Abstract: Abstract: Student attendance is one of the activities carried out in the lecture process. Attendance is also an element of a student's final grade for each course offered in accordance with a university's academic guidelines.…
idelines. Attendance at STMIK Amik Riau is done manually, where students are called one by one and then the lecturer changes the attendance data in SIMDOS. This method is of course very inefficient, and takes a long time. Apart from that, this manual process is prone to fraud where students can make absences. Therefore, this research proposes a QR-Code based student attendance mobile application prototype at STMIK Amik Riau using the User Centered Design (UCD) method. The results of the research are in the form of a prototype or user interface design for the student attendance mobile application. It is hoped that this prototype can help programmers to build QR-Code based student attendance mobile applications.
Keywords: Presence, QR-Code, User Interface, User Centered Design
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Abstrak: Kehadiran atau presensi mahasiswa merupakan salah satu kegiatan yang dilakukan dalam proses perkuliahan. Presensi juga merupakan salah satu elemen nilai akhir mahasiswa setiap mata kuliah yang ditawarkan sesuai dengan panduan akademik suatu perguruan tinggi. Presensi di STMIK Amik Riau dilakukan secara manual, dimana mahasiswa dipanggil satu per satu lalu dosen merubah data presensi yang ada pada SIMDOS. Cara ini tentunya sangat tidak efisien, dan membutuhkan waktu yang lama. Selain itu proses manual ini rentan terjadi kecurangan dimana mahasiswa dapat melakukan titip absen. Oleh karena itu penelitian ini mengusulkan prototype aplikasi mobile presensi mahasiswa berbasis QR-Code di STMIK Amik Riau menggunakan metode User Centered Design (UCD). Hasil dari penelitian berupa prototype atau rancangan user interface aplikasi mobile presensi mahasiswa. Diharapkan prototype ini dapat membantu programmer untuk membangun aplikasi mobile presensi mahasiswa berbasis QR-Code.
Kata kunci: Presensi, QR-Code, User Interface, User Centered Design
Abstract:Abstract: Stunting is one of the nutritional problems that the world pays the most attention to and a major nutritional problem in Indonesia. Stunting is a problem in toddler growth which is characterized by a toddler's…
height that is too short compared to toddlers of his age. In the research location, namely Asahan Regency, the mapping of areas prone to increased stunting rates has not been carried out optimally. The process of exploring the stunting data warehouse is useful for adding information that can assist the government in making policies. Therefore, the aim of this research is to map stunting-prone areas in Asahan district based on the number of stunting cases in Asahan district using the machine learning-based K-Means clustering model. Based on previous research reviews, the k-means clustering method used has not used the normalization process. In addition, distance measurement only uses Euclidean Distance. Meanwhile, in this research, clustering performance analysis was carried out using a more in-depth process, namely by applying data normalization at the beginning, using the elbow method to determine the best number of clusters (K), measuring distance using Euclidean Distance, Manhattan Distance and Minkowski Distance to obtain comparison results. better clusters. The analysis results show that the best number of clusters is cluster 2 which shows the mapping results into 2 groups with a DBI of 0.51290 and a silhouette_score of 0.71432.
Keywords: stunting; k-means clustering; machine learning
Abstrak: Stunting menjadi salah satu permasalahan gizi yang paling diperhatikan dunia dan permasalahan gizi yang utama di Indonesia. Stunting merupakan masalah pada pertumbuhan balita yang ditandai dengan tinggi badan balita yang terlalu pendek dibanding balita seusianya. Pada lokasi penelitian yaitu Kabupaten Asahan, pemetaan daerah rawan peningkatan angka stunting belum dilakukan dengan optimal. Proses eksplorasi gudang data stunting ini berguna untuk menambah informasi yang dapat membantu pemerintah dalam mengambil kebijakan. Maka dari itu, tujuan dari penelitian ini adalah pemetaan daerah rawan stunting di kabupaten Asahan berdasarkan jumlah kasus stunting di Kabupaten Asahan menggunakan model clustering metode K-Means berbasis machine learning. Berdasarkan tinjauan penelitian terdahulu, metode k-means clustering yang digunakan belum menggunakan proses normalisasi. Selain itu, pengukuran jarak hanya menggunakan Euclidean Distance. Sedangkan dalam penelitian ini, analisis kinerja clustering yang dilakukan dengan proses yang lebih mendalam yaitu dengan penerapan normalisasi data di awal, penggunaan elbow method untuk penentuan jumlah cluster (K) terbaik, pengukuran jarak dengan Euclidean Distance, Manhattan Distance dan Minkowski Distance untuk mendapatkan hasil perbandingan cluster yang lebih baik. Hasil analisis menunjukkan bahwa jumlah cluster terbaik yaitu cluster 2 yang menunjukkan hasil pemetaan menjadi 2 kelompok dengan DBI 0.51290 dan silhouette_score sebesar 0.71432.
Kata kunci: stunting; k-means clustering; machine learning
Abstract:Abstract: Flood disasters often occur in areas with certain geographical conditions, such as proximity to rivers, high rainfall especially during the wetseason and soil types that contain clay so that they are not good enough…
nough to absorb water. One of the cities in Indonesia whichhas frequent floods. The planned mitigation strategy must be more targeted so that it is more effective in tackling flood disasters. Therefore, mapping with Geographic Information Systems can be used to map areas that are prone to flooding specifically by combining spatial data on each predetermined parameter. Not only that, the integration of Geographic Information Systems and forecasting with multiple linear regression methods can predict the level of flood vulnerability based on the parameters determined in the following year. Based on the analysis that has been done, the areas in Pontianak City that are prone to flood disasters are spread over several sub-districts, namely East Pontianak District, Pontianak City District and parts of North Pontianak District.
Keywords: Flood vulnerability; Geographic Information System; Multiple Linear Regression
Abstrak: Bencana banjir seringkali terjadi di wilayah dengan kondisi geografis tertentu sepertijaraknya yang dekat dengan sungai, curah hujan cukup tinggi khususnya pada musim hujan hingga mayoritas jenis tanah yang memiliki kandungan lempung sehingga tidak cukup baikdalam menyerap air. Kota Pontianak merupakan satu diantara kota di Indonesia yang sering dilanda bencana banjir. Oleh karena itu, pemetaan dengan Sistem Informasi Geografis dapat digunakan untuk memetakan wilayah-wilayah yang rawan bencana banjir secara spesifik dengan menggabungkan data spasial pada setiap parameter yang sudah ditentukan. Tidak hanya itu, integrasi sistem informasi geografis dan peramalan dengan metoderegresi linier berganda dapatmemprediksi tingkat kerawanan banjir berdasarkan parameter yang ditentukan pada tahun berikutnya. Berdasarkan analisis yang telah dilakukan, daerah di Kota Pontianak yang rawan bencanabanjir tersebar di beberapa kecamatan yaitu Kecamatan Pontianak Timur, Kecamatan Pontianak Kota dan sebagianKecamatan Pontianak Utara.
Kata kunci: Kerawanan Banjir; Regresi Linier Berganda; Sistem Informasi Geografis
Abstract:Many mechanical systems with elastic and damping properties are prone to resonant phenomena at natural frequencies under the action of external forces. Resonance phenomena can also be preserved in control systems of such…
objects closed by negative feedback, which reduces the quality of the functioning of these systems. The paper under review deals with the practically important problem of suppressing oscillations at natural frequencies in control systems for a linear oscillator, which is traditionally considered a dynamic object described by a second-order differential equation with complex roots of the characteristic equation. The focus of the work is the question of the roughness of the system in relation to inaccurate knowledge of the resonant frequency of the controlled object (which is typical for many technical applications).
Abstract:This research aims to identify flood-prone areas in West Sumatra Province using remote sensing data and Machine Learning-based Geographic Information System. By utilizing variables such as distance from the river, Normalized…
ized Difference Water Index (NDWI), elevation, Topographic Position Index (TPI), Normalized Difference Vegetation Index (NDVI), and Rainfall Data, this research was conducted on the Google Earth Engine platform. This analysis method supports resource optimization, public education, increased environmental safety, and the development of new technologies and research. The results of the research are expected to assist in mitigation and adaptation to future flood disasters, as well as provide more accurate and comprehensive insights for local governments, disaster management agencies, and communities. With this approach, it is expected to reduce flood risk and increase community resilience to natural disasters.
Abstract:Masamba and Baebunta District which are located in North Luwu Regency are disaster-prone areas and have a high potential for natural disasters. On July 13 2020, there was a flash flood which damaged infrastructure, public…
c facilities and caused casualties. Until now, the government is still continuing to make improvements. The results of the study indicate that the Management of Infrastructure Development in Masamba District, North Luwu Regency is still experiencing problems. This is due to a lack of estimate regional expenditure revenue-APBD funds which has made infrastructure development unfinished because these funds have been used in handling the Covid-19 virus. To find out how the Management Function of Post Flood Disaster Infrastructure Development in Masamba District, North Luwu Regency. Using the theory of George R Terry which consists of four aspects namely planning, organizing, actuating, and supervising. These four aspects will be used in research to analyze more deeply regarding the research to be carried out. As informants consisted of: PUPR Service, BNPB, Head of Maipi Village, Head of Baloli Village, Head of Bone Village, Old Head of Bone and the Community. This study used interview techniques, observation of research locations, and documentation. Using qualitative methods with descriptive research type.