Abstract:Abstract: Unpredictable weather changes often become a problem in the process of drying clothes, especially when it rains suddenly. This condition can cause clothes to get wet again by reducing the efficiency of time and…
energy. Therefore, this study aims to design and implement a prototype of an automatic clothesline based on the Internet of Things with an ESP32 microcontroller and an LDR sensor as a weather condition detector based on light intensity. The research methods used in this study include hardware and software design, system assembly, and testing the device's performance in various environmental conditions. The LDR sensor is used to read changes in light intensity, then the data is processed by the ESP32 to control the stepper motor as a driver for the automatic opening and closing mechanism of the clothesline. The results of the study show that all system components, including the LDR sensor, ESP32 microcontroller, stepper motor, buzzer, and power supply can work in an integrated and stable manner. This system has a 100% success rate with an average response time of around ±1 second, so it is able to respond to changes in environmental conditions quickly and effectively.
Keywords: Prototype, Automatic clothesline, ESP32, LDR
Abstrak: Perubahan cuaca yang tidak menentu sering menjadi permasalahan dalam proses penjemuran pakaian, khususnya ketika hujan turun secara tiba-tiba. Kondisi tersebut dapat menyebabkan pakaian kembali basah dengan menurunkan efisiensi waktu serta tenaga. Oleh karena itu, penelitian ini bertujuan untuk merancang dan mengimplementasikan prototype jemuran pakaian otomatis berbasis Internet Of Things dengan mikrokontroller ESP32 serta sensor LDR sebagai pendeteksi kondisi cuaca berdasarkan intensitas cahaya. Metode penelitian yang digunakan dalam penelitian ini meliputi perancangan perangkat keras dan perangkat lunak, perakitan sistem, serta pengujian kinerja alat di berbagai kondisi lingkungan. Sensor LDR digunakan untuk membaca perubahan intensitas cahaya, kemudian data di proses oleh ESP32 untuk mengendalikan motor stepper sebagai penggerak mekanisme buka dan tutup jemuran secara otomatis. Hasil penelitian menunjukkan bahwa seluruh komponen sistem, meliputi sensor LDR, mikrokontroller ESP32, motor stepper, buzzer, dan catu daya dapat bekerja secara integrasi dan juga secara stabil. Sistem ini memiliki tingkat keberhasilan 100% dengan rata-rata waktu respon sekitar ±1 detik, sehingga mampu merespon perubahan kondisi lingkungan dengan cepat dan efektif.
Kata kunci: Prototype, Automatic clothesline, ESP32, LDR
Abstract:Abstract: The rapid expansion of online and blended learning requires assessment systems that can comprehensively measure the cognitive, affective, and psychomotor (CAP) domains in an objective and well-documented manner.…
. Recent studies show that online CAP assessments are often conducted separately, manually, or focused on only one domain, making it difficult for teachers and lecturers to monitor student progress and report learning outcomes 1273+3 MORE. This study aims to develop a web-based prototype application for learning assessment using PHP and MySQL, supporting integrated CAP assessment and automatic report generation. A prototype method was employed, including needs analysis, system design (use cases, process flow, and conceptual ERD), interface and database development, and initial functional testing in a classroom assessment scenario. The resulting system provides user authentication, student data management, configuration of CAP instruments and weightings, per-domain score input, and summarized reports per student and per class. Functional testing indicates that the main workflows (login, score input, processing, and report printing) operate as intended and conceptually address issues of redundancy, data loss risk, and limited documentation common in manual assessments. It is concluded that this prototype is a feasible foundation for further development toward an integrated CAP assessment system aligned with online and project-based learning practices.
Keywords: Learning Assessment, Cognitive Affective Psychomotor Domains, Web-Based System, PHP, MySQL.
Abstrak: Transformasi pembelajaran menuju moda daring dan campuran menuntut sistem assessment yang mampu mengukur secara terpadu ranah kognitif, afektif, dan psikomotorik (KAP) secara objektif dan terdokumentasi. Berbagai penelitian menunjukkan bahwa penilaian KAP secara online masih banyak dilakukan secara terpisah, manual, atau hanya berfokus pada salah satu ranah, sehingga menyulitkan dosen/guru dalam pemantauan kemajuan belajar dan pelaporan hasil belajar 1234+2 MORE. Penelitian ini bertujuan mengembangkan prototipe aplikasi sistem assessment pembelajaran berbasis web menggunakan PHP dan MySQL yang memfasilitasi penilaian terintegrasi tiga ranah KAP serta penyajian laporan nilai secara otomatis. Metode yang digunakan adalah metode prototype dengan tahapan analisis kebutuhan, perancangan (use case, flow proses, dan ERD konseptual), pengembangan antarmuka dan basis data, serta uji fungsional awal pada skenario penilaian kelas. Sistem yang dihasilkan menyediakan fitur otentikasi pengguna, pengelolaan data peserta didik, pengaturan instrumen dan bobot penilaian KAP, input nilai per ranah, serta laporan rekap nilai per siswa dan per kelas. Hasil uji fungsional menunjukkan seluruh alur utama (login, input nilai, pengolahan, dan cetak laporan) berjalan sesuai skenario, dan secara konseptual menjawab permasalahan redundansi, risiko kehilangan data, dan keterbatasan dokumentasi pada penilaian manual. Disimpulkan bahwa prototipe ini layak sebagai dasar pengembangan lebih lanjut menuju sistem assessment KAP yang terintegrasi dengan praktik pembelajaran daring dan berbasis proyek.
Kata Kunci: Assessment Pembelajaran, Ranah Kognitif Afektif Psikomotorik, Sistem Berbasis Web, PHP, MySQL
Abstract:Unequal distribution of contraceptive supplies (Alokon) relative to the target population remains a persistent challenge in family planning programs, particularly in regions with high demographic heterogeneity. Evaluation…
n based on absolute distribution values generates proportional bias, as larger-population areas automatically receive higher volumes without accounting for the proportional needs of the Reproductive Age Couples (PUS) population. This study proposes a ratio-based approach — dividing total Alokon distributed by the number of PUS — as the primary clustering variable to enable proportional comparison and reduce population-scale bias across 33 districts and cities in North Sumatra Province. Two algorithms, K-Means and K-Medoids based on Partitioning Around Medoids (PAM), were comparatively evaluated using Silhouette Score as the evaluation metric. The optimal number of clusters (K = 3) was determined through a combination of the Elbow Method — which identified a 75.12% WCSS reduction from K = 2 to K = 3 — and Silhouette Score validation. Results show that both algorithms produced identical cluster compositions: 16 districts in the low-distribution group (48.5%; = 0.1687), 13 districts in the moderate group (39.4%; = 0.3117), and 4 districts in the high group (12.1%; = 0.6077), with equal average Silhouette Scores of = 0.6998 (reasonable structure). Densely populated areas such as Medan City and Deli Serdang — despite receiving the highest absolute distribution volumes — were classified in the low group when measured proportionally, demonstrating the superiority of the ratio-based approach. To the best of the authors' knowledge, this study is the first to apply comparative clustering on Alokon distribution using a proportional ratio framework in North Sumatra Province, providing empirical evidence on algorithm performance in normalized health service distribution data.
Abstract:Abstract: This study aims to analyze the Service Quality strategy as a fundamental instrument in creating customer satisfaction and loyalty in the digital economy ecosystem. Amidst increasingly homogeneous e-commerce platform…
tform competition, service quality is transforming into a key differentiating factor that determines business sustainability. This study focuses on the dynamics of user interactions on the Shopee Indonesia platform, by examining how the dimensions of E-Service Quality influence future consumer behavior. The method used in this study is a quantitative approach with a causal associative design. Data were collected through the distribution of online questionnaires to 150 respondents who are active Shopee users in the productive age range (18–35 years) using a purposive sampling technique. Data analysis was conducted using the Path Analysis technique to test the direct and indirect effects between variables with the help of statistical software. The results show that the dimensions of E-Service Quality, specifically system efficiency, service promise fulfillment, and data security (privacy), have a positive and significant effect on customer satisfaction. Furthermore, it was found that customer satisfaction plays a role as a perfect mediation variable (full mediation) in linking service quality with customer loyalty. These findings confirm that high technical quality does not automatically create loyalty without an emotionally satisfying user experience. The managerial implications of this study suggest that Shopee must continue to synchronize system performance stability with customer service response speed, especially during peak transaction periods. Investing in data-driven service personalization is a strategic imperative to strengthen emotional bonds and user trust, in order to maintain market dominance amidst the dynamic digital industry landscape Shopee in Indonesia.
Keywords: Service Quality, E-Service Quality, Customer Satisfaction, Customer Loyalty, Shopee, Digital Economy
Abstrak: Penelitian ini bertujuan untuk menganalisis strategi Service Quality (Kualitas Pelayanan) sebagai instrumen fundamental dalam menciptakan kepuasan dan loyalitas pelanggan pada ekosistem ekonomi digital. Di tengah persaingan platform e-commerce yang semakin homogen, kualitas layanan bertransformasi menjadi faktor diferensiasi utama yang menentukan keberlangsungan bisnis. Penelitian ini berfokus pada dinamika interaksi pengguna pada platform Shopee Indonesia, dengan menelaah bagaimana dimensi-dimensi E-Service Quality memengaruhi perilaku konsumen di masa depan. Metode yang digunakan dalam penelitian ini adalah pendekatan kuantitatif dengan desain asosiatif kausal. Data dikumpulkan melalui penyebaran kuesioner daring kepada 150 responden yang merupakan pengguna aktif Shopee pada rentang usia produktif (18–35 tahun) dengan teknik purposive sampling. Analisis data dilakukan menggunakan teknik Path Analysis (Analisis Jalur) untuk menguji pengaruh langsung maupun tidak langsung antar variabel dengan bantuan perangkat lunak statistik. Hasil penelitian menunjukkan bahwa dimensi E-Service Quality, khususnya efisiensi sistem, pemenuhan janji layanan (fulfillment), dan keamanan data (privacy), berpengaruh positif dan signifikan terhadap kepuasan pelanggan. Lebih lanjut, ditemukan bahwa kepuasan pelanggan menjalankan peran sebagai variabel mediasi yang sempurna (full mediation) dalam menghubungkan kualitas pelayanan dengan loyalitas pelanggan. Temuan ini menegaskan bahwa kualitas teknis yang tinggi tidak secara otomatis menciptakan loyalitas tanpa adanya pengalaman pengguna yang memuaskan secara emosional. Implikasi manajerial dari penelitian ini menyarankan bahwa Shopee harus terus melakukan sinkronisasi antara stabilitas performa sistem dengan kecepatan respons layanan pelanggan, terutama pada masa puncak transaksi (peak season). Investasi pada personalisasi layanan berbasis data menjadi urgensi strategis untuk memperkuat ikatan emosional dan kepercayaan pengguna, guna mempertahankan dominasi pasar di tengah dinamisnya lanskap industri digital Shoppe di Indonesia.
Kata Kunci: Service Quality, E-Service Quality, Kepuasan Pelanggan, Loyalitas Pelanggan, Shopee, Ekonomi Digital
Abstract:Abstract: This research aims to design and implement a web-based Optical Line Terminal (OLT) network monitoring system to detect congestion in real-time on Gigabit Passive Optical Network (GPON) architecture. The main problem…
oblem in GPON networks is the increase in customer traffic which causes bandwidth bottlenecks and decreases Quality of Service (QoS). The research methodology includes analysis of OLT performance parameters (throughput, utilization, packet loss, latency), design of a system architecture based on SNMP and REST API, development of a monitoring dashboard using a web framework, and testing in an operational network environment. The developed system is able to display PON port status, bandwidth utilization level, and automatic notification when the congestion threshold is exceeded. The test results show that the system can detect an increase in utilization above 80% with a response time of less than 5 seconds. The implementation of this system increases the effectiveness of network monitoring and speeds up the troubleshooting process by administrators.
Keywords: Network Monitoring; OLT; GPON; Congestion; Real-Time.
Abstrak: Penelitian ini bertujuan merancang dan mengimplementasikan sistem monitoring jaringan Optical Line Terminal (OLT) berbasis web untuk mendeteksi congestion secara real-time pada arsitektur Gigabit Passive Optical Network (GPON). Permasalahan utama pada jaringan GPON adalah meningkatnya trafik pelanggan yang menyebabkan bottleneck bandwidth dan penurunan Quality of Service (QoS). Metodologi penelitian meliputi analisis parameter performa OLT (throughput, utilization, packet loss, latency), perancangan arsitektur sistem berbasis SNMP dan REST API, pengembangan dashboard monitoring menggunakan framework web, serta pengujian pada lingkungan jaringan operasional. Sistem yang dikembangkan mampu menampilkan status port PON, tingkat utilisasi bandwidth, dan notifikasi otomatis ketika threshold congestion terlampaui. Hasil pengujian menunjukkan bahwa sistem dapat mendeteksi kenaikan utilisasi di atas 80% dengan waktu respons kurang dari 5 detik. Implementasi sistem ini meningkatkan efektivitas monitoring jaringan serta mempercepat proses troubleshooting oleh administrator.
Kata Kunci: Monitoring Jaringan; OLT; GPON; Congestion; Real-Time.
Abstract:Abstract: The development of digital technology has driven the transformation of educational services through the implementation of data-based learning systems and smart devices. One of the emerging approaches is the use…
of the Internet of Things (IoT) in building smart classrooms, which are classrooms capable of integrating physical devices, sensors, and information systems to improve learning efficiency and learning environment management. This study aims to analyze the implementation of IoT in the formation of smart classrooms, covering aspects of system design, device integration, and evaluation of its effectiveness in supporting the teaching and learning process. The research method used is a quantitative and experimental approach, by designing an IoT-based smart classroom prototype that integrates temperature, humidity, light intensity, and presence detection sensors, as well as device control such as lights, air conditioning, and projectors through an automatic system and remote control. Data was collected through device performance measurements, network stability tests, and questionnaires distributed to users (teachers and students) to assess the system's ease of use and usefulness. The results showed that the implementation of IoT in classrooms can improve the efficiency of facility management through device automation, facilitate real-time monitoring of classroom conditions, and provide a more comfortable and responsive learning environment. In addition, the developed system demonstrated stable data communication performance with low latency within acceptable operational limits. These findings indicate that the application of IoT in smart classrooms has the potential to contribute significantly to improving the quality of learning and classroom management, particularly in supporting a technology-based education ecosystem. This study recommends further development in the areas of data security, device interoperability, and integration with Learning Management Systems (LMS) to strengthen the sustainable implementation of smart classrooms.
Keywords: Internet of Things, Smart Classroom, Classroom Automation, Sensors, Technology Based Education.
Abstrak: Perkembangan teknologi digital mendorong transformasi layanan pendidikan melalui penerapan sistem pembelajaran berbasis data dan perangkat cerdas. Salah satu pendekatan yang berkembang adalah pemanfaatan Internet of Things (IoT) dalam membangun smart classroom, yaitu ruang kelas yang mampu mengintegrasikan perangkat fisik, sensor, serta sistem informasi untuk meningkatkan efisiensi pembelajaran dan pengelolaan lingkungan belajar. Penelitian ini bertujuan untuk menganalisis implementasi IoT dalam pembentukan smart classroom, mencakup aspek desain sistem, integrasi perangkat, serta evaluasi efektivitasnya dalam mendukung proses belajar mengajar. Metode penelitian yang digunakan adalah pendekatan kuantitatif dan eksperimental, dengan merancang prototipe smart classroom berbasis IoT yang mengintegrasikan sensor suhu, kelembapan, intensitas cahaya, deteksi kehadiran, serta pengendalian perangkat seperti lampu, pendingin ruangan, dan proyektor melalui sistem otomatis maupun kendali jarak jauh. Data dikumpulkan melalui pengukuran kinerja perangkat, uji stabilitas jaringan, serta penyebaran kuesioner kepada pengguna (guru dan siswa) untuk menilai tingkat kemudahan penggunaan dan kebermanfaatan sistem. Hasil penelitian menunjukkan bahwa implementasi IoT pada ruang kelas mampu meningkatkan efisiensi pengelolaan fasilitas melalui otomasi perangkat, mempermudah monitoring kondisi kelas secara real-time, serta memberikan dukungan lingkungan belajar yang lebih nyaman dan responsif. Selain itu, sistem yang dikembangkan menunjukkan performa komunikasi data yang stabil dengan tingkat keterlambatan (latency) yang rendah dalam batas operasional yang dapat diterima. Temuan ini mengindikasikan bahwa penerapan IoT dalam smart classroom berpotensi memberikan kontribusi signifikan terhadap peningkatan kualitas pembelajaran dan manajemen kelas, khususnya dalam mendukung ekosistem pendidikan berbasis teknologi. Penelitian ini merekomendasikan pengembangan lanjutan pada aspek keamanan data, interoperabilitas perangkat, serta integrasi dengan Learning Management System (LMS) untuk memperkuat implementasi smart classroom secara berkelanjutan.
Kata Kunci: Internet Of Things, Smart Classroom, Otomasi Ruang Kelas, Sensor, Pendidikan Berbasis Teknologi.
Abstract:Abstract: This study aims to create an information system for registering Munaqasyah or Colloquium hearings by combining Cloud computing and Artificial Intelligence (AI) technologies based on a decision support system. In…
n this study, AI is used to select thesis research fields in order to recommend examiners who are suitable for the students' research topics and to schedule student munaqasyah hearings in a structured and automated manner. Cloud computing is useful for storing all examination requirements, minutes, etc. on a cloud platform that supports the process in real time. The system was developed using a phased Cloud-AI approach, namely planning, design, implementation, testing, and evaluation repeatedly. This system was created using a web platform and combines students' final assignments and lecturers' expertise as a basis for decision making. The research results show that this system can support more efficient examination registration and provide accurate recommendations for examiners and automatic scheduling. With the integration of Cloud-AI in this system, academic administration management can be more effective, and services for students and the management of munaqasyah examinations in the Computer Science study program can be improved.
Keyword: Waterfall Development, Artificial Intelligence, Decision Support System, Munaqasyah Examination, Final Project..
Abstrak: Penelitian ini bertujuan membuat sistem informasi untuk pendaftaran sidang Munaqasyah atau Kolokium dengan menggabungkan teknologi Cloud computing dan Artificial Intelligence (AI) yang sederhana berdasarkan sistem pendukung keputusan. Pada penelitian ini, AI digunakan dengan cara memilih bidang penelitian skripsi agar bisa memberi rekomendasi dosen penguji yang sesuai dengan topik penelitian mahasiswa dan penjadwalan sidang munaqasyah mahasiswa secara terstruktur dan otomatis. Cloud computing berguna untuk penyimpanan semua dokumen syarat sidang, berita acara, dll pada platform cloud yang menunjang proses secara realtime. Pengembangan sistem dilakukan dengan pendekatan Cloud-AI yang bertahap, yaitu perencanaan, desain, implementasi, pengujian, dan evaluasi secara berulang. Sistem ini dibuat menggunakan platform web dan menggabungkan bidang tugas akhir mahasiswa serta keahlian dosen sebagai dasar untuk mengambil keputusan. Hasil penelitian menunjukkan bahwa sistem ini bisa mendukung pendaftaran sidang lebih efisien serta memberi rekomendasi dosen penguji yang tepat dan akurat dan penjadwalan secara otomatis. Dengan adanya integrasi Cloud-AI dalam sistem ini, maka pengelolaan administrasi akademik bisa lebih efektif, dan pelayanan bagi mahasiswa serta pengelolaan sidang munaqasyah di prodi Ilmu Komputer dapat meningkat.
Kata kunci: Waterfall Development, Artificial Intelligence, Decision Support System, Sidang Munaqasyah, Tugas Akhir.
Abstract:Abstract: The development of information technology enables counseling services to be conducted online. One of the challenges in counseling is the manual process of completing and analyzing the Problem Disclosure Tool (AUM),…
UM), which is time-consuming and prone to error. This study aims to develop a web-based AUM system that improves efficiency for both counselors and clients. The system was developed using the Waterfall Model, consisting of requirement analysis, system design, implementation, testing, and maintenance stages. PHP programming language with the CodeIgniter 4 framework and MySQL database were utilized. The results indicate that the system can automatically process AUM results, generate digital reports, and provide online counseling scheduling features. Black box testing confirmed that all key functions performed correctly. This web-based application is expected to enhance efficiency and accuracy in digital counseling services.
Keywords: problem disclosure tool, counseling service, web-based system, CodeIgniter, waterfall
Abstrak: Perkembangan teknologi informasi memungkinkan proses konseling dilaksanakan secara daring. Salah satu kendala dalam layanan konseling adalah proses pengisian dan pengolahan instrumen asesmen seperti Alat Ungkap Masalah (AUM) yang masih dilakukan secara manual dan memakan waktu lama. Penelitian ini bertujuan untuk mengembangkan sistem AUM berbasis web yang dapat digunakan oleh konselor dan konseli secara efisien. Metode pengembangan yang digunakan adalah Waterfall Model, meliputi tahap analisis kebutuhan, desain sistem, implementasi, pengujian, dan pemeliharaan. Sistem dikembangkan menggunakan bahasa pemrograman PHP dengan framework CodeIgniter 4 dan basis data MySQL. Hasil penelitian menunjukkan bahwa sistem mampu memproses hasil AUM secara otomatis, menampilkan laporan dalam bentuk digital, serta menyediakan fitur penjadwalan konseling secara daring. Pengujian menggunakan black box testing menunjukkan seluruh fungsi utama berjalan sesuai harapan. Implementasi sistem ini diharapkan dapat meningkatkan efisiensi dan akurasi dalam layanan konseling berbasis teknologi.
Kata kunci: alat ungkap masalah, layanan konseling, sistem berbasis web, CodeIgniter, waterfall
Abstract:Abstract: Glass is a material that is widely used in various fields, such as construction, the automotive industry, and household appliances. Each type of glass has different characteristics based on its chemical composition…
tion and production process. Problems arise when the process of identifying glass types is still done manually, which is time-consuming, costly, and prone to error. This study aims to apply the K-Nearest Neighbor (K-NN) method in classifying glass types based on their chemical content attributes. The data in this study was sourced from Kaggle, namely the Glass Identification Dataset. The data used consisted of several chemical features, such as Na, Mg, Al, Si, K, Ca, Ba, and Fe, with seven categories of glass classes. The results showed that the K-NN method was able to classify glass types well and could be an effective solution to assist in the automatic glass identification process.
Keyword: Classification, K-Nearest Neighbor, Data Mining, Types of Glass.
Abstrak: Kaca merupakan material yang banyak digunakan dalam berbagai bidang, seperti konstruksi, industri otomotif, dan peralatan rumah tangga. Setiap jenis kaca memiliki karakteristik yang berbeda berdasarkan komposisi kimia dan proses produksinya. Permasalahan muncul ketika proses identifikasi jenis kaca masih dilakukan secara manual, sehingga membutuhkan waktu, biaya, dan berpotensi menimbulkan kesalahan. Penelitian ini bertujuan untuk menerapkan metode K-Nearest Neighbor (K-NN) dalam mengklasifikasikan jenis kaca berdasarkan atribut kandungan kimianya. Data dalam penelitian ini bersumber dari Kaggle, yaitu Glass Identification Dataset. Data yang digunakan terdiri dari beberapa fitur kimia, seperti Na, Mg, Al, Si, K, Ca, Ba, dan Fe, dengan tujuh kategori kelas kaca. Hasil penelitian menunjukkan bahwa metode KNN mampu mengklasifikasikan jenis kaca dengan baik dan dapat menjadi solusi yang efektif untuk membantu proses identifikasi kaca secara otomatis.
Kata kunci: Klasifikasi, K-Nearest Neighbor, Data Mining, Jenis Kaca.
Abstract:Abstract: This study aims to apply the K-Means algorithm for food product segmentation on the GoFood service based on price and rating variables. The large variety of available products makes data difficult to analyze without…
thout systematic grouping, necessitating a method capable of automatically clustering data so that patterns and characteristics become clearer. The K-Means algorithm was chosen for its simple, fast, and effective computational process in dividing data based on distance similarity. The research process includes collecting public datasets, determining the number of clusters, selecting initial centroids, calculating distances using Euclidean Distance, grouping data to the nearest cluster, and iteratively updating centroids until convergence is achieved. Results show that K-Means successfully grouped data into three clusters: Cluster 1 with high price and high rating, Cluster 2 with moderate price and highest rating, and Cluster 3 with low price and very high rating. This study produced a web-based system that automatically processes data and displays clustering results in an easily understandable interface.
Keywords: K-Means, Clustering, Segmentation, GoFood, Data Mining
Abstrak: Penelitian ini bertujuan menerapkan algoritma K-Means untuk segmentasi produk makanan pada layanan GoFood berdasarkan variabel harga dan rating. Banyaknya variasi produk menyebabkan data sulit dianalisis tanpa pengelompokan sistematis, sehingga diperlukan metode yang mampu mengelompokkan data secara otomatis agar pola dan karakteristik terlihat lebih jelas. Algoritma K-Means dipilih karena memiliki proses perhitungan yang sederhana, cepat, dan efektif dalam membagi data berdasarkan tingkat kemiripan jarak. Proses penelitian meliputi pengumpulan dataset publik, penentuan jumlah cluster, pemilihan centroid awal, perhitungan jarak menggunakan Euclidean Distance, pengelompokan data ke cluster terdekat, hingga pembaruan centroid secara iteratif sampai kondisi konvergen tercapai. Hasil penelitian menunjukkan K-Means berhasil mengelompokkan data ke dalam tiga cluster: Cluster 1 dengan harga tinggi dan rating tinggi, Cluster 2 dengan harga sedang dan rating tertinggi, serta Cluster 3 dengan harga rendah dan rating sangat tinggi. Penelitian ini menghasilkan sistem berbasis web yang mengolah data secara otomatis dan menampilkan hasil clustering dalam tampilan mudah dipahami.
Kata kunci: K-Means, Clustering, Segmentasi, GoFood, Data Mining