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Bulletin of Information Technology (BIT)
Published by Forum Kerjasama Pendidikan TInggi
ISSN : -     EISSN : 27220524     DOI : 10.47065/bit.v2i3.106
Core Subject : Science,
Computer Science & IT
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)
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 256 Documents
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Implementasi Algoritma Apriori untuk Meningkatkan Strategi Penjualan di Koperasi ABC Tama Irwan Syahputra; Wahyuni, Sri
Bulletin of Information Technology (BIT) Vol 5 No 4: Desember 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v5i4.1756

Abstract

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.
Machine Learning-Driven Sentiment Analysis of Social Media Data in the 2024 U.S. Presidential Race Samsir, Samsir; Ritonga, Wahyu Azhar; Aditiya, Rahmad; Watrianthos, Ronal
Bulletin of Information Technology (BIT) Vol 5 No 4: Desember 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v5i4.1762

Abstract

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.
Implementasi VPN Menggunakan Protokol L2TP Untuk Pengelolaan NAS (Network Attached Storage) Pada STB Zaldiyanto, Dimas; Subektiningsih; Wulandari, Irma Rofni
Bulletin of Information Technology (BIT) Vol 5 No 4: Desember 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v5i4.1770

Abstract

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.
Sistem Pendukung Keputusan untuk Kelayakan Kredit Nasabah dengan Metode ELECTRE Fitrah Putra Akhir, Ade; Andriyana, Andriyana
Bulletin of Information Technology (BIT) Vol 5 No 4: Desember 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v5i4.1780

Abstract

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.
Analisis Sentimen Terhadap Dampak Inflasi Menggunakan Naive Bayes Nurhaliza Sofyan, Siti; Iqbal, Muhammad
Bulletin of Information Technology (BIT) Vol 6 No 1: Maret 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v6i1.1796

Abstract

This research aims to analyze public sentiment regarding the impact of inflation in 2024 on survival. Inflation is seen as one of the most important factors influencing a country's economic growth. In this research, the results of public sentiment in 300 tweets on the Twitter application were obtained, namely the emotion 'joy' was 194 or 64%, 'surprise' was 71 or 23%, 'fear' was 20 or 6%, 'sadness' was 9 or 3% , 'disgusted' by 7 or 2% and 'angry' by 0.06% . This research uses the orange mining application with multilingual sentiment analysis techniques visualized through box plots and scatter plots, which aims to classify Twitter users based on their emotional responses. The decline in the level of economic growth has led to the emergence of the view that inflation has a negative effect on economic growth, not a positive effect. The findings of this research provide insight into the government's role in overcoming current inflation and providing sustainable benefits and are expected to be used as material for evaluating the government's role.
Analisis Pembelian Handphone Baru Dan Murah Terbaik Dengan Menggunakan Metode Simple Additive Weighting (SAW) Sinulingga, Novemtri; Rizky, Firahmi
Bulletin of Information Technology (BIT) Vol 6 No 1: Maret 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v6i1.1827

Abstract

Pada penelitian inj pembelian handphone yang dilakukan para pembeli kadang membuat binggung para pembeli, karena handphone yang akan dibeli sesuai dengan keteria yang mereka inginkan atau tidak sesuai. Dimana banyak pembeli handphone salah membeli handphone karena melihat handphone viral di sosmed tetapi bukan mengikuti kriteria yang mereka inginkan. Berdasarkan hal tersebut maka penelitian ini melakukan analaisis pendukung Keputusan yang digunakan untuk membantu para pembeli melakukan proses pemilihan handphone yang sesuai dengan kriteria yaitu harga, RAM, dan camera. Dimana kriteria yang digunakan sering menjadi pilihan utama dalam kriteria pemilihan pembelian handphone. Metode Pengambil Keputusan yang digunakan ialah metode Simple Additive Weighting (SAW). Dimana metode ini digunakan untuk menentukan nilai bobot dari setiap kriteria, lalu dilakukan proses prangkingan untuk menentukan alternatif hanphone dari sejumlah alternatif hanphone yang ada. Dengan adanya analisis system pendukung Keputusan yang menggunakan metode SAW (Simple Additive Weighting), supaya bisa membantu pembeli dalam memilih handphone berdasarkan dengan kriteria-kriteria yang telah ditetapkan. Kata Kunci: SAW1; Handphone2; Harga3; RAM4; Camera5
Pengembangan Aplikasi Guest Book Pada Cagar Budaya Sumbawa Berbasis Progressive Web App ( PWA ) Fatihurroyyan; Esabella, Shinta
Bulletin of Information Technology (BIT) Vol 6 No 1: Maret 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v6i1.1868

Abstract

In the research of cellphone purchases made by buyers sometimes confuse the buyers, because the cellphone to be purchased is in accordance with what they want or not. Where many cellphone buyers buy the wrong cellphone because they see viral cellphones on social media but not following the criteria they want. Based on this, this research conducts a decision support analysis that is used to help buyers carry out the process of selecting a cellphone that matches the criteria, namely price, RAM, and camera. Where the criteria used are often the main choice in the criteria for selecting a cellphone purchase. The decision-making method used is the Simple Additive Weighting (SAW) method. Where this method is used to determine the weight value of each criterion, then a ranking process is carried out to determine the alternative cellphone from a number of existing cellphone alternatives. With the analysis of a decision support system that uses the SAW (Simple Additive Weighting) method, so that it can help buyers in choosing a cellphone based on predetermined criteria.
Penerapan Data Mining Untuk Klasifikasi Penduduk Miskin Di Kabupaten Labuhanbatu Menggunakan Random Forest Dan K-Nearest Neighbors Ernawati, Andi; Khairul; Sitorus, Zulham; Iqbal, Muhammad; Nasution, Darmeli
Bulletin of Information Technology (BIT) Vol 6 No 2: Juni 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v6i1.1783

Abstract

This study aims to apply and compare the performance of two data mining algorithms—Random Forest (RF) and K-Nearest Neighbors (KNN)—in classifying poverty status among residents of Labuhanbatu Regency. The dataset includes information on occupation, income, housing, and education from 21,137 individuals. After undergoing preprocessing, model training, hyperparameter optimization, and evaluation, both models were assessed using five key metrics: accuracy, precision, recall, F1-score, and AUC. The results show that Random Forest performed slightly better than KNN, achieving an accuracy of 0.6023, precision of 0.4827, recall of 0.4177, F1-score of 0.4479, and an AUC of 0.5681. In comparison, KNN obtained an accuracy of 0.5990, precision of 0.4771, recall of 0.4006, F1-score of 0.4355, and an AUC of 0.5622. Based on these findings, it can be concluded that Random Forest is more effective for poverty classification on this dataset, although the performance difference is relatively small.
Analysis of Inpatient Data Using Cluster Analysis on Simulation Dataset Putera Utama Siahaan , Andysah; Azizah Harahap, Nur; Yuni Simanullang, Rahma; Khairunnisa; Wanny, Puspita; Utari
Bulletin of Information Technology (BIT) Vol 6 No 1: Maret 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v6i1.1830

Abstract

This study aims to analyze inpatient data using the K-Means Clustering method on a simulated dataset. The dataset includes various patient-related attributes such as age, billing amount, length of stay, medical condition, and type of admission. Several preprocessing steps were applied, including date conversion, duration calculation, numerical normalization, and one-hot encoding for categorical attributes. The Elbow Method was used to determine the optimal number of clusters, and clustering quality was evaluated using both the Silhouette Score and Davies-Bouldin Index. The analysis results show that the patients can be segmented into three major clusters, each exhibiting distinct characteristics—for example, younger patients with short and low-cost stays, and elderly patients with prolonged and more expensive hospitalizations. The resulting Silhouette Score of 0.14 and Davies-Bouldin Index of 1.74 reflect a moderate clustering performance, yet the model remains informative and meaningful. These clusters provide actionable insights that hospitals can use to optimize their service strategies, improve resource allocation, and enhance operational efficiency. Moreover, the study illustrates the practical application of unsupervised learning techniques in healthcare settings, contributing to data-driven decision-making practices and offering a foundation for further research into patient segmentation.
Perbandingan Metode MAUT dan TOPSIS dalam Menentukan Ponsel Terbaik Trianovie, Sri; Pane, Rahmadani; Putra Juledi, Angga
Bulletin of Information Technology (BIT) Vol 6 No 1: Maret 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v6i1.1876

Abstract

Usaha kerupuk ikan merupakan salah satu industri kecil dari UMKM (Usaha Mikro Kecil dan Menengah) tentang kerupuk yang didirikan oleh Febi. Industri ini masih berskala rumah tangga dan kecil. Usaha kerupuk ikan Febi masih tergolong baru dan masih dalam proses pengembangan. Permasalahan yang ada meliputi muncul usaha kerupuk yang sudah mapan dan berkembang pesat. Selain itu terdapat juga usaha kerupuk yang sejenis namun dengan harga yang lebih murah. Permasalahan tersebut menimbulkan persaingan diantara sesama usaha kerupuk. Setiap usaha kerupuk akan terus berinovasi dan mengeluarkan keunggulan dari masing-masing produknya. Hal ini membuat suatu usaha memerlukan strategi untuk bisa berdaya saing dan melakukan proses pengembangan usaha. Pada penelitian ini bertujuan menentukan strategi dalam peningkatan daya saing dan pengembangan usaha kerupuk ikan Febi. Hasil penelitian dapat diketahui bahwa terdapat tiga strategi terbaik yang dapat digunakan oleh Usaha kerupuk ikan Febi yaitu efisiensi biaya, membangun kerja sama (mitra) dengan pemerintah, dan pelaksaanaan promosi (offline dan online) mengenai produk.

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