi tradisional '3D' kurang efektif. Penelitian ini bertujuan untuk merancang sebuah sistem deteksi keaslian uang kertas Rupiah menggunakan pendekatan pengolahan citra digital. Penelitian ini menggunakan total 40 citra uang kertas Rupiah sebagai objek uji, terdiri dari 10 gambar uang asli dan 10 gambar uang palsu untuk masing-masing nominal Rp 50.000 dan Rp 100.000. Metodologi yang diterapkan meliputi akuisisi citra, konversi citra menjadi skala abu-abu, diikuti dengan segmentasi citra. Sistem ini mengintegrasikan Canny Edge Detection untuk mengekstraksi detail tepi dan K-Means Clustering untuk pengelompokan citra. Fitur-fitur kunci yang dianalisis adalah Aspect Ratio dan Edge Density, yang membantu dalam hal membedakan uang asli dan palsu. Hasil pengujian menunjukkan bahwa sistem yang dibangun mampu mengidentifikasi keaslian uang Rupiah dengan akurasi rata-rata sebesar 87.50%. Pendekatan gabungan ini memberikan solusi efektif untuk autentikasi uang kertas Rupiah.Kata kunci: Keaslian Uang Rupiah; Canny Edge Detection; K-Means Clustering; Aspect Ratio; Edge Density.
Evaluasi Kelayakan Platform Ucapan Digital dengan Metode Heuristic Evaluation Gala, Aryatriwulan Buli; Chernovita, Hanna Prillysca
Progresif: Jurnal Ilmiah Komputer Vol 21, No 2: Agustus 2025
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/progresif.v21i2.3112

Abstract

The digital greeting platform of Satya Wacana Christian University (UKSW) was developed as an environmentally friendly solution to replace physical greeting media in ceremonial events. This study aims to evaluate the usability level of the platform using the Heuristic Evaluation method based on Nielsen and Molich’s ten principles. Data were collected through questionnaires distributed to five respondents and in-depth interviews with three of them. The evaluation results indicate five principles with the highest severity levels, namely Help and Documentation (3.8), Visibility of System Status (3.6), Error Prevention (3.6), User Control and Freedom (3.4), and Flexibility and Efficiency of Use (3.2). Identified issues include the absence of user guides, lack of process feedback, weak input validation, limited navigation, and minimal design variations. Recommended improvements involve adding a help page, process indicators, input validation, main navigation buttons, and more varied greeting templates. These findings confirm the effectiveness of heuristic evaluation in identifying interface weaknesses and provide guidance for developing a more user-friendly system.Keywords: Digital greeting platform; Heuristic Evaluation; Usability; User experience AbstrakPlatform ucapan digital Universitas Kristen Satya Wacana (UKSW) dikembangkan sebagai solusi ramah lingkungan untuk menggantikan media ucapan fisik pada acara seremonial. Penelitian ini bertujuan mengevaluasi tingkat usability platform tersebut menggunakan metode Heuristic Evaluation berdasarkan sepuluh prinsip Nielsen and Molich. Penilaian dilakukan melalui kuesioner kepada lima responden serta wawancara mendalam terhadap tiga di antaranya. Hasil evaluasi menunjukkan lima prinsip dengan tingkat keparahan tertinggi, yaitu Help and Documentation (3,8), Visibility of System Status (3,6), Error Prevention (3,6), User Control and Freedom (3,4), dan Flexibility and Efficiency of Use (3,2). Permasalahan yang ditemukan meliputi ketiadaan panduan penggunaan, tidak adanya umpan balik proses, lemahnya validasi input, keterbatasan navigasi, serta minimnya variasi desain. Rekomendasi perbaikan meliputi penambahan halaman bantuan, indikator proses, validasi format input, tombol navigasi utama, serta variasi template ucapan. Temuan ini menegaskan efektivitas evaluasi heuristik dalam mengidentifikasi kelemahan antarmuka serta memberikan arahan pengembangan sistem yang lebih user-friendly.Kata kunci: Platform ucapan digital; Heuristic Evaluation; Usability; Pengalaman pengguna
Prediksi Risiko Kredit Nasabah Menggunakan Algoritma Data Mining: Studi Kasus pada PT Toyota Astra Finance Permadani, Icha Winadya; Sulistyo, Raka; Fadli, Muhammad; Susanto, Erliyan Redy
Progresif: Jurnal Ilmiah Komputer Vol 21, No 2: Agustus 2025
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/progresif.v21i2.2909

Abstract

This study aims to develop a credit risk prediction model for customers at PT Toyota Astra Financial Services using data mining algorithms, specifically Random Forest and XGBoost. In response to the challenge of non-performing loans (NPL), machine learning-based predictive models offer an effective solution to identify potential risks early. The research utilizes historical customer data encompassing demographic information, employment status, and loan history. After data preprocessing, the models were evaluated using accuracy, precision, recall, F1-score, and ROC-AUC metrics. The results indicate that XGBoost outperformed other models with an accuracy of 91.67% and an F1-score of 0.89 for the positive class. These findings demonstrate that applying machine learning algorithms can significantly enhance credit selection efficiency and reduce potential losses from defaulted loans.Keywords: Credit Risk; Machine learning; Random Forest; XGBoost, Data mining. AbstrakPenelitian ini bertujuan untuk membangun model prediksi risiko kredit nasabah pada PT Toyota Astra Financial Services dengan memanfaatkan algoritma data mining, khususnya Random Forest dan XGBoost. Dalam menghadapi tantangan kredit macet, model prediktif berbasis machine learning dapat memberikan solusi yang efektif untuk mengidentifikasi potensi risiko sejak dini. Penelitian ini menggunakan data historis nasabah yang mencakup informasi demografi, status pekerjaan, dan riwayat pinjaman. Setelah melalui tahap pra-pemrosesan data, model dievaluasi menggunakan metrik akurasi, presisi, recall, F1-score, dan ROC-AUC. Hasil menunjukkan bahwa XGBoost memiliki performa terbaik dengan akurasi sebesar 91,67% dan F1-score 0,89 pada kelas positif. Temuan ini menunjukkan bahwa penerapan algoritma machine learning dapat meningkatkan efisiensi seleksi kredit dan mengurangi potensi kerugian akibat kredit bermasalah.Kata kunci: Risiko Kredit; Machine learning; Random Forest; XGBoost; Data mining
Pengembangan Sistem ERP untuk Distribusi Produk PT Solomon Indo Global: Modul Shipping, Inventory, dan User Management Zahran, Afif Ghani; Hadwiyanti, Rizka; Putra, Agung Brastama
Progresif: Jurnal Ilmiah Komputer Vol 21, No 2: Agustus 2025
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/progresif.v21i2.3077

Abstract

Digital transformation is driving companies to integrate technology to improve efficiency. PT Solomon Indo Global, a fast-moving consumer goods company, faces distribution challenges due to a lack of system integration, such as the absence of multi-warehouse stock records, undocumented distribution flows, and unclear partner roles. This study aims to develop an integrated Enterprise Resource Planning (ERP) system with a focus on the User Management, Inventory, and Shipment modules. The methodology employs a 5-Stage ERP Implementation approach (Project Preparation, Business Blueprint, Realization, Final Preparation, Go Live and Support) without a direct implementation phase. Problem identification was conducted through interviews and observations, followed by mapping of the as-is and to-be business processes, and system development using the Scrum method (backlog, sprint, daily Scrum, review, retrospective). The research results produced an integrated ERP system design that includes the main modules of user management, inventory, shipment, and sales support, which has proven to improve the efficiency of the company's distribution process.Keywords: Enterprise Resource Planning; Supply chain; Scrum Method; Logistic AbstrakTransformasi digital mendorong perusahaan mengintegrasikan teknologi guna meningkatkan efisiensi. PT Solomon Indo Global, sektor barang konsumsi cepat, menghadapi tantangan distribusi akibat kurangnya integrasi sistem, seperti tidak adanya pencatatan stok multi-gudang, alur distribusi tidak terdokumentasi, dan peran mitra yang belum jelas. Penelitian ini bertujuan mengembangkan sistem Enterprise Resource Planning (ERP) terintegrasi dengan fokus pada modul User Management, Inventory, dan Shipment. Metodologi menggunakan pendekatan 5 Stages ERP Implementation (Project Preparation, Business Blueprint, Realization, Final Preparation, Go Live and Support) tanpa tahap implementasi langsung. Identifikasi masalah dilakukan melalui wawancara dan observasi, dilanjutkan pemetaan proses bisnis as-is dan to-be, serta pengembangan sistem menggunakan metode scrum (backlog, sprint, daily scrum, review, retrospective). Hasil penelitian menghasilkan rancangan sistem ERP terintegrasi yang memuat modul utama user management, inventory, shipment, serta dukungan sales, yang terbukti mampu meningkatkan efisiensi alur distribusi perusahaan.Kata Kunci: Enterprise Resource Planning; Rantai pasok; Metode scrum; Logistic
Sistem Rekomendasi Kuliner Karanganyar Menggunakan Metode Hybrid Recommendation Putri, Radya Prameswari; Maulindar, Joni; Pradana, Afu Ichsan
Progresif: Jurnal Ilmiah Komputer Vol 21, No 2: Agustus 2025
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/progresif.v21i2.3105

Abstract

Karanganyar has many culinary tourist destinations, but the number of diverse choices often makes it difficult for users to choose where to eat according to their preferences. Therefore, this research aims to help users find culinary places based on special menus. The recommendation system will be developed using a hybrid approach by combining content-based filtering and collaborative filtering. The content-based method matches the special menu with user input using cosine similarity, while collaborative filtering calculates the score from the normalized rating and the number of reviews using the weighted sum. A weight of 0.6 is given for content-based and 0.4 for collaborative because direct preference for menus is considered more dominant. The test was carried out using 5 different menus using precision and recall, with the test results for 100% recall, and the precision got a score of 75.42% because there are still recommendations displayed in the system that only have similar characteristics but are not really relevant to the user's preferencesKeywords: Collaborative filtering; Content-based filtering; Hybrid recommendation; Culinary recommendation; Recommendation system. AbstrakKaranganyar memiliki banyak destinasi wisata kuliner, namun jumlah pilihan yang beragam sering menyulitkan pengguna dalam menentukan tempat makan sesuai preferensi. Oleh karena itu, penelitian ini bertujuan untuk membantu pengguna menemukan tempat kuliner berdasarkan menu spesial. Sistem rekomendasi yang akan dikembangkan menggunakan pendekatan hybrid dengan menggabungkan content-based filtering dan collaborative filtering. Metode content-based mencocokkan menu spesial dengan input pengguna menggunakan cosine similarity, sedangkan collaborative filtering menghitung skor dari rating yang dinormalisasi dan jumlah ulasan dengan menggunakan weighted sum. Bobot 0,6 diberikan untuk content-based dan 0,4 untuk collaborative karena preferensi langsung terhadap menu dinilai lebih dominan. Pengujian dilakukan dengan menggunakan 5 menu yang berbeda menggunakan precision dan recall, dengan mendapatkan hasil pengujian untuk recall 100%, dan precision mendapatkan nilai 75,42% karena masih ada rekomendasi yang ditampilkan disistem yang hanya mirip karakteristiknya tetapi tidak benar-benar relevan dengan preferensi penggunaKata Kunci: Collaborative filtering; Content-based filtering; Hybrid recommendation; Rekomendasi kuliner; Sistem rekomendasi 

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