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All Journal JURNAL SISTEM INFORMASI BISNIS Jurnal Hubungan Internasional Jurnal Informatika dan Teknik Elektro Terapan JUSIFO : Jurnal Sistem Informasi INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi JURNAL ILMIAH INFORMATIKA JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI INTECOMS: Journal of Information Technology and Computer Science JURNAL TEKNOLOGI DAN OPEN SOURCE Simtek : Jurnal Sistem Informasi dan Teknik Komputer Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Jurnal Teknologi Informasi dan Multimedia Journal of Information Systems and Informatics bit-Tech JATI (Jurnal Mahasiswa Teknik Informatika) Nusantara Science and Technology Proceedings Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Sawala : Jurnal pengabdian Masyarakat Pembangunan Sosial, Desa dan Masyarakat Jurnal Pendidikan dan Teknologi Indonesia International Journal of Engineering, Science and Information Technology Djtechno: Jurnal Teknologi Informasi Jurnal Mahasiswa Sistem Informasi (JMSI) KLIK: Kajian Ilmiah Informatika dan Komputer International Journal of Data Science, Engineering, and Analytics (IJDASEA) JITSI : Jurnal Ilmiah Teknologi Sistem Informasi COMSERVA: Jurnal Penelitian dan Pengabdian Masyarakat Abdimas Altruis: Jurnal Pengabdian Kepada Masyarakat Jurnal Informatika Teknologi dan Sains (Jinteks) Jurnal Ilmiah Sistem Informasi dan Ilmu Komputer JUSIFOR : Jurnal Sistem Informasi dan Informatika Journal of Artificial Intelligence and Digital Business Seminar Nasional Ilmu Terapan MDP Student Conference ILTEK : Jurnal Teknologi Scientica: Jurnal Ilmiah Sains dan Teknologi Information Technology International Journal (ITIJ) Jupiter: Publikasi Ilmu Keteknikan Industri, Teknik Elektro dan Informatika Router : Jurnal Teknik Informatika dan Terapan Repeater: Publikasi Teknik Informatika dan Jaringan Neptunus: Jurnal Ilmu Komputer dan Teknologi Informasi Prosiding Seminar Nasional Indonesia Router : Jurnal Teknik Informatika dan Terapan
Abdul Rezha Efrat Najaf
Department Of Information System Department, Faculty Of Computer Science, Universitas Pembangunan Nasional “Veteran” Jawa Timur, Surabaya 60294, Indonesia
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BCA Stock Price Prediction Using Time Series Method With GRU (Gated Recurrent Unit) Nugraha, Rizky; Abdul Rezha Efrat Najaf; Reisa Permatasari
JURNAL TEKNOLOGI DAN OPEN SOURCE Vol. 8 No. 2 (2025): Jurnal Teknologi dan Open Source, December 2025
Publisher : Universitas Islam Kuantan Singingi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36378/jtos.v8i2.4500

Abstract

Stock price prediction is a crucial component in investment decision-making, enabling investors to plan strategies more accurately and minimize risks. This study applies the Gated Recurrent Unit (GRU) model to predict the stock prices of blue-chip banking companies in Indonesia using data from the period 2019 to 2024. The model utilizes historical stock data to forecast future trends. The results from the first testing scheme, with a data split ratio of 70% / 30%, using GRU units (128,256) with the Adam optimizer, show that the GRU model is the most optimal in terms of prediction, measured by metrics such as MSE, RMSE, and MAPE. This study also proposes a web-based dashboard that visualizes the predicted stock prices and provides decision-support tools for investors. The findings highlight the effectiveness of deep learning in financial forecasting and underscore its potential to enhance investment strategies.
House Price Prediction in Surabaya Using Backpropagation Neural Network Pamungkas, Dimas Fajri; Najaf, Abdul Rezha Efrat; Permatasari, Reisa
JURNAL TEKNOLOGI DAN OPEN SOURCE Vol. 8 No. 2 (2025): Jurnal Teknologi dan Open Source, December 2025
Publisher : Universitas Islam Kuantan Singingi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36378/jtos.v8i2.4829

Abstract

This research develops a house price prediction system in Surabaya using the Backpropagation Neural Network (BPNN) method. The dataset was obtained through web scraping of property listings, resulting in 3,435 records with 52 attributes. To improve stability, the target variable (house price) was transformed using natural logarithms. Several neural network architectures were tested, and the best configuration [32, 64, 32] achieved Mean Absolute Error (MAE) of 0.3125, Root Mean Squared Error (RMSE) of 0.4201, R² of 0.7138, and Mean Absolute Percentage Error (MAPE) of 1.46%. A multi-run evaluation of 20 iterations confirmed consistency of results. The model was implemented as a web-based application using Flask, allowing users to predict house prices in real-time. This research shows that BPNN is reliable for property price forecasting and can support decision-making in the housing market.
Decision Support System for Extending PT Nitro Pratama Indonesia Outlet Cooperation Using the Fuzzy AHP-TOPSIS Radhyana Gayatri Faradilla; Rizka Hadiwiyanti; Abdul Rezha Efrat Najaf
JURNAL TEKNOLOGI DAN OPEN SOURCE Vol. 8 No. 2 (2025): Jurnal Teknologi dan Open Source, December 2025
Publisher : Universitas Islam Kuantan Singingi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36378/jtos.v8i2.4847

Abstract

The increasingly competitive business environment required companies to make objective decisions, particularly in determining the feasibility of outlet contract extensions. PT Nitro Pratama Indonesia previously conducted this process manually, which often led to inconsistent decisions. This study aimed to develop a web-based decision support system to evaluate outlet cooperation systematically. A combination of Fuzzy Analytical Hierarchy Process (Fuzzy AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) was applied. Fuzzy AHP was used to determine the weight of criteria under uncertain conditions, while TOPSIS was used to rank alternatives based on their proximity to the ideal solution. The study involved 50 active outlets located in Surabaya and Solo branches. The final criteria weights obtained were Outlet Revenue (0.33), Rental Cost (0.26), Outlet Location (0.16), Accessibility (0.11), Competitiveness (0.08), and Operational Cost (0.06). The ranking process generated objective recommendations that were consistent with manual calculations. Functional testing using Black Box Testing indicated that all system features operated properly. The system proved effective and relevant in supporting accurate and efficient decision-making for outlet contract extensions.
Forecasting and Raw Material Planning in Traditional Songkok Production Using ARIMA and Simple Exponential Smoothing Sayyidah Nafisah; Abdul Rezha Efrat Najaf; Prasasti Karunia Farista Ananto
JUSIFO : Jurnal Sistem Informasi Vol 11 No 1 (2025): JUSIFO (Jurnal Sistem Informasi) | June 2025
Publisher : Program Studi Sistem Informasi, Fakultas Sains dan Teknologi, Universitas Islam Negeri Raden Fatah Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19109/jusifo.v11i1.27833

Abstract

This study investigates the applicability of time series forecasting models—Autoregressive Integrated Moving Average (ARIMA) and Simple Exponential Smoothing (SES)—for optimizing raw material planning in traditional songkok production. Utilizing monthly production data from a small-scale manufacturer in East Java, Indonesia (July 2020–August 2024), the ARIMA(1,1,1) model demonstrated superior forecasting performance, particularly under weak and irregular seasonality. Compared to SES, ARIMA yielded lower MAE, MSE, and MAPE values, enabling more precise production planning. The forecasts were translated into raw material requirements, resulting in improved inventory precision and operational efficiency, with monthly material usage gains ranging from 2.05% to 2.18%. These improvements are especially critical for micro-enterprises constrained by limited resources and seasonally driven demand cycles. While the univariate approach is a limitation, the findings provide a foundation for integrating contextual data in future multivariate models. The study offers practical insights for digital transformation in artisanal sectors and contributes to the broader discourse on data-driven production planning in culturally embedded industries.
PERANCANGAN APLIKASI JASA RIAS WAJAH BERBASIS DESIGN THINKING UNTUK PENGALAMAN PENGGUNA Rizvina Hadi Imani; Abdul Rezha Efrat Najaf; Prasasti Karunia Farista Ananto
Seminar Nasional Ilmu Terapan Vol 9 No 1 (2025): Vol 9 No 1 (2025): Seminar Nasional Ilmu Terapan (SNITER) 2025
Publisher : Universitas Widya Kartika Surabaya

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Abstract

Penelitian ini bertujuan untuk merancang aplikasi jasa rias wajah yang mempermudah pelanggan dalam mencari, memesan, dan melakukan transaksi layanan secara efisien. Latar belakang penelitian didasarkan pada permasalahan yang sering dialami pelanggan, yaitu keterbatasan informasi harga, jadwal, dan portofolio pemilik jasa rias yang tidak transparan, serta proseskomunikasi yang lambat. Metode yang digunakan adalah Design Thinking dengan lima tahapan: Empathize, Define, Ideate, Prototype, dan Test. Melalui pendekatan ini, peneliti berfokus pada pemahaman kebutuhan pengguna untuk menghasilkan desain antarmuka (UI) dan pengalaman pengguna (UX) yang intuitif, menarik, dan sesuai dengan ekspektasi pelanggan. Prosesperancangan dilakukan menggunakan aplikasi Figma untuk menghasilkan wireframe dan prototype beresolusi tinggi, kemudian diuji menggunakan metode System Usability Scale (SUS) terhadap lima responden. Hasil pengujian menunjukkan nilai rata-rata SUS sebesar 73, yang termasuk kategori “Good”, menandakan bahwa desain aplikasi mudah digunakan danmemberikan pengalaman pengguna yang memuaskan. Dengan demikian, rancangan aplikasi ini berpotensi menjadi solusi efektif dalam meningkatkan efisiensi dan transparansi layanan jasa rias di era digital.
PERANCANGAN WEBSITE PENDUKUNG KEPUTUSAN PENGURUS TERBAIK UKKI UPN JATIM MENGGUNAKAN MODEL WATERFALL Nesvia Nissa Artanti; Abdul Rezha Efrat Najaf; Tri Luhur Indayanti Sugata
Prosiding Seminar Nasional Indonesia Vol. 3 No. 3 (2026): Prosiding Seminar Nasional Indonesia
Publisher : CV. Adiba Aisha Amira

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Abstract

UKKI UPN Veteran Jawa Timur requires an objective and transparent mechanism to determine the best management board members in each organizational period. The evaluation process previously relied on manual calculations using spreadsheets, which was considered ineffective, difficult to interpret, and prone to human error and subjectivity. This study aims to design and develop a web-based Decision Support System (DSS) to assist in selecting the best management board members in a systematic and accurate manner. The research adopts a qualitative approach to identify system requirements through interviews with the general chairman, general secretary, and several relevant stakeholders. System development is conducted using the Waterfall model, which consists of requirements analysis, system design, implementation, testing, deployment, and maintenance stages. The Decision Support System applies the Analytical Hierarchy Process (AHP) to determine criteria weights and the Weighted Product (WP) method to rank the alternatives. The results show that the developed website is capable of managing member data, evaluation criteria, assessment scores, and organizational periods, as well as presenting ranking results in real time. The system enhances efficiency, accuracy, and transparency in determining the best management board members at UKKI UPN Veteran Jawa Timur.
Convolutional Neural Network Approach for Aspect-Based Sentiment Analysis of Tourism Reviews Siti Oktavia Eka Putri; Amalia Anjani Arifiyanti; Abdul Rezha Efrat Najaf
bit-Tech Vol. 8 No. 1 (2025): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i1.2582

Abstract

The tourism industry is a key economic sector in Indonesia, with East Java ranking highest in tourist visits. This study aims to enhance tourism development by applying aspect-based sentiment analysis (ABSA) using convolutional neural networks (CNN) to analyze online reviews. CNN was selected for this study due to its proven efficiency in capturing local n-gram features and its relatively lower computational cost compared to other deep learning model. Reviews from TripAdvisor and Google Maps were collected focusing on four aspects: attraction, amenities, access, and price. Five different models were developed in this research: one multilabel aspect classifier designed to identify multiple aspects mentioned within each review, and four sentiment classifiers focused on evaluating the sentiment polarity for each specific aspect. These models were trained and evaluated using various combinations of word embeddings, including static embeddings like Word2Vec, and contextualized embeddings such as BERT and IndoBERT. Additionally, the impact of preprocessing through stemming was investigated to understand how simplifying word forms affects model performance. Results indicate that IndoBERT-CNN attains the best overall sentiment classification, reaching F1-scores up to 0.71 for attraction and 0.93 for amenities, while Word2Vec-CNN with stemming leads multilabel classification. Meanwhile stemming improves performance for static embeddings like Word2Vec by simplifying word forms, it reduces effectiveness in transformer-based models like BERT and IndoBERT that rely on natural language context. These findings highlight the benefit of choosing appropriate embeddings and preprocessing for different tasks, thus providing practical insights for improving tourism services through better tourist reviews analysis.
Comparison of Adam, RMSprop, and SGD on DenseNet121 for Tomato Leaf Disease Classification Heni Lusiana Dewi; Amalia Anjani Arifiyanti; Abdul Rezha Efrat Najaf
bit-Tech Vol. 8 No. 1 (2025): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i1.2684

Abstract

Diseases affecting tomato leaves can severely impact agricultural productivity, as they can reduce crop yields and quality significantly. A swift and dependable identification of these diseases is vital for ensuring prompt interventions and the successful implementation of disease control strategies. This study focus on evaluating and comparing the efficiency of three separate optimizers, such as Adam, RMSProp, and SGD on the pretrained Convolutional Neural Network (CNN) architecture DenseNet121. There has been no previous research that directly compares the performance of Adam, RMSProp, and SGD optimizers on the DenseNet121 model for classifying tomato leaf diseases using the Plant Village dataset. These optimizers are crucial in the training process by influencing the model’s ability to converge and generalize well on new, unseen data. Experimental procedures were performed using a labeled dataset of tomato leaf images, which included healthy leaves and various disease classes. Out of the three optimization techniques tested, the DenseNet121 model trained with the Adam optimizer consistently outperformed the others. It achieved the highest evaluation metrics, with an accuracy of 0.9800, precision of 0.9807, recall of 0.9800, and F1-score of 0.9800 on the test set. These outcomes suggest that the model has a strong and balanced classification performance, capable of correctly identifying disease conditions with minimal errors. Based on these findings, the DenseNet121 architecture combined with the Adam optimizer is considered the optimal model used to recognize various tomato leaf diseases in this study.
UI/UX Development of a Boarding House Reservation Application: A Design Thinking Approach in Surabaya Azizatul Fara Dibah; Abdul Rezha Efrat Najaf; Prasasti Karunia Farista Ananto
bit-Tech Vol. 8 No. 2 (2025): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i2.3320

Abstract

Fragmented, inconsistent, and frequently outdated information about boarding-house availability, facilities, and pricing remains a persistent usability problem in existing digital platforms. Current UI/UX and reservation-system research has not sufficiently addressed these issues within the specific context of urban rental ecosystems, creating gap in designing solutions that respond to the needs of both tenants and property owners. This study addresses that gap by developing and evaluating a user-centered interface for a boarding-house reservation application using the five-stage Design Thinking framework: empathize, define, ideate, prototype, and test. Insights were gathered from 30 participants representing owners, tenants, and administrators in Surabaya, forming the basis for personas, information architecture, user flows, and low- to high-fidelity prototypes designed in Figma. Usability and interface quality were examined through task-based testing, the System Usability Scale (SUS), and Nielsen’s heuristic evaluation to integrate both user perception and normative usability standards. Initial testing produced SUS scores of 74.5 (owners), 76.5 (tenants), and 66 (administrators), indicating acceptable but improvable usability and several interface issues. Iterative refinement led to marked enhancements, with second-round SUS scores of 90, 87, and 89, accompanied by high learnability (96–97%), strong memorability (95–96%), and low error rates (0.0306–0.0800). A minor efficiency decrease was attributed to unstable network conditions rather than design flaws. Overall, the findings demonstrate that structured, iterative UI/UX development supported by heuristic auditing effectively resolves core information and interaction challenges in boarding-house reservation systems. The final prototype demonstrates high usability and provides a replicable design rationale for future implementation and scaling.
Design and Development of a Web-Based Boarding House Management Information System Using RAD Method Mohamad Ilham Praditya Arifatul Nesta; Abdul Rezha Efrat Najaf; Seftin Fitri Ana Wati
bit-Tech Vol. 8 No. 2 (2025): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i2.3342

Abstract

The rapid growth of urban migration in Indonesia, particularly among students and workers, has increased the demand for efficient and integrated boarding house management systems. However, many boarding house businesses still rely on manual processes for tenant registration, payment tracking, and data recording, leading to inefficiencies and data inaccuracies. This study aims to design and develop a web-based boarding house management information system to optimize operational performance and enhance service quality for both owners and tenants. The system was developed using the Rapid Application Development (RAD) method, which emphasizes iterative prototyping, user involvement, and rapid feedback to ensure functional alignment with user requirements. The application was built with ReactJS for the frontend, ExpressJS for the backend, and PostgreSQL as the database, integrated with the Midtrans payment gateway to enable secure, real-time transactions. A key contribution of this study is the combination of RAD methodology with Midtrans integration, providing a scalable and user-friendly solution for small-scale property management. The system’s functionality was tested using Black Box Testing, confirming that all features operated correctly according to design specifications. The results demonstrate that the system successfully streamlines management workflows, reduces human error by 25%, and improves the user experience by reducing administrative processing time by 30%. This study contributes to the digital transformation of small-scale property management by demonstrating the feasibility of using low-cost, scalable technologies to enhance operational efficiency and service transparency.
Co-Authors Agung Brastama Putra Agussalim Agussalim Agussalim, Agussalim Agussalim, Agussalim Aisha Ramadhana Indira Santoso AlHafizh, Hadyan Alla, Muhammad Anbiya Fath Amalia Anjani Arifiyanti Amalia Anjani Arifiyanti Ana Wati, Seftin Fitri Anastasia Lidya Maukar Andreas Nugroho Sihananto Anggreani, Nilam Kumallah Anik Vega Vitianingsih Anindo Saka Fitri Apriyanti, Narti Arief Yahya Prasetio Arinta Ardiyono, Taufiq Arochma, Novita Maulana Aryo Sulistiono, Wisnu Asif Faroqi Aulia Putri Fajar Aulia Rahma, Faradhiya Aulia, Ervina Rosa Aviolla Terza Damaliana Azizatul Fara Dibah Badriyyah, Shofiyyatul Bilqis, Thufailah Nafiisah Bonda Sisephaputra Cahyo Wibowo, Nur Candra, Devilia Dwi Chilmi, Farid Daniar, Ivan Faiz Dewangga Nanda Arjuna Dhian Satria Yudha Kartika Egga Naufal Daffa Tanadi Fais Irwanda Fajar Kurnia Ferdiansyah, Rizky Fitri Ana Wati, Seftin Fitri, Anindo Saka Hadi, Tasya Diva Fortuna Hamdan, Arva Rizqullah Haq, Ahmad Nashirul Heni Lusiana Dewi Iqbal Ramadhani Mukhlis Ivan Faiz Daniar Jannah Arum Kemangi, Anisya Khanza Afiatul Jeremy David Alexander Jojok Dwiridotjahjono Kadek Dwi Natasya Pradnyani Kartika, Dhian Satria Yudha Khoirul Tarmidzi M Aldan Adiar Firdaus Manti, Rival Septian Jeflin Maulana, M. Kandias Happy Mawardi, Alfiandi Imam Mohamad Ilham Praditya Arifatul Nesta Mohamad Irwan Afandi Muhammad Muharrom Al Haromainy Mustika, Yesi Rahma Nabila Octavianti Nabila, Achmad Wildan Nesvia Nissa Artanti Nisrina, Nasywa Nugraha, Rizky Nurdin, Andi Nuryananda, Praja Firdaus Pamungkas, Dimas Fajri Permatasari, Reisa Prasasti Karunia Farista Ananto Prasasti Karunia Farista Ananto Purnaningsih, Elwis Ghaitza Putra, Rio Alghaniy Raden Mohamad Herdian Bhakti Radhyana Gayatri Faradilla Rafli Fahreza Ransi, Paloma Rizka Hadiwiyanti Rizka Hadiwiyanti Rizvina Hadi Imani Robawa, Rizki Setyo Putro Rudiany, Novita Putri Saka Fitri, Anindo Sakti, Ciptagusti Sila Salsabilla, Kharisma Agustya Zahra Sayyidah Nafisah Seftin Fitri Ana Wati Setiawan, Moch Rezeki Shafira, Putri Dian Shofiyyatul Badriyyah Sila Sakti, Ciptagusti Siti Oktavia Eka Putri Sriyanti, Zilvi Azus Sulastri, Eka Nanda Suryo Widodo Tita Ayu Rospricilia Tri Luhur Indayanti Sugata Wahyuni, Eka Dyar Wardani, Lina Wati, Seftin Fitri Ana Wibowo, Nur Cahyo Wulansari, Anita Yudha, Dhian Satria Zein, Isynariyah