1 10 6 https://repository.horizon.ac.id/files/original/36d43f783f1c851d0e4f02b64c5d60c1.pdf 545829b341b29770cb11d140907084ec Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource JANUARI–JUNI 2025, VOL 6(1) Contributor An entity responsible for making contributions to the resource Sri Wahyuni Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource PENGELOMPOKAN PENJUALAN PRODUK DENGAN MENGGUNAKAN K-MEANS CLUSTERING : STUDI KASUS ANALISIS PENJUALAN COFFEE SHOP OLEH KAGGLE.COM Subject The topic of the resource K-Means Clustering, Data Mining, Product Sales, Data Analysis, Silhouette Score Description An account of the resource The purpose of this study is to categorize coffee shop items sold by analyzing sales records with the K�Means clustering method. The Kaggle dataset consists of three main features: Product_ID, number of items sold (Transaction_Qty), and price per item (unit_price). This method was chosen because of its ability to identify sales patterns in grouping products into three clusters, namely cluster 0 has 56 products with the highest sales, cluster 1 has 23 products with medium sales, cluster 2 has 1 product with low sales. This study involved collecting data, cleaning it, standardizing it, finding out the best number of clusters, and then checking the results with a silhouette score of 0.67. The findings show that the K-Means method helps create products that are useful for business decisions, and also improves data-driven stock management and marketing plans. Creator An entity primarily responsible for making the resource Sifa Rismawati, Shofa Shofiah Hilabi , Bayu Priyatna, Agustia Hananto Source A related resource from which the described resource is derived https://ojs.itb-ad.ac.id/index.php/JUSIN/article/view/3078 Publisher An entity responsible for making the resource available Institut Teknologi dan Bisnis Ahmad Dahlan Date A point or period of time associated with an event in the lifecycle of the resource 2025-06-25 Contributor An entity responsible for making contributions to the resource Sri Wahyuni Rights Information about rights held in and over the resource E-ISSN : 2797-8516 Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource Indonesian Type The nature or genre of the resource Text Data analysis data mining K-Means Clustering Product Sales Silhouette Score https://repository.horizon.ac.id/files/original/523f321dfe17095b59b6a97186a6dba7.pdf c729f21eb199e8e89a24107fac865966 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource JANUARI–JUNI 2025, VOL 6(1) Contributor An entity responsible for making contributions to the resource Sri Wahyuni Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource OPTIMASI ALGORITMA RANDOM FOREST UNTUK MENINGKATKAN AKURASI PREDIKSI INDEKS MASSA TUBUH (BMI) Subject The topic of the resource Body Mass Index, Random Forest, Machine Learning Description An account of the resource Accurate Body Mass Index (BMI) prediction is essential for detecting obesity risks and related diseases. This study optimizes the Random Forest algorithm to enhance BMI prediction accuracy through hyperparameter tuning and feature selection. The dataset used is Obesity: Raw and Synthetic Data, which includes demographic and lifestyle variables. After undergoing subsetting, label encoding, and data imbalance handling using SMOTE, the model was trained using Random Forest and evaluated with accuracy, precision, recall, and F1-score metrics. The results indicate that the optimized model achieved 90% accuracy, with precision and recall of 0.89. Additionally, the feature importance analysis identified weight, height, and dietary habits as the most influential factors in BMI prediction. These findings confirm that optimizing the algorithm enhances model reliability in BMI classification and can be applied in data�driven health monitoring systems. This research is expected to contribute to the development of digital health applications and more accurate early obesity detection systems. Creator An entity primarily responsible for making the resource Eva Juliani, Apriade Voutama Source A related resource from which the described resource is derived https://ojs.itb-ad.ac.id/index.php/JUSIN/article/view/3021 Publisher An entity responsible for making the resource available Institut Teknologi dan Bisnis Ahmad Dahlan. Date A point or period of time associated with an event in the lifecycle of the resource 2025-06-25 Contributor An entity responsible for making contributions to the resource Sri Wahyuni Rights Information about rights held in and over the resource E-ISSN : 2797-8516 Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource Indonesian Type The nature or genre of the resource Text body mass index machine learning Random Forest https://repository.horizon.ac.id/files/original/12bce5ddd26956f20cb7bc8b4cdea04f.pdf 890a530401c3bc8ab2e92edc68818ebe Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource JANUARI–JUNI 2025, VOL 6(1) Contributor An entity responsible for making contributions to the resource Sri Wahyuni Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource OPTIMALISASI SISTEM INFORMASI BERBASIS AGILE UNTUK PENGELOLAAN BIAYA VARIABEL DAN EXCHANGE RATE DI INDUSTRI FMCG Subject The topic of the resource Information System, Agile, Variable Costs, Exchange Rate, FMCG Description An account of the resource In the FastMoving Consumer Goods (FMCG) industry, managing variable costs and exchange rates is a major challenge that affects operational efficiency and business decision-making. This study aims to develop an Agile-based information system that enables real-time data integration to improve transparency and accuracy in recording variable costs and exchange rates. The system was developed using the Agile Software Development methodology, consisting of Product Backlog, Sprint Planning, Daily Scrum, Development, Testing, and User Acceptance Testing (UAT). Key features include a variable cost and exchange rate Dashboard, which provides structured data presentation, and an input form that facilitates users in entering and managing data according to operational needs. Testing was conducted through UAT involving the System Developer, IT Product team, and production team users. The results indicate that the system enhances cost recording efficiency, provides better visibility of exchange rate fluctuations, and accelerates data validation processes. Creator An entity primarily responsible for making the resource Muhammad Rizky Saputra, Apriade Voutama Source A related resource from which the described resource is derived https://ojs.itb-ad.ac.id/index.php/JUSIN/article/view/3039 Publisher An entity responsible for making the resource available Institut Teknologi dan Bisnis Ahmad Dahlan. Date A point or period of time associated with an event in the lifecycle of the resource 2025-06-25 Contributor An entity responsible for making contributions to the resource Sri Wahyuni Rights Information about rights held in and over the resource E-ISSN : 2797-8516 Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource Indonesian Type The nature or genre of the resource Text Agile Exchange rate FMCG Information System Variable Costs https://repository.horizon.ac.id/files/original/ab576dbb916ab0f26e55c9d4f8f000e4.pdf d52695a3407ad7c555a5c847a7e7c3b2 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource JANUARI–JUNI 2025, VOL 6(1) Contributor An entity responsible for making contributions to the resource Sri Wahyuni Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource PENGEMBANGAN APLIKASI BERBASIS WEB UNTUK PERAWATAN MOBIL DAN PENGELOLAAN BENGKEL DENGAN METODE PROTOTIPE Subject The topic of the resource Web-Based, Application, Car Workshop, Car Maintenance, Prototyping Description An account of the resource This study presents the development of CekMobilmu.com, a web-based application designed to support car owners and automotive workshop in Jakarta by facilitating the digital recording of vehicle maintenance and repair activities. In response to the increasing technological advancement and rising demand for efficient service documentation, the application provides features for logging service history, monitoring vehicle condition, and managing workshop operations. Employing the Prototype Method, the research was conducted through sequential stages of data collection, system design, implementation, and evaluation. Data were obtained using questionnaires, interviews, and comparative analysis with existing similar applications. The evaluation phase demonstrated that the application effectively assists users in tracking maintenance schedules and enables workshops to record and manage repair tasks more efficiently. CekMobilmu.com addresses the communication gap between vehicle owners and service providers, offering a centralized and practical solution for vehicle maintenance management. Creator An entity primarily responsible for making the resource Aisha Gemala Jondya, Alva Davian Trisanto, Azizah Dinda Yukadifa, Muhammad Rizky Noval Source A related resource from which the described resource is derived https://ojs.itb-ad.ac.id/index.php/JUSIN/article/view/3121 Publisher An entity responsible for making the resource available Institut Teknologi dan Bisnis Ahmad Dahlan Date A point or period of time associated with an event in the lifecycle of the resource 2025-06-25 Contributor An entity responsible for making contributions to the resource Sri Wahyuni Rights Information about rights held in and over the resource E-ISSN : 2797-8516 Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource Indonesian Type The nature or genre of the resource Text Application Car Maintenance Car Workshop Prototyping Web-based https://repository.horizon.ac.id/files/original/9596243b78ac243d9927d22a6dade76c.pdf a4091768f4bb5060aff414032d19a0fb Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource JANUARI–JUNI 2025, VOL 6(1) Contributor An entity responsible for making contributions to the resource Sri Wahyuni Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource ANALISIS FAKTOR SOSIAL EKONOMI YANG MEMPENGARUHI RENDAHNYA CAPAIAN PENDIDIKAN DI INDONESIA MENGGUNAKAN KOMBINASI METODE DATA MINING Subject The topic of the resource Education inequality, Socio-economic factors, K-Means Clustering , Decision Tree, Data�driven policy Description An account of the resource Educational inequality remains a persistent issue in Indonesia, particularly in regions with challenging socio-economic conditions. This study aims to analyze how various socio-economic factors influence the average years of schooling across Indonesian provinces using a combination of K-Means Clustering and Decision Tree algorithms. The dataset includes indicators such as poverty rate, gross regional domestic product (GRDP), per capita expenditure, and life expectancy, obtained from official national statistics. K-Means Clustering was employed to segment provinces into three distinct groups based on socio�economic similarities. The clustering revealed clear disparities among regions, where the most disadvantaged cluster showed significantly lower education levels. Subsequently, the Decision Tree algorithm was used to classify the average years of schooling, identifying per capita expenditure, life expectancy, and socio-economic cluster as the most influential variables. The combined approach allows for both segmentation and interpretation, providing data-driven insights that are accessible and actionable for policymakers. The findings highlight the importance of targeting socio-economic improvements as a strategy to enhance educational outcomes. Ultimately, this study underscores the value of integrating unsupervised and supervised machine learning models in addressing complex social issues in education. Creator An entity primarily responsible for making the resource Diana Yusuf, Fahrul Razi Source A related resource from which the described resource is derived https://ojs.itb-ad.ac.id/index.php/JUSIN/article/view/3115 Publisher An entity responsible for making the resource available Institut Teknologi dan Bisnis Ahmad Dahlan Date A point or period of time associated with an event in the lifecycle of the resource 2025-06-25 Contributor An entity responsible for making contributions to the resource Sri Wahyuni Rights Information about rights held in and over the resource E-ISSN : 2797-8516 Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource Indonesian Type The nature or genre of the resource Text Data-driven policy Decision Tree Education inequality K-Means Clustering Socio-economic factors https://repository.horizon.ac.id/files/original/9c856faa2aaf4948ebbc4a3bd8a2e059.pdf 8ce7a93ad738c48e6138a567697232da Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource JANUARI–JUNI 2025, VOL 6(1) Contributor An entity responsible for making contributions to the resource Sri Wahyuni Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource PENGARUH TIKTOK ADS DAN BLACK CAMPAIGN TERHADAP PERILAKU PEMBELIAN KONSUMEN DI KOTA BATAM Subject The topic of the resource black campaign, tiktok ads, endorsement, digital marketing, regresi Description An account of the resource The use of social media platforms such as TikTok as a tool for digital marketing continues to grow along with the increasing number of users, both for building brand awareness through TikTok Ads and indirectly through black campaigns. This study aims to analyze the influence of TikTok Ads and Black Campaigns on consumer purchasing behavior in Batam City. A quantitative method was employed by distributing online questionnaires to active TikTok users using stratified disproportional random sampling. Data analysis was conducted using SPSS software, including validity and reliability tests, multiple linear regression, and classical assumption testing. The results show that both TikTok Ads and Black Campaigns have a positive and significant influence on consumer purchasing behavior, with B coefficients of 0.360 and 0.390, respectively. These findings indicate that although black campaigns are negative in nature, their exposure can trigger consumer curiosity about the highlighted product. The implications of this study suggest that business actors need to be more selective and adaptive in developing digital marketing strategies, as consumer perceptions are influenced not only by positive promotions but also by the negative narratives circulating online. Therefore, ethical and fact-based communication strategies are key to maintaining consumer trust and brand reputation in the digital era. Creator An entity primarily responsible for making the resource R. Ilham Ramizan Fahris, Felix Madison, Andiko Damar Putra, Bimo Birra, Aelwen Ababil Source A related resource from which the described resource is derived https://ojs.itb-ad.ac.id/index.php/JUSIN/article/view/3143 Publisher An entity responsible for making the resource available Institut Teknologi dan Bisnis Ahmad Dahlan Date A point or period of time associated with an event in the lifecycle of the resource 2025-06-25 Contributor An entity responsible for making contributions to the resource Sri Wahyuni Rights Information about rights held in and over the resource E-ISSN : 2797-8516 Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource Indonesian Type The nature or genre of the resource Text black campaign Digital Marketing endorsement regresi tiktok ads