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All Journal JUSIFO : Jurnal Sistem Informasi Sistemasi: Jurnal Sistem Informasi Tech-E JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Jurnal Pilar Nusa Mandiri JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jurnal Sisfokom (Sistem Informasi dan Komputer) Technomedia Journal Jurnal Sistem Cerdas JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) CCIT (Creative Communication and Innovative Technology) Journal Journal of Social Science Jurnal Teknik Informatika (JUTIF) Jurnal Abmas Negeri (JAGRI) Naratif : Jurnal Nasional Riset, Aplikasi dan Teknik Informatika Green Intelligent Systems and Applications Jurnal Algoritma Journal of Social Science IWJ : Inland Waterways Journal Information Technology International Journal (ITIJ) The Indonesian Journal of Computer Science Indonesia Berdampak: Jurnal Pengabdian Kepada Masyarakat
Nouval Trezandy Lapatta
Universitas Tadulako
Religion Humanities Automotive Engineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Immunology & microbiology Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Physics Social Sciences Transportation Other

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Implementation of ResNet-50-Based Convolutional Neural Network For Mobile Skin Cancer Classification Asriani, Asriani; Lapatta, Nouval Trezandy; Nugraha, Deny Wiria; Amriana, Amriana; Wirdayanti, Wirdayanti
Journal of Applied Informatics and Computing Vol. 9 No. 4 (2025): August 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i4.9696

Abstract

The skin is one of the most important parts of the human body, serving vital functions such as protecting internal organs from injury, shielding against direct bacterial exposure, regulating body temperature, and more. However, the skin is also susceptible to diseases, one of which is skin cancer. Skin cancer can be extremely dangerous if not treated promptly, as it can lead to death. Therefore, early detection is crucial. This study proposes a technology-based solution by classifying skin cancer using a convolutional neural network (CNN) with a ResNet50 architecture implemented into a mobile application via a REST API using Flask. The HAM10000 dataset, consisting of 10,015 skin lesion images across seven classes, was used for model training. Various testing scenarios were conducted to determine the optimal parameter combination. The best results were achieved with an accuracy of 83.84%, precision and recall of 83%, and an F1-score of 83%, using a training data configuration of 70%, dropout of 0.4, and a batch size of 64. The model implemented in this Android application can perform early detection of skin cancer quickly, practically, and easily accessible to the general public, though healthcare professionals must still supervise it. However, although this model can assist users in making early predictions, the prediction results from this model are only a tool for early detection and do not replace clinical diagnosis by professional medical personnel.2) Figure 8 shows the display for taking pictures through the gallery or camera. Users can choose the image they want to upload from the gallery or the camera to be analysed and predicted by the model.
IMPLEMENTASI PEMBOBOTAN TF-IDF PADA CHATBOT TELEGRAM UNTUK SISTEM LAYANAN INFORMASI Maulana, Muhammad Syahputra; Anshori, Yusuf; Azhar, Ryfial; Laila, Rahma; Lapatta, Nouval Trezandy
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 10, No 3 (2025)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v10i3.6314

Abstract

Chatbot populer dalam interaksi manusia-mesin dan efektif dalam layanan pelanggan, bantuan pengguna, dan pengelolaan informasi. Pengembangannya meliputi pengumpulan data pertanyaan, pem-rosesan teks, dan penerapan algoritma TF-IDF untuk mengekstrak in-formasi relevan dari dataset. Penelitian ini mengkaji penerapan algo-ritma TF-IDF pada chatbot Telegram menggunakan dataset yang terdiri dari 94 dokumen dan 300 data uji. Hasil penelitian menunjuk-kan bahwa algoritma TF-IDF menghasilkan 268 respons yang relevan dan akurat, 12 respons yang tidak relevan namun tetap diberikan, dan 32 respons yang seharusnya relevan tetapi tidak ditemukan. Penggunaan algoritma TF-IDF, yang memberikan pembobotan pada kata-kata berdasarkan pentingnya dalam dokumen, menunjukkan akurasi yang cukup baik. Hasil ini didukung oleh pengujian relevansi menggunakan metrik umum dalam bidang information retrieval, yang menghasilkan nilai precision sebesar 95,71%, recall sebesar 89,33%, dan F1-Score sebesar 92,4%. Dengan nilai-nilai tersebut, kinerja chat-bot Telegram dinilai sangat baik dalam memberikan respons.
Bahasa Inggris Abdillah Sani, Ilham; Lapatta, Nouval Trezandy; Ngemba, Hajra Rasmita; Fahlevi, Mohammad Fazrin
The Indonesian Journal of Computer Science Vol. 13 No. 4 (2024): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i4.4307

Abstract

Implementing a digital-based hazardous work licensing management system at PT Citra Palu Minerals is intended to enhance the efficiency and transparency of the work permit process. The research methodology involves a qualitative approach, Agile methodology system development, and integration with WhatsApp for notifications. The research findings indicate that this system simplifies the submission, approval, and monitoring of work permits in a structured manner, thereby reducing the risk of work accidents. Black box testing demonstrates that the system's performance meets expectations, while the questionnaire results indicate a high level of user satisfaction with an average score of 4.3 out of 5. Implementing this system can serve as a model for enhancing occupational safety and health management in similar industries.
TWITTER (X) SENTIMENT ANALYSIS OF KAMPUS MERDEKA PROGRAM USING SUPPORT VECTOR MACHINE ALGORITHM AND SELECTION FEATURE CHI-SQUARE Sari, Mutiara; Syahrullah, Syahrullah; Lapatta, Nouval Trezandy; Ardiansyah, Rizka
Jurnal Teknik Informatika (Jutif) Vol. 5 No. 5 (2024): JUTIF Volume 5, Number 5, Oktober 2024
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2024.5.5.2037

Abstract

Ministry of Education, Culture, Research and Technology (Kemendikbudristek) has implemented numerous policies aimed at enhancing the quality of education in the country. One of these policies is Kampus Merdeka program. The program includes various initiatives such as Teaching Campus, the Merdeka Student Exchange program, and Internship and Independent Study programs, which have gained significant popularity among students across Indonesia. However, the Kampus Merdeka program has drawn many pros and cons, with some parties supporting the initiative, but also many criticisms related to its implementation, which is considered not optimal in some educational institutions. Social media is where many of these opinions are voiced, one of the most widely used of which is twitter. In light of these circumstances, this study conducted a sentiment analysis of the independent campus program to assess public sentiment towards it. The dataset used in this research consisted of 500 tweets containing the keyword "kampus merdeka" with 250 tweets reflecting positive sentiment and 250 tweets reflecting negative sentiment. The results of the tests carried out obtained the highest increase in results in the 10:90 ratio, namely with an accuracy that increased by 14% from the previous 66% to 80%, precision also increased by 22% from the previous 67% to 89%, recall increased by 16% from the previous 58% to 79%, and the f1-score value which was previously 62% turned into 79% because it also increased by 17%.
Predicting Potential Car Buyers using Logistic Regression Algorithm Lapatta, Nouval Trezandy; Husin, Abdullah
Sistemasi: Jurnal Sistem Informasi Vol 13, No 3 (2024): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v13i3.4068

Abstract

This research aims to develop a predictive model to identify individuals with a high potential to become car buyers, employing logistic regression algorithm. The primary objective is to support the automotive industry in devising more efficient and focused marketing strategies. The choice of logistic regression is based on its superiority in handling categorical dependent variables and its practicality in result interpretation. The data processed in this study derive from demographic information, consumption habits, brand preferences, and various other factors that influence car buying decisions. The main data source is the outcome of online surveys participated in by individuals predicted to have the potential to buy a car within the next 12 months. The analysis results indicate that factors such as income, age, previous vehicle ownership status, gender and marriage status play significant roles in predicting the likelihood of someone becoming a car buyer. The developed model achieved an accuracy and precision of 95%, proving its significant capability in identifying potential car buyers with a high success rate. These findings provide valuable insights for the automotive industry in formulating more targeted and efficient marketing strategies, as well as contributing to the academic literature on the application of logistic regression in consumer behavior prediction.
Usability and User Experience Evaluation on Extracurricular Website (SINEMA) Implementation using SUS and UEQ Methods Wirdayanti; AKBAR, MUHAMMAD; Sabarudin Saputra; Deni Luvi Jayanto; Sri Khaerawati Nur; Nouval Trezandy; Bakri
Information Technology International Journal Vol. 3 No. 2 (2025): Information Technology International Journal
Publisher : Magister Teknologi Informasi UPN "Veteran" Jawa Timur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33005/itij.v3i2.57

Abstract

The rapid integration of web-based platforms in higher education highlights the importance of usability and user experience in supporting students’ extracurricular activities. This study evaluates the usability and user experience of the Student Extracurricular Information System (SINEMA) developed at Tadulako University. A total of 99 respondents participated, selected from a population of 5,581 active users through Slovin’s formula. Two standardized instruments were applied: the System Usability Scale (SUS) to capture global usability perceptions and the User Experience Questionnaire (UEQ) to assess six dimensions of user experience. The SUS results indicate a mean score of 76.06, which falls within Grade B and the “Good” category, exceeding the global benchmark. This suggests that the system is generally usable, although certain respondents reported minor challenges requiring further improvement. The UEQ results show that Perspicuity (1.94), Dependability (1.94), and Stimulation (1.93) achieved the “Excellent” category, reflecting clarity, reliability, and engagement. Meanwhile, Attractiveness (1.65), Efficiency (1.58), and Novelty (1.72) were rated “Good,” highlighting positive perceptions but also opportunities for optimization. Overall, the findings demonstrate that SINEMA effectively supports extracurricular management with satisfactory usability and strong user experience. The study contributes novelty by integrating SUS and UEQ for comprehensive evaluation within a higher education extracurricular context. Recommendations include enhancing efficiency and novelty to elevate user satisfaction and system adoption.
Performance Comparison of Multilayer Perceptron (MLP) and Random Forest for Early Detection of Cardiovascular Disease Setiawan, Dita Widayanti; Lapatta, Nouval Trezandy; Amriana, Amriana; Nugraha, Deny Wiria; Lamasitudju, Chairunnisa Ar.
Journal of Applied Informatics and Computing Vol. 9 No. 6 (2025): December 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i6.10826

Abstract

Cardiovascular disease is a disorder of the heart and blood vessels that can lead to heart attacks, strokes, and heart failure, so early detection is essential. This study compares Multilayer Perceptron (MLP) and Random Forest for risk classification in a Kaggle dataset containing 70,000 samples with balanced targets. Pre-processing included age conversion, outlier cleaning, standardization, and feature selection based on feature importance. Both models were optimized using RandomizedSearchCV and evaluated using accuracy, precision, recall, F1-score, AUC-ROC, confusion matrix, and k-fold cross-validation. The results show that the accuracy of MLP is 73.90% and Random Forest is 74.23% with an AUC of 0.80 for both. Random Forest is more stable across all folds and performs better on the negative class, while MLP is slightly more sensitive to the positive class. Independent t-test and Mann-Whitney U tests show p>0.05, indicating that the difference in performance is not significant. The most influential features were diastolic blood pressure, age, cholesterol, and systolic blood pressure. The non-clinical Streamlit prototype demonstrated the model's potential for education and initial decision support.
Implementation of Collaborative Filtering in the Salted Fish Recommendation Process Rizky, Moh Taufiq; Rinianty, Rinianty; Nugraha, Deny Wiria; Amriana, Amriana; Lapatta, Nouval Trezandy
Journal of Applied Informatics and Computing Vol. 9 No. 6 (2025): December 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i6.11576

Abstract

The development of e-commerce in the current era has been so rapid that buying and selling transactions are carried out online through various media, including websites and applications. With so many products available in the application, users often feel confused when choosing the product they want to buy, so it takes a long time to choose a product to avoid regret after purchasing it. In this study, a web-based recommendation system was created for the process of recommending salted fish with the aim of making it easier for customers to choose the type of salted fish. The Collaborative Filtering method was used, employing Pearson Correlation as a tool to calculate the similarity value between users, then using Weighted Sum to calculate the prediction value. Collaborative Filtering often experiences the cold start problem, where the system has difficulty providing recommendations to users who do not yet have a transaction history. Therefore, the author proposes a popularity-based strategy as a measure to overcome this problem. Based on testing, the author obtained results of MAE = 0.63 and RMSE = 0.81 based on train-test split results with a data distribution of 80:20, 80% of the dataset for training and 20% of the dataset for testing with an accuracy of 70-80%, indicating that this system works well. This system has been tested using the Blackbox method.
Design and Implementation of a Customer Relationship Management System for Medium-Sized Digital Printing Enterprises Noel Marcell Jonathan Wongkar; Wirdayanti Wirdayanti; Syahrullah Syahrullah; Rinianty Rinianty; Nouval Trezandy Lapatta
JUSIFO : Jurnal Sistem Informasi Vol 10 No 2 (2024): JUSIFO (Jurnal Sistem Informasi) | December 2024
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.v10i2.25023

Abstract

This study investigates the design and implementation of a Customer Relationship Management (CRM) system specifically developed to address the operational challenges faced by medium-sized enterprises in the digital printing sector, with Rio Digital Printing as a case study. The research identifies key issues such as communication gaps and the lack of real-time order tracking, which negatively impact customer satisfaction. Employing a prototyping methodology, the system was iteratively refined with active user participation, ensuring alignment with stakeholder requirements. Key features include real-time order tracking, automated notifications, and a comprehensive interactive dashboard to support data-driven decision-making. The results demonstrate that the CRM system significantly enhances operational transparency, improves customer engagement, and fosters loyalty. This study contributes to the academic discourse by addressing the underexplored application of CRM systems in small and medium-sized enterprises, presenting a scalable framework for adaptation in similar industries. The findings also provide practical implications, advocating for digital transformation as a strategy to improve competitiveness in dynamic market environments.
Visualization of Village Fund Budget Realization to Improve Transparency of Information to the Community Syahrullah, Syahrullah; Lapatta, Nouval Trezandy; Rinianty, Rinianty; Hernita, Ayu; Supardi, Nurhikmah
Jurnal Abmas Negeri (JAGRI) Vol. 6 No. 2 (2025): Volume 6 Nomor 2 Desember 2025
Publisher : Sarana Ilmu Indonesia (salnesia)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36590/jagri.v6i2.1763

Abstract

Generally, village fund information is delivered in manual format or through printed materials. This type of information delivery is difficult for certain groups to understand, resulting in low community participation in village development planning and evaluation. A new approach is needed, involving the application of information technology through the visualization of village fund planning and budget realization data. This community service program aimed to increase the transparency of village fund management through training in data visualization of planning and budget realization, thereby providing village officials, neighborhood associations, family welfare programs, youth organizations, and young people with an understanding of the importance of information disclosure and the skills to process budget data digitally. The activities are carried out through a combination of theory, practice, group discussions, and monitoring and evaluation. Participants were trained to use Microsoft Excel to present data in the form of infographics, tables, and diagrams that are easy to understand. In this way, the community can obtain a clearer picture of village fund management. The community service activity was designed to last for 6 months (June to November 2025) and the training was conducted over 2 days with a duration of 10 hours, divided into 5 hours per day. The results of the activity showed an average increase in participants’ knowledge and skills of 34 points. This activity can improve participants’ skills and knowledge in visualizing village fund planning and realization data.
Co-Authors ., Rezki Abdillah Sani, Ilham Abdul Mahatir Najar Abdullah Abdullah Adhira Putri, Dhivanny Agung Stiven Cahyati Angely Ain, Moch. Zukhruf Amriana Amriana Amriana Amriana Andhyka, Andhyka Andi Hendra Andi Hendra Angraeni, Dwi Shinta Anita Ahmad Kasim Anita, Ayu Arsita, Tiara Juli Asriani Asriani, Asriani Ayu Hernita Bakri Chandra, Ferri Rama Darojah, Murtafiatun Delia, Fenita Deni Luvi Jayanto Deny Wiria Nugraha Dessy Santi Djohari, Riyandi Dwitama Dwi Shinta Angreni Dwimanhendra, Muhammad Rifaldi Fahlevi, Mohammad Fazrin Fajar, Moh Fajriyah, Nurul Faldiansyah, Faldiansyah Firzatullah, Raden Muhamad Hajra Rasmita Ngemba Hamid, Odai Amer Hanama, Ikhsan Wahyudin Ihalauw, Sahron Angelina Ihwan, Abib Raifmuaffah Ilman, Meilani Karnita Sumbaluwu, Harlin Feby Kartika, Rina Krama, Tri Laila, Rahma Lamadjido, Moh. Raihan Dirga Putra Lamasitudju, Chairunnisa Mandra Maulana, Muhammad Syahputra Mohamad Irfan, Mohamad Mohammad Yazdi Pusadan Muhammad Akbar Muhammad Akbar Mutiara Sari Ngemba, Hajra Ningsih, Alief Surya Noel Marcell Jonathan Wongkar Noviantika, Noviantika Nurhikmah Supardi Nursiana Zasqia, Andi Nirina Pagiu, Harry T. Paloloang, Muhammad Fadhil Akmal B. Priska, Salsa Dilah Putra, Adhitya Pramana Qofifa, Sitti Nurlaili Rahmah Laila Rasmita Ngemba, Hajra Rasmita, Hajra Rasyid, Muh. Ashari Rinianty Rinianty Rinianty, Rinianty Rizka Ardiansyah Rizky, Moh Taufiq Ryfial Azhar Saada, Rahmadian A. Sabarudin Saputra Saputra, Sabaruddin Septiano Anggun Pratama Setiawan, Dita Widayanti Siswahyudianto Siti Rahmawati skandar, Iskandar Sri Khaerawati Nur Sukirman Sukirman Syahrullah Syahrullah Syahrullah Syaiful Hendra Wirdayanti Wirdayanti Wirdayanti Wongkar, Noel Marcell Jonathan Yanti, Wirda Yuri Yudhaswana Joefrie Yusuf Anshori Zulkifli Zulkifli