Abstract:Dalam data mining, penelitian mengenai klasifikasi kelulusan mahasiswa sudah pernah dilakukan oleh peneliti lain. Sebagian besar penelitian tersebut difokuskan pada identifikasi variabel prediktor. Ada banyak penelitian…
dalam literatur terdahulu yang menjelaskan faktor-faktor apa saja yang dapat mensukseskan proses pengklasifikasian kelulusan mahasiswa. Pemilihan penggunaan algoritma Naive Bayes, dan pada penelitian ini didasarkan pada beberapa alasan, yaitu: Selain ketiga algoritma tersebut sama-sama mudah diimplementasikan dan sama-sama dapat memberikan hasil yang baik dalam kasus klasifikasi, ketiga algoritma tersebut juga mempunyai beberapa keunggulan masing-masing. Implementasi data training sebanyak 51 data dengan algoritma Naive Bayes berhasil memprediksi besarnya kelulusan mahasiswa dengan persentase keakuratan sebesar 74,67%, Sebanyak 184 mahasiswa sebagai data uji yang dihasilkan penelitian ini bahwa mahasiswa yang akan lulus tepat waktu sebanyak 42 mahasiswa atau sekitar 22,8% dari jumlah data testing dengan keakuratan sebesar 74,67%, Bagi Prang Studi Teknik Informatika berdasarkan hasil penelitian ini diharapkan dapat dimanfaatkan oleh pihak jurusan sebagai bahan pertimbangan bahwa dari jumlah data testing sebanyak 184 mahasiswa yang diperdiksi lulus tepat waktu sekitar 22,8% dan jumlah tidak tepat waktu 77,2%.
Abstract:Technological advances support digital transformation in sales data management. Wan Toys & Sport stores face difficulty understanding sales patterns, such as the highest sales months and most popular products. This research…
rch uses the K-Means clustering method with the CRISP-DM approach to group sports products based on their sales level. The analysis results show that this method is able to divide products into three categories: high, medium and low, thus providing strategic insight for stock management and marketing. Products with high sales are prioritized for stock, while products with low sales are targeted for promotion. This method effectively supports operational efficiency and data-based decision making at Wan Toys & Sport stores.
Abstract:Education plays an important role in improving the quality of human life, but economic constraints often prevent many students from continuing their education. The Smart Indonesia Program (PIP) was launched to address these…
ese issues by providing educational assistance. However, in its implementation, the selection of PIP recipients at IT Al-Ikhsan Private Junior High School is still inaccurate. This research aims to classify the eligibility of PIP recipients using the Naive Bayes method. This method is applied to student data from the school's Dapodik in 2024 which consists of 265 students. The data is processed through CRISP-DM data mining stages, namely Business Understanding, Data Understanding, Data Preparation, Modeling, Evaluation, and Deployment. As a result, the Naive Bayes model showed an accuracy of 92.31% with a precision value for the “Yes” class of 89%, recall 100%, and F1-score 94%. In conclusion, variables such as means of transportation, KPS and KIP recipients, parents' income, and distance from home to school affect the eligibility of PIP recipients.
Abstract:Everbright has become one of the distributing companies selling various products, one of which is the Dettol product. In optimizing the stock and marketing of Dettol products, the company faces difficulties in identifying…
g the best-selling products and those less favored by customers. This research data originates from the sales transaction data of Dettol soap in November, comprising 77 sales data. Through the use of data mining, particularly the K-means Clustering method, it becomes a relevant approach to solving this issue. The objective of this research is to avoid excess inventory that remains unsold while meeting the diverse needs of customers. The results of this study show the visualization of the distribution of Dettol soap product clusters and grouping based on sales levels. There were 21 best-selling item data, 31 well-selling item data, and 25 less popular item data, enabling the company to manage inventory based on the best-selling items.
Abstract:The Self-Help Housing Stimulant Assistance (BSPS) is a government house renovation program aimed at low-income communities. This program aims to enhance self-sufficiency in construction and improve the quality of houses,…
facilities, infrastructure, and public utilities through the principle of mutual cooperation. BSPS recipients must meet several criteria, such as income, house ownership status, house size, floor type, wall type, roof type, and water source. To address issues based on these criteria, Data Mining techniques using the Naive Bayes method were employed. This study utilized a dataset of BSPS recipients in Air Genting Village, Air Batu Sub-district, comprising 88 samples. The classification results from applying Naive Bayes yielded a precision value of 84%, a recall value of 81%, an F1-score of 82%, and an accuracy of 81%. The objective of this research is to facilitate the classification of eligible and rightful recipients of government assistance in the form of BSPS. The results of this study are expected to provide an alternative solution in determining BSPS recipients in Air Genting Village, Air Batu Sub-district
Abstract:Stunting is a chronic nutritional problem that remains a serious challenge to child health because it is associated with impaired physical growth, cognitive development, and the quality of human resources in the future.…
This condition is influenced by inadequate nutritional intake, particularly during the first 1,000 days of life, which plays a critical role in determining the quality of child growth. Exclusive breastfeeding is considered an important factor that contributes to meeting nutritional needs and strengthening the immune system of children. The research problem focuses on the relationship between breastfeeding practices and the degree of stunting among children aged 1-5 years in the working area of Sempol Community Health Center, Bondowoso Regency, in 2025. The study employed a quantitative approach using an analytic survey design with a population consisting of all stunted toddlers in the area. A sample of 75 respondents was selected using a proportionate stratified random sampling technique. Data were collected through questionnaires and observation sheets that assessed breastfeeding practices and the level of stunting based on the height-for-age (HFA) indicator. The results show that 72% of children received exclusive breastfeeding, while the remainder received partial breastfeeding or were not exclusively breastfed. The distribution of stunting severity indicates that 57.3% of children experienced mild stunting, 34.7% moderate stunting, and 8% severe stunting. The Chi-Square statistical test produced a p-value of 0.003 (p < 0.05), indicating a significant relationship between breastfeeding practices and the degree of stunting. These findings demonstrate that the nutritional quality and antibodies contained in breast milk play an important role in supporting optimal child height growth. The novelty of this study lies in its analysis of the relationship between breastfeeding practices and the severity of stunting within the specific context of a local community health center area that has rarely been examined in detail. The findings emphasize the importance of health education for mothers and strong family support to strengthen exclusive breastfeeding practices as a strategic effort to prevent stunting.
Abstract:Islamic economics has different principles from conventional economics, including in terms of sales contracts. In Islamic economics, there are several types of sales contracts used, such as bai' al-salam (future sales) and…
nd bai’ al-salam(manufacturing sales). Trust sales contracts are also important in ensuring transparency of the price of the goods or services sold. The research method uses descriptive qualitative in describing and explaining specifically with literature studies in data collection. The purpose of this research is to find out specifically about the types and qualifications of sharia sales that do not contain gharar and usury. In Islamic economics, payments in sales contracts can be deferred or paid in installments without involving interest or riba. This allows the buyer to pay according to an agreed schedule. Sales contracts in the Islamic economy differ from interest-bearing loan contracts, where there is an exchange of goods or services at a predetermined price. Islamic banks use sales contracts as a legitimate alternative to interest-bearing loan contracts, allowing them to provide financing that is fair and compliant with sharia principles. In the Islamic economy, there are also contracts for the sale of future commodities (salam), the sale of manufacturing (istisna'), and currency exchange (sarf). Islamic banks have an important role to play in facilitating these sales contracts, as intermediaries who ensure the contracts adhere to Shariah principles and meet applicable legal requirements. With a good understanding of the different types of these sales contracts, economic actors can choose the ones that suit their needs while complying with sharia principles.
Abstract:Data mining merupakan salah satu metode yang paling efektif dalam menghasilkan klasifikasi yang akurat, efisien, dan relevan. Pengelompokan jenis kendaraan berdasarkan sistem transmisi dilakukan dengan menggunakan algoritma…
tma Decision Tree dan dievaluasi melalui confusion matrix. Dataset yang digunakan mencakup empat jenis kendaraan: Bebek, Skuter, Sport, dan Trail, dengan tiga jenis transmisi: Manual, Automatic, dan Kopling. Algoritma Decision Tree dipilih karena kemampuannya dalam membagi dataset secara rekursif untuk menghasilkan aturan klasifikasi yang jelas dan mudah dipahami. Model dilatih dan diuji untuk memprediksi jenis transmisi berdasarkan fitur kendaraan, dengan hasil akurasi mencapai 95%. Evaluasi menggunakan confusion matrix mengungkap distribusi prediksi benar dan salah pada setiap kategori. Hasilnya menunjukkan bahwa transmisi Automatic dan Kopling diklasifikasikan dengan akurasi tinggi, meskipun terdapat beberapa kesalahan pada prediksi transmisi Manual. Nilai Cohen’s Kappa sebesar 0,913 mengindikasikan kesesuaian yang sangat baik antara prediksi dan data aktual. Algoritma Decision Tree terbukti efektif dalam klasifikasi jenis kendaraan, meskipun diperlukan perbaikan untuk meningkatkan akurasi pada kategori tertentu.
Abstract:Abstract: This study aims to classify the nutritional status of toddlers based on anthropometric data using the K-Nearest Neighbor (KNN) algorithm. Data were obtained from 20 Integrated Health Posts (Posyandu) in Rumbai…
Timur District, including Lembah Sari Village and Limbungan Village with a total of 1,000 toddler data. After cleaning and preprocessing, 782 data were obtained ready for use. The preprocessing stages include data cleaning and transformation, outlier removal, minority class handling, and data normalization. Next, data balancing was carried out using the Synthetic Minority Oversampling Technique (SMOTE) to address class imbalance. The data was divided into 80% training data and 20% test data, then the K parameter was tested from 1 to 15 using 5-fold cross-validation. The results showed that the value of K = 1 provided the best performance with a macro recall of 0.8827 and an accuracy of 86.26%. These results indicate that the combination of the KNN algorithm with the SMOTE method and Min-Max normalization is effective in improving classification performance on imbalanced data and producing accurate and balanced predictions of toddler nutritional status between classes.
Keywords: k-nearest neighbor; toddler nutritional status; SMOTE; min-max scaling; classification; anthropometric data
Abstrak: Penelitian ini bertujuan untuk mengklasifikasikan status gizi balita berdasarkan data antropometri menggunakan algoritma K-Nearest Neighbor (KNN). Data diperoleh dari 20 Posyandu di Kecamatan Rumbai Timur, meliputi Kelurahan Lembah Sari dan Kelurahan Limbungan dengan total 1.000 data balita. Setelah melalui proses cleaning dan preprocessing, diperoleh 782 data yang siap digunakan. Tahapan pra-pemrosesan meliputi pembersihan dan transformasi data, penghapusan outlier, penanganan kelas minoritas, serta normalisasi data. Selanjutnya dilakukan penyeimbangan data menggunakan Synthetic Minority Oversampling Technique (SMOTE) untuk mengatasi ketidakseimbangan kelas. Data dibagi menjadi 80% data latih dan 20% data uji, kemudian dilakukan pengujian parameter K dari 1 hingga 15 menggunakan 5-fold cross-validation. Hasil penelitian menunjukkan bahwa nilai K = 1 memberikan performa terbaik dengan recall macro sebesar 0,8827 dan akurasi 86,26%. Hasil ini menunjukkan bahwa kombinasi algoritma KNN dengan metode SMOTE dan normalisasi Min-Max efektif dalam meningkatkan kinerja klasifikasi pada data tidak seimbang serta menghasilkan prediksi status gizi balita yang akurat dan seimbang antar kelas.
Kata kunci: k-nearest neighbor; status gizi balita; SMOTE; min-max scaling; klasifikasi; data antropometri
Abstract:Abstract: Information Technology (IT) has played a crucial role in various sectors, including the transportation sector, as seen in the Department of Transportation of Asahan Regency, North Sumatra. One of the challenges…
in this area is the performance of parking attendants, which affects the effectiveness of parking management and traffic safety. Poor performance of parking attendants can cause various issues, including traffic congestion, rule violations, and user discomfort. Therefore, evaluating the performance of parking attendants is essential to improve service quality and parking safety. In this context, the implementation of a technology-based information system is an appropriate solution to enhance the effectiveness of the performance evaluation process for parking attendants. Classification methods, such as k-nearest neighbor (KNN), are used to evaluate the performance of parking attendants more accurately and efficiently. This method allows early detection of poor performance, such as fraud or traffic rule violations, and provides feedback for improvements. The primary goal is to measure effectiveness, identify areas for improvement, and recognize parking attendants with good performance.
Keywords: Information Technology, Parking Attendants, Performance Evaluation, KNN, Asahan Regency.
Abstrak: Teknologi Informasi (TI) telah memainkan peran penting dalam berbagai sektor, termasuk sektor transportasi, seperti yang terlihat pada Dinas Perhubungan Kabupaten Asahan, Sumatera Utara. Salah satu tantangan di wilayah ini adalah kinerja juru parkir yang mempengaruhi efektivitas pengelolaan parkir dan keselamatan lalu lintas. Kinerja juru parkir yang kurang optimal dapat menimbulkan berbagai masalah, termasuk kemacetan, pelanggaran aturan, dan ketidaknyamanan pengguna parkir. Oleh karena itu, penilaian kinerja juru parkir menjadi sangat penting untuk meningkatkan kualitas layanan dan keamanan parkir. Dalam konteks ini, penerapan sistem informasi berbasis teknologi menjadi solusi yang tepat untuk meningkatkan efektivitas proses penilaian kinerja juru parkir. Metode klasifikasi, seperti k-nearest neighbor (KNN), digunakan untuk mengevaluasi kinerja juru parkir dengan lebih akurat dan efisien. Metode ini memungkinkan deteksi dini terhadap kinerja buruk, seperti penipuan atau pelanggaran aturan lalu lintas, serta memberikan umpan balik untuk perbaikan. Tujuan utamanya adalah mengukur efektivitas, mengidentifikasi area perbaikan, dan memberikan apresiasi bagi juru parkir yang memiliki kinerja baik.
Kata Kunci: Teknologi Informasi, Juru Parkir, Penilaian Kinerja, KNN, Kabupaten Asahan.