Abstract:Abstract: Mental health is an essential aspect of overall well-being, particularly for university students vulnerable to emotional strain. This study aims to identify clusters of student mental health trends using the K-Means…
Means clustering technique. The research involved 60 students from four academic programs at the Faculty of Science and Technology, selected using stratified and cluster sampling techniques. Data were collected using a modified Mental Health Inventory (MHI). The results revealed distinct commonalities among majors: the Statistics program was predominantly defined by the depressed cluster at 53.3%, while Mathematics followed at 40% within the same cluster. In contrast, Biology students predominantly fell under the neu-tral/stable cluster (66.7%), whilst Information Systems students exhibited an even distribution (33.3% per cluster) without a dominant trend. The clustering quality was evaluated using the Silhouette Coefficient, yielding a range of 0.39 to 0.60. Biology (0.60) and Statistics (0.54) exhibited a reasonable structure, but Information Systems (0.39) and Mathematics (0.34) demonstrated a deficient structure. In conclusion, K-Means effectively discerns mental health patterns, providing a data-driven basis for targeted psychological interventions in educational settings.
Keywords: biology; information systems; k-means; mathematics; mental health; silhouette coefficient; statistics
Abstrak: Kesehatan mental merupakan komponen vital dari kesejahteraan total, terutama bagi maha-siswa yang rentan terhadap stres emosional. Penelitian ini bertujuan untuk mengidentifikasi kelompok tren kesehatan mental mahasiswa melalui penerapan metode pengelompokan K-Means. Studi ini mencakup 60 mahasiswa dari empat program studi di Fakultas Sains dan Teknologi, yang dipilih melalui metode pengambilan sampel bertingkat dan kelompok. Data dikumpulkan dengan menggunakan Inventaris Kesehatan Mental (MHI) yang dimodifikasi. Temuan menunjukkan kesamaan yang jelas di antara jurusan: program studi Statistika terutama ditandai oleh kelompok depresi (53,3%), diikuti oleh Matematika dengan 40% dalam kelompok depresi. Sebaliknya, mahasiswa Biologi terutama termasuk dalam kelompok netral/stabil (66,7%), sedangkan mahasiswa Sistem Informasi memiliki distribusi yang merata (33,3% per kelompok) tanpa pola yang dominan. Kualitas pengelompokan dinilai dengan Koefisien Sil-houette, menghasilkan rentang 0,39 hingga 0,60. Biologi (0,60) dan Statistika (0,54) memiliki struktur sedang, sedangkan Sistem Informasi (0,39) dan Matematika (0,34) menunjukkan struktur yang buruk. Kesimpulannya, K-Means secara akurat mengidentifikasi tren kesehatan mental, menawarkan landasan berbasis data untuk terapi psikologis yang ditargetkan di ling-kungan pendidikan.
Kata kunci: biologi; kesehatan mental; K-Means; matematika; silhouette coefficient; sistem in-formasi; statistika
Abstract:Abstract: Tourism in Pati Regency currently lacks an integrated digital information system, resulting in suboptimal dissemination of information and trip planning. To address this issue, a tourism website for Pati Regency…
y was developed, equipped with a recommended tourist route feature. This study aims to design and develop a web-based tourism information system that provides destination information based on categories, media galleries, and promotional YouTube videos, as well as a Patiways feature that allows users to select multiple tourist destinations. The system then calculates the most efficient visiting order using a greedy heuristic algorithm, based on the selected starting point. The system was developed using the Waterfall method, consisting of analysis, design, implementation, and testing phases. The system design is illustrated through UML diagrams such as Use Case, Activity, and Class Diagrams. With this system, the distribution of tourism information becomes more effective, and tourists can plan trips with optimized routes. Additionally, the website is expected to serve as a digital promotion medium that contributes to increasing tourist visits to Pati Regency.
Keywords: heuristic greedy; recommendation route; tourism; waterfall
Abstrak: Pariwisata di Kabupaten Pati saat ini belum memiliki sistem informasi digital yang terintegrasi, sehingga penyebaran informasi dan perencanaan perjalanan wisata masih belum optimal. Untuk mengatasi permasalahan tersebut, penelitian ini mengembangkan sebuah website pariwisata Kabupaten Pati yang dilengkapi dengan fitur rekomendasi rute wisata terbaik. Penelitian ini bertujuan untuk merancang dan membangun sistem informasi pariwisata berbasis web yang mampu menyajikan informasi destinasi wisata berdasarkan kategori, galeri media, serta video promosi YouTube. Selain itu, sistem ini dilengkapi dengan fitur unggulan bernama Patiways yang memungkinkan pengguna memilih beberapa destinasi wisata dan secara otomatis memperoleh urutan kunjungan paling efisien menggunakan algoritma heuristik greedy berdasarkan titik awal perjalanan. Pengembangan sistem dilakukan menggunakan metode Waterfall yang meliputi tahapan analisis kebutuhan, perancangan sistem, implementasi, dan pengujian. Perancangan sistem direpresentasikan menggunakan diagram UML, meliputi Use Case Diagram, Activity Diagram, dan Class Diagram. Dengan adanya sistem ini, diharapkan penyebaran informasi pariwisata menjadi lebih efektif, wisatawan dapat merencanakan perjalanan dengan rute yang optimal, serta website dapat berfungsi sebagai media promosi digital yang berkontribusi terhadap peningkatan kunjungan wisatawan ke Kabupaten Pati.
Kata kunci: heuristik greedy; pariwisata; rekomendasi rute; waterfall
Abstract:Abstract: Bakery MSMEs in Kisaran City play a significant role in the local economy, but their distribution data is still managed manually, making it difficult to access and analyze. This study aims to develop a WebGIS-based…
ased Geographic Information System to map and manage bakery MSME data digitally and in an integrated manner. The research methods include field surveys, spatial and non-spatial data collection, system design using UML, development with Leaflet.js and MySQL, and testing using the blackbox method. The results show that the resulting system is capable of displaying interactive maps with location details, business information, and an easy-to-use search feature. This system makes it easier for the government, business actors, and the public to access MSME information and supports data-based economic development planning. With the output in the form of publications in accredited journals, this research is expected to be an effective solution for MSME data management in other regions.
Keyword: bakery; mapping; MSME; WebGIS
Abstrak: UMKM toko roti di Kota Kisaran memiliki peran penting dalam perekonomian lokal, namun data persebarannya masih dikelola secara manual sehingga sulit diakses dan dianalisis. Penelitian ini bertujuan mengembangkan Sistem Informasi Geografis berbasis WebGIS untuk memetakan dan mengelola data UMKM toko roti secara digital dan terintegrasi. Metode penelitian meliputi survei lapangan, pengumpulan data spasial dan non-spasial, perancangan sistem menggunakan UML, pengembangan dengan Leaflet.js dan MySQL, serta pengujian menggunakan metode blackbox. Hasil penelitian menunjukkan sistem yang dihasilkan mampu menampilkan peta interaktif dengan detail lokasi, informasi usaha, dan fitur pencarian yang mudah digunakan. Sistem ini mempermudah pemerintah, pelaku usaha, dan masyarakat dalam mengakses informasi UMKM, serta mendukung perencanaan pembangunan ekonomi berbasis data. Dengan luaran berupa publikasi pada jurnal terakreditasi, penelitian ini diharapkan menjadi solusi efektif untuk pengelolaan data UMKM di daerah lain.
Kata kunci; pemetaan; toko roti; UMKM; WebGIS
Abstract:Abstract: Ineffective drug demand management can lead to problems such as imbalanced drug distribution, excess stock, or shortages in community health centers. To address this, data mining can be utilized to support the…
planning and control process of drug inventory. Clustering techniques were chosen because they are able to group drug data based on certain characteristics, thus identifying stable and unstable drug supply patterns. This study aims to group drug data at Simpang Kawat Community Health Center in Jambi City, which can be used as a reference in planning drug needs in the next period. Data grouping is divided into three categories: slow-moving, medium-moving, and fast-moving. The research data includes attributes of drug name, initial stock, receipt, inventory, usage, and final stock, with a total of 1758 data sets, which were processed using the CRISP-DM framework through the RapidMiner application. Cluster quality evaluation was carried out using the Davies-Bouldin Index (DBI). The results showed that the K-Means algorithm obtained a DBI value of 0.175, smaller than K-Medoids which obtained a value of 0.354. Because a smaller DBI value indicates better cluster quality, K-Means provides more optimal clustering results than K-Medoids. Through these clustering results, community health centers can utilize drug cluster information to support more efficient drug procurement planning, as well as reduce the risk of excess or shortage of stock.
Keywords: data mining; clustering; k-means; k-medoids; davies-bouldin index
Abstract:Abstract: The global transition towards sustainable food systems faces significant challenges in vegetarian food supply chains, including transparency issues, distribution inefficiencies, and quality verification problems.…
s. This research proposes VegeChain development, a decentralized marketplace ecosystem based on smart contracts designed to transform vegetarian food supply chains and accelerate Meatless, Balanced, Green (MBG) program adoption. Using mixed-method methodology integrating blockchain system design, stakeholder analysis, and economic simulation, this research develops a comprehensive technology framework combining blockchain transparency, smart contract automation, and sustainable tokenomics with novel mathematical models. The system implements dynamic pricing algorithms based on Automated Market Maker (AMM) mechanisms, multi-objective optimization for supply chain efficiency, and reputation-based consensus protocols. Simulation results demonstrate that VegeChain implementation can improve supply chain efficiency by 35%, reduce food waste by 28%, and increase consumer trust by 42% measured through validated stakeholder satisfaction surveys (n=456) using 5-point Likert scales with statistical significance p<0.001. Technical innovations include Byzantine Fault Tolerant consensus with 99.9% reliability, gas optimization achieving 67% cost reduction, and real-time quality verification algorithms with 98.7% accuracy.
Keywords: smart contracts; supply chain optimization; automated market makers; blockchain technology; sustainable tokenomics
Abstract:Abstract: This study applies an integrated approach to optimize heart failure classification. The main objective is to address the challenge of class imbalance in medical datasets and to improve the accuracy, sensitivity,…
, and generalization of the classification model. The urgency of this issue is emphasized by statistics showing that cardiovascular diseases cause approximately 17.9 million deaths worldwide each year. Using a quantitative experimental approach, this study analyzes the "Heart Failure Prediction Dataset" from Kaggle, which consists of 918 records. The data were processed through normalization and encoding, followed by the application of SMOTE on the training set to balance class distribution. This step successfully increased model accuracy from 88.41% to 90.22% and minority class recall from 0.82 to 0.88. Furthermore, Bayesian Optimization was employed to refine the hyperparameters of SVM, resulting in a final model with an accuracy of 89.13% that demonstrated better generalization. This integrated approach significantly enhances the stability, sensitivity, and generalization of the model, making it a reliable tool for clinical decision support systems in predicting heart failure.
Keywords: bayesian optimization; heart failure; machine learning; SMOTE; SVM.
Abstrak: Penelitian ini menerapkan pendekatan terintegrasi untuk mengoptimalkan klasifikasi gagal jantung. Tujuan utama studi ini adalah untuk mengatasi tantangan ketidakseimbangan kelas dalam dataset medis dan meningkatkan akurasi, sensitivitas, serta generalisasi model klasifikasi. Urgensi ini ditegaskan oleh statistik yang menunjukkan bahwa penyakit kardiovaskular menyebabkan sekitar 17,9 juta kematian setiap tahun secara global. Menggunakan pendekatan eksperimental kuantitatif, penelitian ini menganalisis "Heart Failure Prediction Dataset" dari Kaggle, yang terdiri dari 918 catatan. Data diproses dengan normalisasi dan encoding, lalu SMOTE diterapkan pada data pelatihan untuk menyeimbangkan distribusi kelas. Langkah ini berhasil meningkatkan akurasi dari 88,41% menjadi 90,22% dan recall kelas minoritas dari 0,82 menjadi 0,88. Selanjutnya, Bayesian Optimization menyempurnakan hyperparameter SVM, menghasilkan model akhir dengan akurasi 89,13% yang menunjukkan generalisasi lebih baik. Pendekatan terintegrasi ini secara signifikan meningkatkan stabilitas, sensitivitas, dan generalisasi model. Hasil penelitian ini menjadikannya alat yang andal untuk sistem pendukung keputusan klinis dalam prediksi gagal jantung.
Kata kunci: bayesian optimization; gagal jantung; machine learning; SMOTE; SVM
Abstract:Face recognition has become a common thing used in the field of surveillance and security in computer technology and image devices. This study aims to identify the usefulness of a person's face on 3 test images. This study…
dy examines the methods of cropping techniques, image enhancement through intensity measurement, and histogram analysis to improve the contrast and distribution of image intensity. In addition, the Viola-Jones algorithm is used to detect key facial features such as eyes, nose, and mouth. The results of the analysis are then applied in the feature evaluation stage, where usually between facial features are applied to measure the ratio of facial proportions. Furthermore, the comparison of proportional ratios of several images was analyzed using bar graphs and line graphs to evaluate the trend and stability of facial proportions. The results showed the best ratio stability with a smaller variation of the on-off ratio of image 2 which is 0.4762 pixels to 0.4983 pixels. Image 2 is the most ideal for face measurement systems based on geometric ratios because it provides more consistent and visible results.
Abstract:Abstract: In the retail industry, effective supply chain management is essential to ensure stock availability aligns with market demand. Gasti Jaya Store, a growing shoe retailer, faces challenges in optimizing inventory…
management, often leading to stock surpluses or shortages. These issues can impact operational efficiency and customer satisfaction. To address this problem, this study the implementation of Electronic Supply Chain Management (E-SCM) as a solution to optimize supply chain management. E-SCM enables the integration of technology-based systems for real-time stock monitoring, procurement, and distribution. Using a case study method and a qualitative approach, this research evaluates the effectiveness of E-SCM in enhancing operational efficiency, reducing excess stock, and accelerating the distribution process at Gasti Jaya Store. The findings indicate that E-SCM implementation improves data transparency, speeds up decision-making, and enhances customer satisfaction. Additionally, the system helps reduce operational costs by optimizing inventory management and minimizing the risk of stock imbalances. In conclusion, the adoption of E-SCM can serve as an effective strategy for mid-sized retail businesses to improve their competitiveness and supply chain efficiency.
Keywords: E-SCM; inventory stock; operational efficiency.
Abstrak: Dalam industri ritel, manajemen rantai pasok yang efektif sangat diperlukan untuk memastikan ketersediaan stok sesuai dengan permintaan pasar. Toko Gasti Jaya sebagai salah satu toko sepatu yang berkembang menghadapi tantangan dalam mengelola persediaan secara optimal, yang sering kali menyebabkan kelebihan atau kekurangan stok. Permasalahan ini dapat berdampak pada efisiensi operasional dan kepuasan pelanggan. Untuk mengatasi masalah tersebut, penelitian ini mengusulkan penerapan Electronic Supply Chain Management (E-SCM) sebagai solusi dalam mengoptimalkan manajemen rantai pasok. E-SCM memungkinkan integrasi sistem berbasis teknologi dalam proses pemantauan stok, pengadaan barang, hingga distribusi secara real-time. Dengan metode studi kasus dan pendekatan kualitatif, penelitian ini mengevaluasi efektivitas E-SCM dalam meningkatkan efisiensi operasional, mengurangi kelebihan stok, serta mempercepat proses distribusi di Toko Gasti Jaya. Hasil penelitian menunjukkan bahwa implementasi E-SCM mampu meningkatkan transparansi data, mempercepat pengambilan keputusan, dan meningkatkan kepuasan pelanggan. Selain itu, sistem ini membantu mengurangi biaya operasional dengan mengoptimalkan manajemen persediaan dan meminimalkan risiko ketidakseimbangan stok. Kesimpulannya, penerapan E-SCM dapat menjadi strategi yang efektif bagi bisnis ritel skala menengah untuk meningkatkan daya saing dan efisiensi rantai pasok mereka.
Kata Kunci: E-SCM; efisiensi operasional; persediaan stok.
Abstract:Abstract: The implementation of Geographic Information Systems (GIS) within organizations has become essential in accomplishing work activities in the modern era. Sideak Motor is a financing company in Kisaran City, Asahan…
an Regency, that provides loans using motorcycle registration certificates (BPKB) as collateral, with a customer base reaching 6,052. Sideak Motor faces difficulties in data management. During meetings concerning customer locations, data communication with owners and office staff is often problematic. Additionally, when duties are transferred, new field officers struggle to locate customers because the previous officers could only provide textual information. As a result, office staff have no precise knowledge of customer locations—only the field officers do. This study aims to design a web-based customer mapping system to facilitate information storage, reduce costs, save time, and produce an information system that enhances the efficiency and accuracy of customer data management. The resulting system presents the distribution of customer locations and provides accessible information such as personal data, addresses, route details, and photos of customers’ homes, thereby simplifying the operations of Sideak Motor.
Keywords: customer distribution mapping; geographic information system (GIS); sideak motor.
Abstrak: Penerapan sistem informasi geografis dalam organisasi menjadi hal utama untuk menyelesaikan suatu aktivitas pekerjaan pada era sekarang ini. Sideak Motor merupakan salah satu perusahaan pembiayaan dengan agunan BPKB sepeda motor di Kota Kisaran Kabupaten Asahan yang memiliki nasabah mencapai 6.052, Sideak Motor kesulitan dalam pengelolaan data, saat melakukan rapat mengenai lokasi nasabah sulit dilakukan komunikasi data dengan pemilik dan petugas kantor lainnya, serta pada saat pergantian tugas, petugas lainnya kesulitan mencari lokasi nasabah, karena petugas lapangan hanya bisa memberikan informasi berupa teks, dengan begitu petugas kantor tidak mengetahui lokasi pasti nasabah Sideak Motor, jadi yang mengetahui lokasi mengenai tempat tinggal nasabah hanya petugas lapangan. Penelitian ini memiliki tujuan untuk merancang sebuah sistem pemetaan nasabah berbasis web yang dapat mempermudah dalam penyimpanan informasi, mengurangi biaya, menghemat waktu serta menghasilkan sistem informasi yang dapat meningkatkan efisiensi dan akurasi pengelolaan data nasabah. Hasil sistem ini menyajikan sebaran pemetaan lokasi nasabah menyediakan informasi berupa biodata, alamat, rincian rute, dan gambar rumah nasabah yang dapat diakses secara cepat dan akurat sehingga dapat mempermudah pihak sideak motor.
Kata Kunci: pemetaan sebaran nasabah; sistem informasi geografis (SIG); sideak motor
Abstract:Abstract: The rapid population growth in Tanjung Tiram District, primarily driven by increased in-migration, demands an accurate forecasting system to support effective and sustainable development planning. This study aims…
ms to predict population growth in Tanjung Tiram District in 2024 using the Least Square method. The analysis covers birth, arrival, and migration data from 2019 to 2023. The results show that the Least Square method successfully predicts 936 births, 104 arrivals, and 142 migrations in 2024, with a very low error rate: MAPE for births is 0.01%, arrivals 0.12%, and migrations 0.04%. These research demonstrate that the Least Square method can effectively support data-driven development policies and improve the accuracy of public service distribution planning.
Keywords: forecasting; least square method; population growth; tanjung tiram.
Abstrak: Pertumbuhan penduduk yang pesat di Kecamatan Tanjung Tiram, terutama akibat peningkatan migrasi masuk, menuntut adanya sistem prediksi yang akurat untuk mendukung perencanaan pembangunan yang efektif dan berkelanjutan. Penelitian ini bertujuan untuk memprediksi pertumbuhan penduduk di Kecamatan Tanjung Tiram pada tahun 2024 menggunakan pendekatan metode Least Square. Data yang dianalisis mencakup jumlah kelahiran, kedatangan, dan perpindahan penduduk dari tahun 2019 hingga 2023. Hasil penelitian menunjukkan bahwa metode Least Square mampu memprediksi jumlah kelahiran sebesar 936 jiwa, kedatangan 104 jiwa, dan perpindahan 142 jiwa pada tahun 2024, dengan tingkat kesalahan yang sangat rendah: MAPE untuk kelahiran sebesar 0,01%, kedatangan 0,12%, dan perpindahan 0,04%. Penelitian ini membuktikan bahwa metode Least Square dapat digunakan secara efektif untuk mendukung penyusunan kebijakan pembangunan yang berbasis data dan memperkuat akurasi distribusi layanan publik.
Kata kunci: metode least square; peramalan; pertumbuhan penduduk; tanjung tiram.