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Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi)
Published by Ikatan Ahli Informatika Indonesia
ISSN : -     EISSN : 25973584     DOI : -
Core Subject : Science,
Computer Science & IT
Seminar Nasional Sistem Informasi dan Teknologi (SISFOTEK) merupakan ajang pertemuan ilmiah, sarana diskusi dan publikasi hasil penelitian maupun penerapan teknologi terkini dari para praktisi, peneliti, akademisi dan umum di bidang sistem informasi dan teknologi dalam artian luas.
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 471 Documents
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Aplikasi Pengenalan Budaya Cirebon untuk Meningkatkan Pemahaman dan Apresiasi terhadap Kearifan Lokal Sabda Insan Pamungkas; Haris Burhanudin; Hilpad Hidayat; Naufal Ibrahim
Prosiding SISFOTEK Vol 9 No 1 (2025): SISFOTEK IX 2025
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

This study presents the design and implementation of a mobile-based educational and cultural forum application introducing Cirebon's local culture, developed using the React Native framework and the Design Thinking approach. The application aims to enhance public understanding and appreciation of local wisdom through interactive and accessible digital media. The development process involved stages of empathizing with users, defining needs, ideating, prototyping, and testing. Based on usability testing using the All-Positive System Usability Scale (SUS), the “Cirebon Culture Introduction” application achieved excellent user satisfaction, with most respondents giving a score of 4 (agree) across all indicators and an average satisfaction level above 80%. These results indicate high usability, an engaging interface, and strong cultural relevance. Overall, the iterative Design Thinking process proved effective in producing a user-centered and culturally meaningful application that supports the preservation and promotion of regional culture.
Perbandingan Kinerja Algoritma Machine Learning dalam Analisis Sentimen Aplikasi Grok AI Mohammad Farhan Surury; Salsabillah Azahra; Nisha Pancarana; Dwi Maulana Siddiq
Prosiding SISFOTEK Vol 9 No 1 (2025): SISFOTEK IX 2025
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

The rapid development of artificial intelligence (AI) applications has increased the demand for sentiment analysis of user reviews, particularly on the Google Play Store. This study aims to compare the performance of four classical machine learning algorithms—Logistic Regression, Support Vector Machine (SVM), Naïve Bayes, and K-Nearest Neighbors (KNN)—in classifying user sentiments toward the Grok AI application. A total of 2,426 reviews were collected through Google Play Store scraping and processed using several preprocessing steps, including case folding, cleaning, tokenization, stopword removal, normalization, and stemming. Sentiment labels were assigned based on user ratings, while feature representation was conducted using Term Frequency–Inverse Document Frequency (TF-IDF). To address class imbalance, the Synthetic Minority Over-sampling Technique (SMOTE) was applied. Model evaluation employed accuracy, precision, recall, F1-score, and confusion matrix. The experimental results show that SVM achieved the best performance with 88% accuracy, 0.87 precision, 0.86 recall, and 0.86 F1-score. Logistic Regression ranked second with 86% accuracy, followed by Naïve Bayes (81%) and KNN (78%). These findings indicate that SVM is the most effective algorithm for sentiment analysis of AI-based application reviews, while Logistic Regression provides a stable and interpretable alternative. This research contributes by providing a benchmark for the performance of classical machine learning algorithms in the context of Grok AI reviews and offers methodological insights for developers to enhance the quality of AI-based applications.
Analisis Perbandingan K-Means dan K-Medoids dalam Klasterisasi Provinsi di Indonesia Berdasarkan Indikator Ketahanan Pangan Ananda Rafly; Refy Fariskasari; Muhammad Yopi Triana; Shohibul Ilham
Prosiding SISFOTEK Vol 9 No 1 (2025): SISFOTEK IX 2025
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

Food security is a strategic and increasingly complex issue in Indonesia, where agricultural productivity, urbanization, climate change, and regional disparities pose major challenges. Data-driven analysis provides significant opportunities to support the formulation of evidence-based food policies, one of which is through clustering methods. This study aims to compare the performance of the K-Means and K-Medoids algorithms in classifying 34 Indonesian provinces based on food security indicators, namely plant energy availability, animal energy availability, total energy availability, and the ratio of animal energy. The dataset was obtained from the Central Statistics Agency (BPS) for 2023. The research process involved data preprocessing, normalization, application of both algorithms, and evaluation using the Silhouette Coefficient, Davies–Bouldin Index (DBI), and the Elbow Method to determine the optimal number of clusters. The results indicate that K-Means with k=5 provides the best balance between internal validity and policy usefulness, while K-Medoids demonstrates better robustness against outliers and higher interpretability through the use of medoids as cluster centers. The comparative results show that K-Means performs better for clearly separated clusters, whereas K-Medoids yields more stable results for data with high variability. These findings highlight the importance of selecting clustering algorithms according to data characteristics and analytical objectives. This study contributes to the development of data-based approaches for food policy formulation and provides a scientific foundation for designing more targeted and effective food security intervention strategies across Indonesian provinces.
Pemodelan Topik Pada Ulasan Kegiatan Dakwah Menggunakan Algoritma Latent Dirichlet Allocation Elfizar; Sherly Fillia; Rahmad Kurniawan; Sukamto; Tisha Melia; Fitra Lestari
Prosiding SISFOTEK Vol 9 No 1 (2025): SISFOTEK IX 2025
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

The Indonesian Ulema Council (MUI) of Riau Province plays an important role in dakwah (Islamic preaching) development, yet its evaluation methods remain limited. Understanding congregant feedback is crucial, but manually analyzing thousands of comments is ineffective. This research aims to apply topic modeling to automatically identify the main themes within congregant opinions. The algorithm used is Latent Dirichlet Allocation (LDA), analyzing 2,581 comments collected from the MUI Riau Smart Evaluation System. The research phase involved text preprocessing, such as cleaning, case folding, tokenizing, stopword removal, and stemming to produce clean data. This data was then converted into a Bag-of-Words (BoW) representation as input for the LDA model. The optimal number of topics was determined through evaluation using Coherence Score and Perplexity. Experimental results show that a configuration with 16 topics provides the best balance between semantic coherence and model generalizability, with a Coherence Score of 0.5008 and a Perplexity of -7.7787. The identified topics reflect diverse aspects, including prayers, appreciation for preachers, respect, discussions on Islamic values, and spiritual reflections. The LDA method proved effective in extracting thematic patterns from congregant opinions, providing a foundation for developing a real-time evaluation system.
Pencarian Jalur Terpendek Jakarta ke Jawa Barat Berbasis Algoritma Genetika Firyal Wishal Nabili; Eva Yulia Puspaningrum; Afina Lina Nurlaili
Prosiding SISFOTEK Vol 9 No 1 (2025): SISFOTEK IX 2025
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

The Travelling Salesman Problem (TSP) is a well-known combinatorial optimization problem aimed at finding the shortest route that visits each location exactly once and returns to the starting point. This study aims to determine the shortest travel route from Jakarta to all cities in West Java Province using a Genetic Algorithm (GA). Distance data between cities were obtained from the Central Bureau of Statistics (BPS) of Bekasi Regency and used to construct a distance matrix for distance calculation. The optimization process employed a population size of 100 individuals, a crossover rate of 0.7, a mutation rate of 0.05, and 500 generations. The algorithm used Roulette Wheel Selection for parent selection, PMX (Partially Mapped Crossover) for crossover, swap mutation for mutation, and elitism to preserve the best individuals across generations. Experimental results show that the initial route distance of 2918 km was reduced to 1314 km at generation 110 and remained stable until generation 500. The optimal route found was: Jakarta ? Bekasi ? Karawang ? Tangerang ? Serang ? Pandeglang ? Lebak ? Bogor ? Sukabumi ? Cianjur ? Subang ? Indramayu ? Kuningan ? Cirebon ? Tasikmalaya ? Ciamis ? Majalengka ? Sumedang ? Garut ? Bandung ? Purwakarta ? Jakarta. These results demonstrate that the Genetic Algorithm effectively provides optimal route solutions with fast convergence and high efficiency in solving the TSP.
Penerapan Design Thinking dalam Perancangan Prototipe Sistem Informasi Online Food Delivery Marsha Febriani Aditama; Umi Mamnuah Al Amini; Indah Fajriah; Jihan Cahya Marsya
Prosiding SISFOTEK Vol 9 No 1 (2025): SISFOTEK IX 2025
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

In this project, a mobile-based food delivery information system prototype was designed using the Design Thinking methodology. The development of a user-oriented prototype design aimed to address a number of issues in related applications, including ambiguous user interfaces, limited accessibility, and challenging navigation. The five main stages of Design Thinking—empathy, definition, ideation, prototyping, and testing—were used to carry out the development process. To determine user needs and assess satisfaction levels after prototype testing, 20 respondents were given pre-test and post-test questionnaires. Based on the test results, the prototype design was able to meet most user needs related to usability, interface appearance, and application functionality, with an average Likert score of 4.123, which falls into the “Good” category. These results demonstrate the effectiveness of the Design Thinking methodology in creating user-friendly and intuitive mobile applications. It is hoped that this will meet the needs of communities in areas with limited access to digital services
Perancangan Sistem Informasi Penjualan Web untuk Efisiensi Administrasi UMKM Makanan dan Minuman Fadhil Ezar Rahman; Binastya Anggara Sekti
Prosiding SISFOTEK Vol 9 No 1 (2025): SISFOTEK IX 2025
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

This research focuses on the design of a web-based sales information system aimed at assisting micro, small, and medium enterprises (MSMEs), particularly in the food and beverage sector, in managing their sales activities more effectively. The utilization of information technology is expected to improve operational efficiency and support the digitalization process, which is essential for business growth and sustainability. The proposed system includes key features such as an activity dashboard, modules for managing sales and purchase transactions, user account management, and product stock monitoring. The development method applied in this research is the Software Development Life Cycle (SDLC) using the Waterfall model, which consists of several stages: requirement analysis, system design, implementation, and testing. The results demonstrate that the system is capable of automating administrative processes that were previously managed manually. This leads to significant improvements in accuracy, speed, and accessibility of sales and purchase data With the implementation of this information system, MSMEs can manage transactions in a more structured manner, minimize recording errors, and support better business decision-making based on available data. This research is expected to provide a solution for MSMEs in adapting to digital transformation while contributing to the acceleration of digitalization in the food and beverage sector
Perancangan Sistem Informasi Klien Dewasa Pada BAPAS Kelas 1 Palembang Raka Ramadhan; Evi Fadilah
Prosiding SISFOTEK Vol 9 No 1 (2025): SISFOTEK IX 2025
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

This study aims to design an information system for adult clients at the Class I Correctional Center (Bapas) Palembang using the Prototyping method. The background of this research lies in the limitations of the existing Correctional Database System (SDP) which has not fully supported the operational needs of the Adult Client Guidance Section (BKD), especially in managing attendance records, Litmas archiving, and preparing periodic reports. Data were collected through observation and interviews with BKD officers, then analyzed to identify system requirements. The Prototyping method was applied through iterative stages, starting from communication, quick planning, design modeling, construction, and user feedback. The results of the design produced a prototype consisting of eight main interfaces, including client data management, attendance schedules, Litmas archives, and monthly reports. This prototype provides added value in terms of efficiency, accuracy, and ease of use for BKD officers, even though it is still limited to the design stage and has not yet been integrated with SDP. The findings of this research are expected to serve as a basis for the development of a more comprehensive system in the future.
Penerapan Power BI dalam Analisis Perilaku Pendengar Musik Streaming Ramadhani Rahmania Luhri; Rifky Dwitama; Risman Lesmana; Raihan Rizqia Zaini Rosadi
Prosiding SISFOTEK Vol 9 No 1 (2025): SISFOTEK IX 2025
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

This study aims to analyze the behavior of music streaming listeners using a Business Intelligence (BI) approach based on Microsoft Power BI. The dataset used includes demographic attributes, user behavior, and musical features such as energy, danceability, valence, and BPM. The data was processed through the Extract, Transform, and Load (ETL) stages to ensure the quality, integrity, and consistency of the information before being visualized in an interactive dashboard. The analysis results show age distribution, genre preferences, music listening patterns, and in-depth comparisons between streaming platforms and subscription types. The findings show that young adults to middle-aged adults (32, 38, and 51 years old) dominate as active listeners, with a high preference for Jazz, Reggae, and EDM genres. Further analysis reveals that premium users have higher engagement and loyalty rates than free users, while geographical and local cultural factors also significantly influence music preferences, with countries such as Australia and South Korea showing the highest number of users. Power BI was chosen for its ease of integration, affordability, scalability, and full support for Data Analysis Expressions (DAX), which enables complex data modeling and dynamic, real-time analysis of user behavior. The developed dashboard not only presents descriptive visualizations but also has the potential to be expanded for predictive and prescriptive analysis to strengthen the recommendation system, improve user retention strategies, and support data-driven strategic decision-making in the digital music industry.
Penerapan Text Mining untuk Pengelolaan dan Klasifikasi Informasi Berita Online Menggunakan Algoritma Naïve Bayes Alfitianti Azahra; Qonita Luthfiyah; Erika Nurkholisah; Kartika
Prosiding SISFOTEK Vol 9 No 1 (2025): SISFOTEK IX 2025
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

Negative reporting can cause a decline in public trust in public officials and news hoaxes can also cause divisions among local residents. Naïve Bayes is a simple probabilistic classifier that calculates a set of probabilities by adding up the frequencies and combinations of values ??from the given dataset, the accuracy results are obtained at 61.22% with this being explained in detail, namely Prediction of news results with the Neutral Category and it turns out to be true Neutral as many as 27 data. Predicted news results with a Neutral Category and turned out to be true positive as many as 23 data. Prediction of news results with a Neutral Category and it turns out to be true Negative as much as 1 Data. Predicted news results with a Positive Category and turned out to be true Neutral as many as 14 Data. Predicted news results with positive categories and turned out to be true positive as many as 33 data. Prediction of news results with a positive category and it turns out to be true negative as much as 0 data. Prediction of news results with a Negative Category and turns out to be true Neutral as much as 0 Data. Prediction of news results with a Negative Category and it turns out to be true Positive as much as 0 Data. Prediction of news results with a Negative Category and it turns out to be true Negative as much as 0 Data.

Page 42 of 48 | Total Record : 471

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