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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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Penerapan Data Mining Menggunakan Metode Cluster K-Means Untuk Pengelompokkan Fasilitas Sekolah Muhammad, Faisal; Suharmanto; Janu Ilham Saputo; Wiranti Sri Utami
Bulletin of Information Technology (BIT) Vol 6 No 4 (2025): Desember 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v7i1.2340

Abstract

School Facilities are facilities provided by schools or universities to support activities and can be utilized by students, teachers, students and staff within the scope of a particular education. In order to create good teaching and learning activities (KBM) and support the development process and achievements, good schools or universities must have classroom facilities, laboratories, libraries, canteens, places of worship and fields. By applying data mining and utilizing the data sources obtained and the application of the K-Means cluster method, information related to school facilities can be drawn. The number of clusters obtained is 2 clusters with the number of squares according to the cluster of 76.0%.
Penerapan Algoritma K-Means dan Apriori dalam Manajemen Stok UMKM Toko Sembako Berbasis Analisis BCG Matrix Tasril, Virdyra; Olivian, Daffa; Hasmajaya Simarmata, Randy
Bulletin of Information Technology (BIT) Vol 6 No 4 (2025): Desember 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v6i4.2375

Abstract

This study aims to analyze purchasing patterns at Toko Sembako HAS in Medan City, Medan Polonia District, using a Hybrid Data Mining approach that combines K-Means and Apriori algorithms. The dataset consists of 75,294 items sold over a 7-month period. The research workflow began with problem identification, literature review, data collection, and pre-processing, followed by algorithm implementation to produce product clustering and association patterns. Data normalization was performed using the Min-Max method to align the scales of Quantity and Profit, ensuring accurate K-Means clustering. The K-Means clustering combined with BCG Matrix categorized products into Stars, Cash Cows, Question Marks, and Dogs. Products such as Indomie and Mie Sedap were classified as Stars with high sales volume and medium-high profitability, while Minyak Curah and Beras were Cash Cows with moderate sales volume but the highest profitability. The Apriori algorithm revealed hidden purchasing patterns, with the highest Lift Ratio of 1.48 observed for the pair Pampers S and Mie Sedap, indicating a strong correlation within the young family segment. The hybrid approach provides strategic insights: K-Means supports inventory management and product segmentation, while Apriori guides marketing strategies such as product bundling and store layout. However, combinations of Cash-Cows and Question Marks yielded Lift Ratios below 1, indicating insignificant associations. The results demonstrate that this hybrid approach enhances understanding of consumer behavior and supports data-driven decisions to optimize sales and profitability.
Analisis Dan Prediksi Hasil Pertandingan Dota 2 Menggunakan Fuzzy Tsukamoto Tan, Muhammad Arief Adidharma; Yulindawati; Fahmi, Muhammad
Bulletin of Information Technology (BIT) Vol 6 No 4 (2025): Desember 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v6i4.2382

Abstract

Predicting the outcome of a Dota 2 match is a complex problem because it is influenced by many dynamic variables that change at each stage of the game. This study aims to analyze and predict the probability of winning a Dota 2 match using the Fuzzy Tsukamoto method based on three main variables: Hero Win Rate, Number of Kills, and Tower Destroyed. The fuzzy model was constructed using triangular and trapezoidal membership functions, with variable weights adjusted for the early game, mid game, and late game. Test results show that in the early game, the Hero Win Rate variable has the most dominant influence on the probability of winning, with a weight of 0.7. In the mid game, the number of kills and tower destruction begin to have a significant impact, while in the late game, towers and kills become the primary determinants of the probability of winning. The proposed system is able to generate different percentages of the probability of winning at each stage of the game and logically reflect the dynamics of the Dota 2 game. Based on these results, the Fuzzy Tsukamoto method is considered capable of handling uncertainty in Dota 2 match prediction and provides more flexible results than deterministic approaches, although it still depends on the quality of the dataset and the fuzzy rules used.
Sistem Pendukung Keputusan Pemilihan Staf Keamanan Terbaik Hotel Menggunakan Metode SMARTER Surizar Rahmi Danur; Nirwan Sinuhaji; Alyiza Dwi Ningtyas; Donny Sanjaya
Bulletin of Information Technology (BIT) Vol 6 No 4 (2025): Desember 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v6i4.2423

Abstract

The hotel industry provides accommodations that focus on guest comfort and safety. One crucial aspect of maintaining hotel security is selecting qualified security staff. However, the hotel faces challenges due to a lack of prior security staff selection. This results in difficulties in establishing clear selection criteria, resulting in an inefficient and unprofessional selection process. To address this issue, a decision support system (DSS) is required. This system will assist in data management, value calculation, and the generation of informed decisions. With a DSS, decision-making becomes easier, faster, and more accurate. This will increase efficiency, professionalism, and reliability in the security staff selection process. Furthermore, the best security staff will be given incentives for a period as a reward for the quality of their work. Implementing a DSS allows the selection of the best security staff based on predetermined criteria. The SMARTER (Simple Multi-Attribute Rating Technique Exploiting Ranks) method can be used as a tool in a DSS to select the best security staff. Using the SMARTER method can solve the problem of selecting the best security staff. Aripin, with a score of 0.87, was selected as the best security staff. This will help the hotel maintain guest trust, provide a sense of security and comfort, and build a positive reputation. As a result, it will become more professional in managing hotel security and providing excellent guest service.
Implementasi Metode ROC dan WP Dalam Sistem Pendukung Keputusan Terhadap Calon Penerima Pinjaman Koperasi Suhada, Karya; Hendrik, Dede; Andriyana; Isnandar, Evi; Dauni, Popon
Bulletin of Information Technology (BIT) Vol 6 No 4 (2025): Desember 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v6i4.2446

Abstract

Cooperatives are financial institutions that play a vital role in the economy, especially in developing countries. They provide various financial services to their members, including loans with relatively lower interest rates compared to commercial financial institutions. This study aims to develop and implement a Decision Support System (DSS) using the Rank Order Centroid (ROC) and Weighted Product (WP) methods for selecting cooperative loan recipients. Cooperatives often face challenges in determining eligible loan recipients to minimize default risk. The ROC method is used to objectively determine the criteria weights, while the WP method integrates these weights with the performance values of each candidate. By combining these two methods, it is expected to produce more accurate and fair decisions. The study was conducted in Asahan with data collected from various official sources. The criteria used include age, monthly income, employment status, credit history, and income stability. The results show that the combination of ROC and WP methods can improve the accuracy and efficiency of the cooperative loan recipient selection process and minimize the risk of default. This study contributes significantly to the field of DSS and can serve as a reference for developing decision-making methods in other fields requiring multi-criteria analysis. The findings also can be used by cooperatives to enhance the loan granting process, ensuring financial health, and member welfare. The implementation results indicate that the selected cooperative loan recipient is alternative A6, Fitriani Sari, with a score of 0.1257.
Penentuan Prioritas Bantuan Sosial Dengan Metode Combined Compromise Solution (CoCoSo) Darmansyah, Darmansyah; Yanitasari, Yessy; Yudiana, Yudiana; Nugraha, Agus; Suryana, Nana
Bulletin of Information Technology (BIT) Vol 6 No 4 (2025): Desember 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v6i4.2447

Abstract

Penyaluran bantuan sosial yang tepat sasaran merupakan kunci dalam mendukung kesejahteraan masyarakat, terutama di tengah keterbatasan sumber daya. Penelitian ini bertujuan untuk menentukan prioritas penerima bantuan sosial dengan menggunakan metode Combined Compromise Solution (CoCoSo), sebuah metode pengambilan keputusan multi-kriteria yang mampu menghasilkan solusi kompromi optimal dengan mempertimbangkan berbagai kriteria secara seimbang. Metode CoCoSo digunakan untuk mengevaluasi dan mengkombinasikan nilai dari setiap alternatif penerima bantuan berdasarkan kriteria yang telah ditentukan, sehingga menghasilkan peringkat prioritas yang objektif dan efisien. Penerapan metode ini diharapkan dapat membantu dalam proses seleksi penerima bantuan sosial yang lebih transparan dan tepat sasaran, terutama dalam kondisi di mana terdapat konflik atau perbedaan kepentingan antar kriteria. Hasil penelitian menunjukkan bahwa metode CoCoSo efektif dalam memberikan rekomendasi prioritas penerima bantuan sosial dengan solusi yang seimbang dan dapat diandalkan.

Page 26 of 26 | Total Record : 256

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