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INDONESIA
BULLET : Jurnal Multidisiplin Ilmu
Published by CV. Multi Kreasi Media
ISSN : -     EISSN : 28292049     DOI : -
Core Subject : Humanities, Health, Education, Social,
Humanities Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Medicine & Pharmacology Nursing
- Ilmu Komputer - Kemasyarakatan - Kewirausahaan - Manajemen - Ekonomi - Manajemen - Agama - Ilmu Hukum - Pendidikan - Pertanian - Sastra - Teknik - Dan Bidang Ilmu Lainnya
Arjuna Subject : Umum - Umum
Articles 589 Documents
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Hasil Belajar Kewirausahaan Ditinjau Dari Aspek Motivasi Dan Konsep Diri Pratiwi Ramdayana, Ira; Jayanti, Memmy; Muharomah, Siti
BULLET : Jurnal Multidisiplin Ilmu Vol. 4 No. 2 (2025): BULLET : Jurnal Multidisiplin Ilmu
Publisher : CV. Multi Kreasi Media

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Abstract

 The aim of this research is to determine 1). The influence of learning motivation and self-concept together on the entrepreneurship learning outcomes of class XI students at Pertiwi Vocational School, 2). The influence of learning motivation on the entrepreneurship learning outcomes of class The sample used was 60 students as research samples using simple random sampling techniques with multiple linear regression. Based on the results of the hypothesis and data analysis, it is concluded as follows: 1). There is a significant influence of motivation and self-concept together on the entrepreneurship learning outcomes of class XI students at Pertiwi Vocational School. This is proven by the simultaneous test results obtained by the calculated f value of 34.333 > f table 2.76. 2) There is a significant influence of motivation on the entrepreneurship learning outcomes of class XI students at Pertiwi Vocational School. This is proven by the partial test results which obtained a calculated t value of 4.125 > t table 1.672 3) There is a significant influence of self-concept on the entrepreneurship learning outcomes of class XI students at Pertiwi Vocational School. This is proven by the partial test results which obtained a calculated t value of 2.065 > t table 1.672.
Pengembangan Model Prediksi Keberhasilan Mahasiswa Menggunakan Algoritma Machine Learning Dalam Learning Management System Tohidi, Edi; Ali, Irfan
BULLET : Jurnal Multidisiplin Ilmu Vol. 2 No. 1 (2023): BULLET : Jurnal Multidisiplin Ilmu
Publisher : CV. Multi Kreasi Media

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Abstract

The advancement of digital technology in education has driven the widespread adoption of Learning Management Systems (LMS) as effective platforms for online learning. This study aims to develop a predictive model for student success in LMS environments using machine learning algorithms. Student success is classified based on parameters such as participation levels, access frequency, assessment results, and punctuality in assignment submissions. Several machine learning algorithms, including Decision Tree, Random Forest, Support Vector Machine, and K-Nearest Neighbors, are employed to build the prediction model. The performance of each model is evaluated using metrics such as accuracy, precision, recall, and F1-score. The results show that the Random Forest algorithm achieved the best performance with an accuracy of 89%, followed by Support Vector Machine and Decision Tree. The developed model is expected to assist educators and academic institutions in identifying students who may face learning difficulties at an early stage, allowing for timely and targeted interventions. This research contributes to the application of machine learning in supporting adaptive learning processes and enhancing data-driven educational quality.
Segmentasi Minat Mahasiswa Terhadap Program Studi Menggunakan Algoritma K-Means Clustering Wahyudin, Edi; Dikananda, Fatihanursari
BULLET : Jurnal Multidisiplin Ilmu Vol. 2 No. 1 (2023): BULLET : Jurnal Multidisiplin Ilmu
Publisher : CV. Multi Kreasi Media

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Abstract

Segmenting student interest in study programs is a crucial step in strategic decision-making within higher education. By identifying interest groups, institutions can design more relevant curricula and develop more effective marketing strategies. This study aims to cluster student interests in study programs using the K-Means Clustering algorithm. The data used in this research were obtained from questionnaires assessing the interests and preferences of new students towards various study programs. The results of applying the K-Means algorithm indicate that students can be grouped into several clusters based on the similarity of their interests, which can be utilized to support academic policy and program promotion strategies.
Evaluasi Efektivitas Sistem Rekomendasi Pembelajaran Adaptif Berbasis Deep Learning Dalam Meningkatkan Performa Siswa Kaslani; Anam, Khaerul
BULLET : Jurnal Multidisiplin Ilmu Vol. 2 No. 1 (2023): BULLET : Jurnal Multidisiplin Ilmu
Publisher : CV. Multi Kreasi Media

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Abstract

Artificial intelligence (AI)-based adaptive learning systems have shown great potential in enhancing the personalization and effectiveness of the learning process. This study evaluates the effectiveness of an adaptive learning recommendation system that utilizes deep learning models, specifically Bi-directional Long Short-Term Memory (BiLSTM), in improving student performance. The model is developed to analyze student interaction patterns on a Learning Management System (LMS) and provide personalized learning material recommendations. The study was conducted through an experiment involving 120 high school students divided into experimental and control groups. The evaluation results indicate that students using the system experienced significant improvements in final scores and completion rates. These findings support the integration of deep learning technology into adaptive learning systems to enhance the effectiveness and personalization of education.
Penerapan Naïve Bayes Dan Visualisasi Wordcloud Dalam Analisis Sentimen Pengguna E-Learning Narasati, Riri; Solehudin, Dodi
BULLET : Jurnal Multidisiplin Ilmu Vol. 2 No. 2 (2023): BULLET : Jurnal Multidisiplin Ilmu
Publisher : CV. Multi Kreasi Media

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Abstract

This study aims to analyze the sentiment of e-learning users using the Naïve Bayes method and WordCloud visualization. In today's digital era, e-learning has become an increasingly popular learning platform, making sentiment analysis of users on this platform crucial to understand their experiences. The Naïve Bayes method was chosen for classifying user sentiment, while WordCloud visualization is used to display the frequency of words appearing in user reviews. The data used in this research were collected from user comments and reviews on e-learning platforms. The results indicate that the Naïve Bayes method is effective in classifying user sentiment, while WordCloud provides a clear representation of the most frequent words in the reviews, revealing the sentiment patterns present.
Eksplorasi Pola Pembelian Konsumen Di E-Commerce Menggunakan Algoritma FP-Growth Hamonangan, Ryan; Arie Wijaya, Yudhistira
BULLET : Jurnal Multidisiplin Ilmu Vol. 2 No. 2 (2023): BULLET : Jurnal Multidisiplin Ilmu
Publisher : CV. Multi Kreasi Media

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Abstract

This study aims to explore consumer purchasing patterns on e-commerce platforms using the FP-Growth (Frequent Pattern Growth) algorithm. With the rise of e-commerce, it is crucial for platform managers to understand existing purchasing patterns in order to design more effective marketing strategies. The FP-Growth algorithm is chosen due to its efficiency in extracting association patterns, especially in large datasets. The data used in this research was obtained from purchase transactions on an e-commerce platform, including the items purchased by consumers over a specific time period. The results of this study reveal frequent purchasing patterns and product associations that can help platform managers design better product recommendations. The FP-Growth algorithm provides valuable insights to enhance consumer shopping experiences and the effectiveness of marketing strategies on e-commerce platforms.
Perbandingan Akurasi Algoritma Random Forest Dan Naïve Bayes Dalam Memprediksi Risiko Hipertensi Suprapti, Tati; Anwar, Saeful
BULLET : Jurnal Multidisiplin Ilmu Vol. 2 No. 2 (2023): BULLET : Jurnal Multidisiplin Ilmu
Publisher : CV. Multi Kreasi Media

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Abstract

Hypertension is one of the leading causes of serious health complications. Therefore, it is crucial to predict hypertension risks early to take preventive measures. This study aims to compare the accuracy of two machine learning algorithms, Random Forest and Naïve Bayes, in predicting hypertension risks using a dataset containing information about factors affecting health. Both algorithms were applied to classify patient data into two categories: high hypertension risk and low hypertension risk. Based on testing using evaluation metrics such as accuracy, precision, recall, and F1-score, the results showed that the Random Forest algorithm performed better than Naïve Bayes, with higher accuracy and more consistent performance. This finding can be used as a reference for the development of a decision support system for early hypertension detection in the community.
Studi Eksperimen Regenerative Shock Absorber Dan Implementasi Pada Model Half Car Rizky Riadini, Elfrida; An Nizhami, Avicenna
BULLET : Jurnal Multidisiplin Ilmu Vol. 3 No. 6 (2024): BULLET : Jurnal Multidisiplin Ilmu
Publisher : CV. Multi Kreasi Media

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Abstract

This study investigates the potential of utilizing vehicle vibrations as an energy source through a regenerative shock absorber (RSA) system based on a rack-pinion mechanism and electromagnetic generator. The research comprises two main stages: experimental testing of the RSA and its implementation into a numerical half-car suspension model. Experimental data were used to establish the relationship between translational velocity, damping force, voltage, and current. The average damping coefficient obtained was 827.33 Ns/m and was applied in simulations. The results indicate that the highest voltage and current outputs occur at a speed of 90 km/h, which corresponds to the largest suspension deflection amplitude. Simulation outcomes also demonstrate that the RSA effectively functions as both a vibration damper and an energy harvester. This study confirms the dual-functionality of RSA systems in improving ride comfort while simultaneously converting mechanical energy into electrical energy.
Pengelolaan Sampah Di Kota Tanggerang : Upaya Penerapan Kebijakan Publik Ananda, Faradila; Rahmawati; Satrio Wicaksono, Agung
BULLET : Jurnal Multidisiplin Ilmu Vol. 4 No. 2 (2025): BULLET : Jurnal Multidisiplin Ilmu
Publisher : CV. Multi Kreasi Media

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Abstract

The purpose of this study is based on the formulation of the problem that has been determined, namely to find out how to implement the Waste Management Policy in Cipondoh District, Tangerang City. This study uses a qualitative research design with the intention of understanding and delving deeper into the Implementation of Waste Management Policy in Cipondoh, Tangerang City. The data collection technique in this study uses primary sources and secondary sources. The tools used for data collection consist of: interview guides. The results of the research on the implementation of the waste bank management policy in Cipondoh District, Tangerang City, which was analyzed using the policy implementation theory of George C. Edward III, showed that the implementation of the policy has shown significant efforts, but still faces various challenges in each of the main variables. Overall, the implementation of the waste bank management policy in Cipondoh District still requires strengthening in terms of public communication, human resource capacity, implementation incentives, and bureaucratic consistency. A more inclusive participatory approach and adaptive technical policies are needed to increase the effectiveness of community-based waste management through waste banks. With the strengthening of the four Edward III variables, it is hoped that the waste management policy can run more optimally and sustainably.
Efektivitas Pengawasan Dinas Tenaga Kerja Dan Transmigrasi Wilayah Serang 1 Dalam Penerapan Keselamatan Dan Kesehatan Kerja Studi Di PT. Krakatau Baja Kontruksi Cilegon Nur Jarnita, Annisa; Waseh, Hasuri; Rahmawati
BULLET : Jurnal Multidisiplin Ilmu Vol. 4 No. 2 (2025): BULLET : Jurnal Multidisiplin Ilmu
Publisher : CV. Multi Kreasi Media

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Abstract

This research aims to determine the effectiveness of the supervision conducted by the Manpower and Transmigration Office of Serang Region I in addressing Occupational Safety and Health (OSH) issues at PT. Krakatau Baja Kontruksi, Cilegon City. The study applies the organizational effectiveness theory of Gibson, Ivancevich, and Donnelly using the goal achievement approach and the systems approach consisting of input, process, output, and environment dimensions. The method used is descriptive qualitative with exploratory approach and data collection techniques through interviews, observation, and documentation. The results show that OSH supervision has been carried out but is not yet optimal due to several shortcomings, such as uneven distribution of training, delays in following up violations, limited budget, and lack of firm sanctions from the Manpower and Transmigration Office of Serang Region I. Nevertheless, the company has made internal improvements, such as reporting violations through P2K3 and gradually implementing training programs. This research recommends enhancing OSH socialization, increasing the number of inspectors, and strengthening the reporting and evaluation system to support zero accident efforts in the workplace.

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