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All Journal Jurnal Simetris Jurnal Ilmu Komputer dan Agri-Informatika Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Edukasi dan Penelitian Informatika (JEPIN) Scientific Journal of Informatics Journal of Information Systems Engineering and Business Intelligence Register: Jurnal Ilmiah Teknologi Sistem Informasi International Journal of Artificial Intelligence Research Jurnal Penelitian Pendidikan IPA (JPPIPA) Jurnal Sains dan Informatika Jurnal Ilmiah Matrik Jurnal Sisfokom (Sistem Informasi dan Komputer) Journal of Information Systems and Informatics Jurnal Teknologi Informatika dan Komputer Djtechno: Jurnal Teknologi Informasi
Usman Ependi
Universitas Bina Darma
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Materials Science & Nanotechnology Mathematics Physics

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Advanced Techniques for Anomaly Detection in Blockchain: Leveraging Clustering and Machine Learning Ferdiansyah, Ferdiansyah; Ependi, Usman; Tasmi, Tasmi; Haikal, Muhammad; Mikko, Mikko
Journal of Information System and Informatics Vol 7 No 1 (2025): March
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v7i1.1047

Abstract

Blockchain technology has revolutionized data security and transaction transparency across various industries. However, the increasing complexity of blockchain networks has led to anomalies that require further investigation. This study aims to analyze anomalies in blockchain systems using machine learning approaches. Various anomaly detection techniques, including supervised and unsupervised methods, are evaluated for their effectiveness in identifying irregularities. The results indicate that machine learning models can detect anomalies with high accuracy, providing insights into potential threats and system vulnerabilities. The findings of this research contribute to improving blockchain security and developing more robust monitoring systems.
Enhancing Usability of the Qualitiva Educational Applications: A Mixed-Methods Study using SUS and Heuristic Evaluation. Berlianti, Marutha; Ependi, Usman; Novaria Kunang, Yesi; Haidar Mirza, A.
Jurnal Ilmu Komputer dan Agri-Informatika Vol. 12 No. 1 (2025)
Publisher : Sekolah Sains Data, Matematika, dan Informatika. Institut Pertanian Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/jika.12.1.79-90

Abstract

Studi ini mengevaluasi kegunaan aplikasi Qualitiva menggunakan metode System Usability Scale (SUS) dan Heuristic Evaluation (HE). Tujuan dari penelitian ini adalah untuk mengidentifikasi kekuatan dan kelemahan aplikasi, serta memberikan rekomendasi perbaikan. Pendekatan kuantitatif digunakan dengan mendistribusikan kuesioner SUS kepada 100 responden, sementara pendekatan kualitatif melibatkan evaluasi heuristik oleh dua ahli usability. Hasil menunjukkan skor rata-rata SUS sebesar 69,00 (Grade C), yang menunjukkan penerimaan pengguna secara umum namun menyoroti beberapa area yang perlu perbaikan dalam kecepatan, desain, keamanan data, dan efisiensi sistem. Evaluasi heuristik mengidentifikasi masalah seperti kejelasan status sistem, penggunaan terminologi yang ramah pengguna, desain antarmuka, dan fitur pencegahan kesalahan. Penelitian ini meningkatkan pemahaman tentang kegunaan dalam aplikasi pendidikan dan memberikan rekomendasi yang dapat ditindaklanjuti untuk meningkatkan pengalaman pengguna, termasuk mengoptimalkan kecepatan, memperbaiki antarmuka, dan meningkatkan panduan pengguna.
SYSTEM USABILITY SCALE VS HEURISTIC EVALUATION: A REVIEW Ependi, Usman; Kurniawan, Tri Basuki; Panjaitan, Febriyanti
Simetris: Jurnal Teknik Mesin, Elektro dan Ilmu Komputer Vol 10, No 1 (2019): JURNAL SIMETRIS VOLUME 10 NO 1 TAHUN 2019
Publisher : Fakultas Teknik Universitas Muria Kudus

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (5004.496 KB) | DOI: 10.24176/simet.v10i1.2725

Abstract

Usability merupakan salah satu bidang ilmu untuk menganalisa atau menguji tingkat kemudahan penggunaan perangkat lunak.  Usability atau yang sering dikenal dengan kebergunaan adalah teknik pengujian atau pengukuran aplikasi perangkat lunak yang dilihat dari lima aspek yaitu  learnability, efficiency, memorability, errors dan satisfaction. Untuk melakukan analisa atau pengujian usability dapat dilakukan dengan pendekatan heuristic evaluation (HE) dan system usability scale (SUS). Heuristic evaluation (HE) merupakan pengujian dengan cara melibatkan ahli dalam proses pengerjaannya dan system usability scale (SUS) merupakan pengujian dengan cara melibatkan pengguna akhir (end user) dalam proses pengerjaannya. Untuk itu dalam penelitian dilakukan pengkajian antara heuristic evaluation (HE) dan system usability scale (SUS). Dari hasil kajian didapat bahwa heuristic evaluation (HE) dapat dilakukan bersamaan dengan teknik pengujian lain namun membutuhkan biaya yang besar serta proses pengujian yang lebih mudah. Sedangkan system usability scale (SUS) proses pengujian dan perhitungan lebih rumit namun dapat dilakukan dengan jumlah sampel yang sedikit.
ANALISIS TINGKAT KEMATANGAN DOMAIN LAYANAN SISTEM PEMERINTAHAN BERBASIS ELEKTRONIK MENGGUNAKAN E-GOVERNMENT MATURITY MODEL PADA PEMERINTAH KOTA PALEMBANG pratama, rianda; Herdiansyah, Muhammad Izman; Sutabri, Tata; Amin, Zaid; Ependi, Usman
Djtechno: Jurnal Teknologi Informasi Vol 6, No 1 (2025): April
Publisher : Universitas Dharmawangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46576/djtechno.v6i1.6198

Abstract

Pemerintah negara Indonesia melakukan percepatan pembangunan pemerintahan yang berbasis elektronik. Pada tahun 2018 Presiden Republik Indonesia mengeluarkan peraturan yang dituangkan ke dalam Perpres Nomor 95 Tahun 2018 tentang sistem pemerintahan berbasis elektronik. SPBE terdiri dari 4 domain utama yaitu domain kebijakan, tata kelola, manajemen dan layanan. Berdasarkan dari nilai bobot domain, domain layanan merupakan domain yang memiliki bobot nilai tertinggi yaitu 45,50%. Guna mendukung percepatan SPBE perlunya dilakukan penilaian tingkat kematangan domain layanan SPBE. Saat ini di kota Palembang belum melakukan penilaian secara sistematis terhadap nilai domain layanan SPBE maka dari itu perlu dilakukan penilaian secara sistematis menggunakan  framework SPBE berdasarkan Permenpan-RB Nomor 59 Tahun 2020. Domain layanan SPBE terbagi menjadi dua aspek yaitu aspek layanan administrasi pemerintahan berbasis elekronik yang terdiri dari 10 indikator penilaian dan layanan publik berbasis elektronik yang memiliki 6 indikator penilaian. Hasil penilaian 16 Indikator domain layanan tersebut menghasilkan nilai indeks aspek layanan administrasi pemerintahan sebesar 3,45 dan indeks aspek layanan publik sebesar 4,0. Berdasarkan hasil nilai indeks aspek tersebut dapat diketahui capaian nilai indeks domain layanan sistem pemerintahan berbasis elektronik pada pemerintah kota Palembang yaitu 3,67 dengan predikat Sangat Baik
Pengembangan Aplikasi Mobile Travel Guide pada Provinsi Sumatera Selatan Ependi, Usman; Panjaitan, Febriyanti; Syakti, Firamon
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 7 No 3: Juni 2020
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2020732107

Abstract

Sektor pariwisata adalah komponen penting bagi sebuah negara dalam meningkatkan pendapatan negara. Dalam mengelolah sektor pariwisata salah satu faktor penting adalah penyediaan informasi terutama petunjuk perjalanan wisata terutama tujuan wisata dan hal yang terkaitan dengannya. Di Indonesia terutama di Provinsi Sumatra Selatan berbagai upaya telah dilakukan pemerintah dalam menyediakan informasi pariwisata diantaranya melalui iklan, koran dan televisi. Namun penggunaan media tersebut belum cukup efektif yang dibebabkan tidak dapat diakses langsung (real time) oleh wisatawan. Selain itu, media ini memiliki keterbatasan dalam menjangkau wisatawan karena kegiatan pariwisata yang dilakukan wisatawan. Untuk itu didalam penelitian ini dilakukan pengembangan aplikasi mobile yang dikhususkan untuk penyediaan informasi wisata yang ada di Provinsi Sumatra Selatan. Proses pengembangan aplikasi mobile yang digunakan adalah Mobile D, dengan tahapan explore, initialize, productionize, stabilize, system test dan fix. Informasi yang tersedia didalam aplikasi ini terdiri dari tujuan wisata dan hal yang terkaitan dengannya. Dengan demikian wisatawan dapat dengan mudah mencari informasi berkaitan dengan tujuan wisata dan yang terkait dengan pariwisata yang ada di Provinsi Sumatra Selatan yang dibuktikan dengan hasil pengujian dengan istrumen heuristic evaluation yang mendapatkan nilai rerata 0.2 dan system usability scale mendapatkan nilai rerata 84.75. Nilai pengujian menunjukkan bawah aplikasi mobile yang dihasilkan tidak memiliki masalah usability dan dapat diterima oleh pengguna. Sesuai kondisi tersebut diharapkan wisatawan dapat dengan mudah dalam mencari informasi tentang parwisata dan hal terkait dengannya melalui perangkat smartphone yang mereka miliki.AbstractThe tourism sector is an important component for a country to increase its income. In managing the tourism sector, an important factor is to provide information on travel guides that include tourism destinations and matters related to travel. In Indonesia, especially in the South Sumatra Province, various efforts have been made to provide information to travelers, such as through advertising, pamphlets, newspapers, and television. However, these media are not effective because travelers cannot access them in real-time. Besides, these media have limitations in reaching tourists due to tourism activities. For this reason, in the research presented in this paper, the development of the mobile application as a tourism information media in the South Sumatra Province was carried out. The process of developing a mobile application used is Mobile D, with stages of exploring, initialize, production, stabilize, system test, and fix. The information available in this application consists of tourism destinations and matters related to travel. Therefore, travelers can easily search for a tourism destination and everything related to tourism, especially in South Sumatra Province based on testing results using heuristic evaluation that got average score 0.2 and using system usability scale that got average score 84.75. From the testing result of mobile application, the mobile application does not have usability problems and can be accepted by the user. According to these conditions, travelers are expected to easily find information about tourism and related matters through their smartphone devices. 
Principal Component Analysis and Bacterial Foraging Optimization for Credit Scoring Arjun, Jennifer; Kisworo, Marsudi Wahyu; Negara, Edi Surya; Ependi, Usman
Jurnal Teknologi Informatika dan Komputer Vol. 11 No. 1 (2025): Jurnal Teknologi Informatika dan Komputer
Publisher : Universitas Mohammad Husni Thamrin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37012/jtik.v11i1.2515

Abstract

Information technology in the current era is developing very quickly. Information systems themselves are found in various aspects of life, such as health, law, education and finance. With the improvement of information systems, systems can be created as considerations for making decisions or agreements. Credit scoring is a status that is usually held by banks or other financial institutions and contains data from debtors who have applied for credit at certain banks or financial institutions. There are many attributes in determining whether someone will get good credit or bad credit status. Therefore, a fast and accurate classification method is needed. This research proposes the use of Principal Component Analysis to reduce several attributes without reducing the attributes that are important or crucial in determining. This research also uses the Bacterial Foraging Optimization algorithm to optimize qualification results on the Support Vector Machine which uses 4 kernels, namely Linear, RBF, Polynomial and Sigmoid. The research results show that the Linear kernel accuracy which only uses Principal Component Analysis gets a value of 79%. Then optimized with Bacterial Foraging Optimization to get an accuracy of 81%. So the Bacterial Foraging Optimization algorithm increases accuracy by 2%. For RBF and Poly kernels, the accuracy is the same, namely 78%. For the Sigmoid kernel, it got the best results in Principal Component Analysis, namely getting an accuracy value of 80%.
A Novel Hybrid Classification on Urban Opinion Using ROS-RF: A Machine Learning Approach Ependi, Usman; Ahmad, Nahdatul Akma
Jurnal Penelitian Pendidikan IPA Vol 10 No 8 (2024): August
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v10i8.8042

Abstract

Urban opinion from crowdsourced data often leads to imbalanced datasets due to the diversity of issues related to urban social, economic, and environmental topics. This study presents a novel hybrid approach that combines Random Over-Sampling and Random Forest (ROS-RF) to effectively classify such imbalanced data. Using crowdsourced urban opinion data from Jakarta, experimental results show that the ROS-RF method outperforms other approaches. The ROS-RF classifier achieved an impressive F1-score, recall, precision, and accuracy of 98%. These findings highlight the superior effectiveness of the ROS-RF method in classifying urban opinions, especially those related to social, economic, and environmental issues in urban settings. This hybrid approach provides a robust solution for managing imbalanced datasets, ensuring more accurate and reliable classification outcomes. The study underscores the potential of ROS-RF in enhancing urban data analysis and decision-making processes
Predicting Bitcoin and Ethereum Prices Using the Long Short- Term Memory (LSTM) Model Aswadi, M; Ependi, Usman
Journal of Information System and Informatics Vol 7 No 3 (2025): September
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v7i3.1228

Abstract

Cryptocurrency is a highly volatile digital asset, necessitating accurate and adaptive forecasting methods. This study implements a Long Short-Term Memory (LSTM) model to predict the daily closing prices of two leading cryptocurrencies Bitcoin (BTC) and Ethereum (ETH) using historical data from Yahoo Finance and Binance. To enhance data richness and model robustness, datasets from both sources were vertically merged. The methodological framework included data preprocessing, Min–Max normalization, formation of 24-day sliding input windows, and training across three data split ratios (70:30, 80:20, and 90:10). Model performance was evaluated using the Root Mean Squared Error (RMSE). Results indicate that the LSTM model achieved high prediction accuracy, with the lowest RMSE values of 0.0137 for BTC and 0.0152 for ETH using the combined dataset with a 90:10 split. Beyond modeling, a web-based application was developed using Streamlit, enabling users to perform real-time predictions and export results. This study contributes to the field of cryptocurrency forecasting by demonstrating that multi-source data integration significantly improves predictive accuracy and model generalization. The proposed framework offers both theoretical insights and practical tools for researchers and investors in financial technology.
Predicting Accounts Receivable of the Social Security Administration for Employment Using LSTM Algorithm Khansa, Ainna; Ependi, Usman
Journal of Information System and Informatics Vol 7 No 4 (2025): December
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63158/journalisi.v7i4.1274

Abstract

This study explores the use of Long Short-Term Memory (LSTM) networks for predicting outstanding contributions from employers to the BPJS Ketenagakerjaan, Indonesia’s social security agency. The research aims to address the challenges BPJS faces due to delayed or unpaid contributions, which impact the institution's operational stability and financial health. The LSTM model, a deep learning technique well-suited for time-series prediction, was applied to historical data from BPJS Ketenagakerjaan to predict overdue contributions across three different training-validation splits: 70:30, 80:20, and 90:10. The results demonstrate that the 80:20 split achieved the highest validation accuracy of 84.71%, offering the optimal balance between training data and model generalization. The model's ability to predict overdue contributions with high accuracy could significantly improve BPJS's receivables management, allowing for more proactive financial planning and risk mitigation. The study also highlights the integration of an attention mechanism within the LSTM model, enhancing its predictive capabilities by focusing on the most relevant historical data. This research contributes to the field of predictive analytics in public sector financial management, showcasing the potential of machine learning in enhancing the efficiency and effectiveness of social security programs.
Co-Authors Ade Putra Ahmad, Nahdatul Akma Antoni, Darius Ari Muzakir Ari Wibowo Ariandi, Muhamad Arjun, Jennifer Aswadi, M Berlianti, Marutha Edi Surya Negara Febriyanti Panjaitan Ferdiansyah Ferdiansyah Firamon Syakti, Firamon Haidar Mirza, A. Irwansyah Irwansyah Khansa, Ainna Kisworo, Marsudi Wahyu Kurniawan, Tri Basuki Mikko, Mikko Muhammad Haikal Muhammad Izman Herdiansyah Mukmin, Chairul Novaria Kunang, Yesi Novifika, Seva Nurwijayanti Nyimas Sopiah Oktaviani, Nia Oktaviani, Nia pratama, rianda Purwaningtias, Fitri Sabeli Aliya Suyanto Suyanto Tata Sutabri Tri Basuki Kurniawan Valdo, Muhammad Widya Cholil Wulandari, Intan Fitriana Yesi Novaria Kunang Zaid Amin, Zaid