Bulletin of Information Technology (BIT)
Jurnal Bulletin of Information Technology (BIT) memuat tentang artikel hasil penelitian dan kajian konseptual bidang teknik informatika, ilmu komputer dan sistem informasi. Topik utama yang diterbitkan mencakup:berisi kajian ilmiah informatika tentang : Sistem Pendukung Keputusan Sistem Pakar Sistem Informasi, Kriptografi Pemodelan dan Simulasi Jaringan Komputer Komputasi Pengolahan Citra Dan lain-lain (topik lainnya yang berhubungan dengan teknologi informasi)
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<![CDATA[Penerapan Algoritma Apriori untuk Optimasi Strategi Penjualan Berdasarkan Analisis Pola Pembelian di Torsa Cafe ]]>
<![CDATA[Ibezato Zalukhu, Anzas]]>;
<![CDATA[Sartika, Dewi]]>;
<![CDATA[Wahyuni, Sri]]>
<![CDATA[ Bulletin of Information Technology (BIT) Vol 5 No 4: Desember 2024 ]]>
Publisher : <![CDATA[Forum Kerjasama Pendidikan Tinggi (FKPT) ]]>
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DOI: 10.47065/bit.v5i4.1715
<![CDATA[This study aims to analyze consumer purchasing patterns at Torsa Café using data mining methods with the Apriori algorithm to discover association rules between products that are frequently purchased together. In facing the increasingly competitive business environment in the food and beverage industry, understanding consumer purchasing behavior becomes key to enhancing marketing and operational strategies. This research uses sales transaction data from October 2024, consisting of 31 transactions with a total of 129 items. The analysis process begins with data collection and normalization of transaction data, followed by the application of the Apriori algorithm to calculate the support and confidence values of items in the transactions. The analysis results show several items with high support levels, such as "Sanger Espresso", "Avocado Cappuccino Torsa", and "Kopi Susu Torsa", with support values above 30%. Additionally, product combinations frequently purchased together, such as Kopi Tancap with Redvelvet, Macchiato, Frappucino, and Kopi Susu Torsa, can serve as the basis for promotions or more efficient stock management. These findings provide valuable insights for Torsa Café management to determine product placement strategies, raw material stock management, and design more targeted promotions based on the identified purchasing patterns. Therefore, the results of this study are expected to improve operational efficiency and enhance Torsa Café’s competitiveness in the increasingly competitive market.]]>
<![CDATA[Analisa data Untuk Menentukan Kelulusan Proposal Penelitian Dosen internal STMIK Triguna Dharma Menggunakan Metode Analytical Hierarchy Proses (AHP) ]]>
<![CDATA[Ayu, Ayu Ofta Sari]]>;
<![CDATA[Wahyuni, Sri]]>
<![CDATA[ Bulletin of Information Technology (BIT) Vol 5 No 4: Desember 2024 ]]>
Publisher : <![CDATA[Forum Kerjasama Pendidikan Tinggi (FKPT) ]]>
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DOI: 10.47065/bit.v5i4.1726
<![CDATA[he selection process for lecturer research proposals at STMIK Triguna Dharma is often faced with challenges in objective and transparent assessment. This is due to the high number of proposals submitted and the variety of criteria that need to be considered, such as scientific contribution, innovation, relevance and implementation potential. This research aims to develop a more objective selection model by applying the Analytical Hierarchy Process (AHP) method in determining the feasibility of lecturer research proposals. The AHP method is used because of its ability to break down complex problems into a hierarchical structure and calculate the priority weights of each assessment criterion. This research process begins with identifying the main criteria and sub-criteria, followed by collecting data from research proposals, expert interviews, and literature studies. Each criterion is evaluated through a pairwise comparison matrix to obtain objective priority weights. Next, all research proposals are assessed based on the weight of the criteria and ranked to determine the most feasible proposal. The research results show that the criteria for scientific contribution and relevance to institutional goals have the highest weight in the assessment, making them the main aspects in the proposal selection process at STMIK Triguna Dharma. With the AHP method, this research concludes that the proposal selection process can be carried out more systematically, transparently and fairly. The implementation of this model is expected to be able to help institutions fund research that is most relevant and has a significant impact in accordance with the campus' vision and mission. Keywords: Lecturer research; Analytical Hierarchy Process; Data analysis; Matrix; Ranking]]>
<![CDATA[Implementasi Data Mining Dalam Mengelompokkan Tingkat Kepuasan Pemakaian Jasa Cleaning Service Dengan Menggunakan Algoritma K-Means Clustering ]]>
<![CDATA[Nadya, Nadya Septiani]]>;
<![CDATA[Wahyuni, Sri]]>
<![CDATA[ Bulletin of Information Technology (BIT) Vol 5 No 4: Desember 2024 ]]>
Publisher : <![CDATA[Forum Kerjasama Pendidikan Tinggi (FKPT) ]]>
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DOI: 10.47065/bit.v5i4.1729
<![CDATA[Pinang Jaya Abadi Indonesia is a company providing cleaning services to various sectors, including hospitals, commercial businesses, offices, and shopping centers. However, problems arise when complaints regarding the quality of service provided by its employees occur. To improve service quality and assess customer satisfaction with the offered services, a system capable of accurately and efficiently clustering customer satisfaction data is needed. As a solution, this study applies the K-Means Clustering algorithm in the field of Data Mining to cluster customer satisfaction data regarding the cleaning services provided by PT. Pinang Jaya Abadi Indonesia. The K-Means algorithm was chosen for its ability to cluster data quickly and effectively, and its proven efficiency in various data clustering cases. By using this algorithm, the study aims to produce more structured and informative data clusters, providing a clearer understanding of customer satisfaction levels. The results of this study show that the system designed using the K-Means Clustering algorithm can effectively cluster customer satisfaction data, yielding efficient and accurate results. This system can serve as a tool for PT. Pinang Jaya Abadi Indonesia to enhance service quality and minimize customer complaints by focusing more on clusters with low satisfaction levels.]]>
<![CDATA[Automatic Detection of Diabetic Retinopathy Eye Fundus Images Using Matlab ]]>
<![CDATA[Siska, Siska Atmawan Oktavia]]>
<![CDATA[ Bulletin of Information Technology (BIT) Vol 5 No 4: Desember 2024 ]]>
Publisher : <![CDATA[Forum Kerjasama Pendidikan Tinggi (FKPT) ]]>
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DOI: 10.47065/bit.v5i4.1742
<![CDATA[Diabetic Retinopathy (DR) is one of the causes of diabetes mellitus and is an important cause of visual disability and blindness. Screening of diabetic retinopathy is essential for both early detection and early treatment. Currently, the ophthalmologists use a non-mydriatic fundus camera to capture retinal images. Based on the fundus images, the ophthalmologists diagnose manually, which is time-consuming and prone to errors. The objectives of this project are to study image processing techniques, particularly on fundus images for diabetic retinopathy screening, to develop an automatic screening and classification system for diabetic retinopathy using fundus images in order to detect diabetic retinopathy at an early stage, and finally, to propose use of new eye fundus images, expert diagnosis image processing techniques, machine learning classifiers, and also App Designer as the Graphical User Interface (GUI) environment for early detection of the signs of diabetic retinopathy. An accurate retinal screening, therefore, is required to assist the retinal screeners to classify the retinal images effectively. Highly efficient and accurate image processing techniques must thus be used in order to produce an effective screening of diabetic retinopathy. It is envisaged that the proposed decision support system for clinical screening would greatly contribute to and assist the management and the detection of diabetic retinopathy.]]>
<![CDATA[Analisis Tren Pendaftaran Siswa Menggunakan Big Data di Yayasan Pendidikan Raksana Medan ]]>
<![CDATA[Nadya, Nadya Septiani]]>;
<![CDATA[Iqbal, Muhammad]]>
<![CDATA[ Bulletin of Information Technology (BIT) Vol 5 No 4: Desember 2024 ]]>
Publisher : <![CDATA[Forum Kerjasama Pendidikan Tinggi (FKPT) ]]>
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DOI: 10.47065/bit.v5i4.1744
<![CDATA[Yayasan Pendidikan Raksana Medan is an educational institution encompassing SMP, SMA, SMK-1, and SMK-2 levels. With an increasing number of students each year, analyzing student enrollment data has become crucial for strategic planning and decision-making. This study aims to analyze student enrollment trends using a Big Data approach to identify enrollment patterns, study program preferences, and factors influencing the number of applicants. The data used includes enrollment information from the past five years, such as demographic data, program choices, and enrollment timing. The analysis was conducted using data mining methods and data visualization to identify specific trends and patterns. The results of the study indicate a significant increase in applicants to vocational programs, with the majority of applicants coming from areas around Medan. These findings are expected to assist Yayasan Pendidikan Raksana Medan in improving marketing strategies and curriculum adjustments based on student and community demand]]>
<![CDATA[A Text Mining Approach to Analyzing the Role of Negative Sentiment Words in News Articles on Suicide and Related Incidents ]]>
<![CDATA[Subagio, Selamat]]>;
<![CDATA[Samsir, Samsir]]>;
<![CDATA[Dalimunthe, Abdul Hakim]]>;
<![CDATA[Ronal Watrianthos]]>
<![CDATA[ Bulletin of Information Technology (BIT) Vol 5 No 4: Desember 2024 ]]>
Publisher : <![CDATA[Forum Kerjasama Pendidikan Tinggi (FKPT) ]]>
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DOI: 10.47065/bit.v5i4.1745
<![CDATA[This study examines the role of negative sentiment words in news media coverage of suicide and related incidents through analysis of 1,515 news articles published between 2019 and 2024. Using advanced text mining techniques and sentiment analysis, we investigated patterns in emotional language use and their impact on public discourse. The research revealed frequent usage of negative sentiment words such as "crisis" (256 occurrences), "despair" (214 occurrences), and "death" (189 occurrences), which significantly influenced the emotional framing of these sensitive topics. Statistical analysis showed strong correlations between negative sentiment words and mental health-related terms (correlation value 0.75), indicating consistent patterns in media narrative construction. Temporal analysis identified a notable increase in negative sentiment during the COVID-19 pandemic (2020-2021), followed by a shift toward more solution-focused coverage in 2022-2024. The findings suggest that while negative sentiment words are inherent in covering suicide-related topics, their use can be balanced with solution-oriented language to promote more responsible reporting. This research contributes to understanding how emotional language shapes public discourse on mental health crises and provides insights for developing more effective guidelines for responsible journalism.]]>
<![CDATA[Implementasi Algoritma Apriori untuk Meningkatkan Strategi Penjualan di Koperasi ABC Tama ]]>
<![CDATA[Irwan Syahputra]]>;
<![CDATA[Wahyuni, Sri]]>
<![CDATA[ Bulletin of Information Technology (BIT) Vol 5 No 4: Desember 2024 ]]>
Publisher : <![CDATA[Forum Kerjasama Pendidikan Tinggi (FKPT) ]]>
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DOI: 10.47065/bit.v5i4.1756
<![CDATA[Penelitian ini bertujuan untuk meningkatkan strategi penjualan di Koperasi ABC Tama dengan memanfaatkan algoritma Apriori. Algoritma ini diterapkan untuk menganalisis data transaksi dan mengidentifikasi pola asosiasi produk yang sering dibeli bersama oleh anggota koperasi. Di tengah persaingan bisnis yang semakin ketat, pemahaman mendalam tentang perilaku konsumen menjadi krusial, dan algoritma Apriori menawarkan solusi untuk menggali informasi berharga tersebut. Dalam penelitian ini, algoritma Apriori digunakan untuk menemukan hubungan tersembunyi antara produk-produk yang dibeli anggota. Nilai minimum support ditetapkan sebesar 30% untuk memastikan bahwa pola asosiasi yang ditemukan cukup signifikan dan mewakili perilaku mayoritas anggota. Hasil analisis menunjukkan adanya hubungan yang kuat antara produk "Floridina Orange" dan "Gula". Pola asosiasi ini memiliki support sebesar 0,68, yang berarti 68% dari seluruh transaksi di koperasi memuat kedua produk tersebut. Confidence sebesar 0,875 menunjukkan bahwa 87,5% dari anggota yang membeli "Floridina Orange" juga membeli "Gula". Temuan ini memberikan wawasan berharga bagi koperasi dalam merancang strategi pemasaran yang lebih tepat sasaran. Dengan memahami produk-produk yang cenderung dibeli bersamaan, koperasi dapat mengoptimalkan penataan produk di toko, membuat paket promosi yang menarik, dan menawarkan rekomendasi produk yang relevan kepada anggota. Penerapan algoritma Apriori diharapkan dapat membantu Koperasi ABC Tama meningkatkan daya saing, memaksimalkan profitabilitas, serta meningkatkan efisiensi dalam pengelolaan stok dan pemasaran.]]>
<![CDATA[Machine Learning-Driven Sentiment Analysis of Social Media Data in the 2024 U.S. Presidential Race ]]>
<![CDATA[Samsir, Samsir]]>;
<![CDATA[Ritonga, Wahyu Azhar]]>;
<![CDATA[Aditiya, Rahmad]]>;
<![CDATA[Watrianthos, Ronal]]>
<![CDATA[ Bulletin of Information Technology (BIT) Vol 5 No 4: Desember 2024 ]]>
Publisher : <![CDATA[Forum Kerjasama Pendidikan Tinggi (FKPT) ]]>
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DOI: 10.47065/bit.v5i4.1762
<![CDATA[This study investigates public sentiment patterns during the 2024 U.S. Presidential Race through machine learning analysis of social media data from X (formerly Twitter). Using a dataset of 500 annotated tweets collected from Kaggle, we employ BERT-based sentiment analysis, temporal engagement tracking, and Latent Dirichlet Allocation (LDA) topic modeling to examine discourse across five major candidates. The analysis reveals predominantly positive sentiment (54.2%) in political discussions, with established party candidates receiving higher positive engagement. Temporal analysis demonstrates strong correlations between major campaign events and public engagement, with presidential debates generating peak interaction levels. Topic modeling identifies five key themes driving voter discourse: economic policy, healthcare, climate change, social justice, and foreign policy. Positive content consistently achieved 20-30% higher engagement rates than negative content, though negative sentiments showed sharp spikes during controversies. Our findings contribute to understanding digital political discourse dynamics and offer practical insights for campaign strategy in the social media era. The study's limitations include platform-specific constraints and a two-month observation period, suggesting opportunities for cross-platform analysis in future research.]]>
<![CDATA[Implementasi VPN Menggunakan Protokol L2TP Untuk Pengelolaan NAS (Network Attached Storage) Pada STB ]]>
<![CDATA[Zaldiyanto, Dimas]]>;
<![CDATA[Subektiningsih]]>;
<![CDATA[Wulandari, Irma Rofni]]>
<![CDATA[ Bulletin of Information Technology (BIT) Vol 5 No 4: Desember 2024 ]]>
Publisher : <![CDATA[Forum Kerjasama Pendidikan Tinggi (FKPT) ]]>
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DOI: 10.47065/bit.v5i4.1770
<![CDATA[Implementing Virtual Private Network (VPN) in remote Network Attached Storage (NAS) control using L2TP protocol on Mikrotik Router. This study uses a used device, Set Top Box HG680P, converted into a NAS server as a more economical and environmentally friendly alternative to buying a conventional NAS server. Implementation of L2TP VPN via Mikrotik facilitates remote access with guaranteed security levels. Testing was carried out using two devices, a Laptop and a Smartphone, which were used to access and transfer data via a VPN network. The test results showed that the VPN implementation successfully facilitated access from various locations and data transfer with good performance. In testing, the download speed was 50 Mbps, and the upload speed was 10 Mbps for file sizes from 50 Mb to 1000 Mb. The test results using VPN gave an average speed of all file transfers of 15.12Mb/s with an average transfer time of 4 minutes 14 seconds. Testing was also carried out by disconnecting the VPN connection on Mikrotik. The unconnected VPN on Mikrotik causes the browser to fail to access the site because the VPN cannot access information on the NAS Server. Therefore, VPNs play an important role as a bridge to access the NAS server outside the local network. In access management, restrictions are imposed on each user to increase security when accessing or sharing files on the NAS server with others. The goal is for users to have access restrictions, only being able to access the specified parts. This research is expected to contribute to developing secure, economical, and efficient network solutions, especially in utilizing used devices for data management.]]>
<![CDATA[Sistem Pendukung Keputusan untuk Kelayakan Kredit Nasabah dengan Metode ELECTRE ]]>
<![CDATA[Fitrah Putra Akhir, Ade]]>;
<![CDATA[Andriyana, Andriyana]]>
<![CDATA[ Bulletin of Information Technology (BIT) Vol 5 No 4: Desember 2024 ]]>
Publisher : <![CDATA[Forum Kerjasama Pendidikan Tinggi (FKPT) ]]>
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DOI: 10.47065/bit.v5i4.1780
<![CDATA[In the era of globalization and the rapid development of information technology, the role of financial services in the economy is very important. One sector that plays a central role is banking, especially in the distribution of collateral-based cash credit. Cash credit is credit provided for consumer needs with physical collateral, and its eligibility is assessed based on the customer's capabilities and the value of the collateral. This assessment faces challenges related to fluctuations in asset values and economic conditions. The Electre Method (Elimination Et Choix Traduisant la Realité) is a multi-criteria decision making method that can assist banks in assessing the feasibility of cash credit based on collateral. This research aims to develop a Decision Support System (SPK) to assess the feasibility of applying for cash credit using the Electre method. The results of calculating loan eligibility using the Electre method, both manually and through the system, display appropriate results. SPK produced a final score of 13,953 as first place with the alternative Ajeng Sekar. Testing the system using black box testing shows that all features in the system function properly as designed. The novelty of this research includes the application of the Electre method in a banking context, customization for local conditions, stronger predictive capabilities, comprehensive risk analysis, and optimization of the decision process. Thus, this research has the potential to increase efficiency, accuracy and stability in cash credit assessment, as well as supporting economic growth and banking stability in Indonesia.]]>
