Arna Fariza

Digitalization is an important step in improving the efficiency of public services, particularly in managing queues in government institutions such as sub-district offices. Kelurahan Gebang Putih Surabaya faces significant challenges in managing its manual queue system, which often results in discomfort for the public due to long waiting times, exceeding 5 minutes. This reduces public satisfaction and causes inefficiencies in the queue process. To address this issue, this study aims to develop and implement a digital queue system that can be accessed both online and on-site, using the User-Centered Design (UCD) approach. This approach ensures that every aspect of the system's design and development focuses on user needs through an iterative process, where the design is adjusted based on direct feedback from users. The proposed solution in this study includes the creation of a mobile and website-based queue system, allowing the public to easily take a queue number online and also enabling quick on-site queueing with a wait time of less than 10 seconds. Another advantage of this system is its automated reporting feature, which facilitates documentation and queue reports, thereby accelerating administration and monitoring to the city government. The results show that the implementation of this system significantly reduces the queue-taking time from over 5 minutes to less than 10 seconds, successfully transforming the manual system into a more efficient digital system, and streamlining the reporting process to the government, which in turn improves the quality and satisfaction of public services.

In Indonesia, Dengue Fever (DF) is a contagious disease that is a significant issue in public health. The Kediri Regency in East Java, as reported by the Ministry of Health in 2019, had the highest number of DF cases. If not addressed promptly, DF can lead to outbreaks, creating a health emergency. The lack of a thorough investigation into the diversity of risk within a spatial and temporal region exacerbates this issue. Therefore, spatial-temporal analysis is crucial in developing a warning system to prevent and control DF. This paper proposes a method that combines the Euclidean Distance calculation with the Hierarchical Clustering method. We collected data from the Kediri Regency health department and conducted pre-processing and classification processes, considering the number of DF victims, death rate, population, rainfall, and public facilities. The hierarchical clustering algorithm was used to categorize the 344 village analyses into low, medium, and high vulnerability categories. This method allows for a comparison of yearly single, average, complete, and centroid linkage in DF vulnerability levels. We also employed spatial-temporal visualization based on cellular applications to create a clear picture of areas vulnerable to DF. The experimental results in clustering showed a satisfactory level of matching, with variant values calculated using the hierarchical clustering method. The variants for single linkages were 0.113; for average linkages, they were 0.120; for complete linkages, they were 0.178; and for centroid linkages, they were 0.106. The grouping validation results indicated that the centroid linkage method produced the best variant level. We suggest further enhancing the methods with better process steps using other pre-processing methods to improve the validation quality.

Convolutional neural network enhancement for mobile application of offline handwritten signature verification

Tajwid is an important science that regulates the way of reading the verses of the Al-Qur’an properly. Learning Tajwid means knowing the meaning that corresponds to the correct recitation. Learning to read the Al-Qur’an tends to be done traditionally in a place of learning or by calling a teacher to the house. Learning in this way has some drawbacks, such as the limited availability of trained and competent teachers because not all areas have sufficient access to these teachers. Dependence on schedules and locations can be a constraint for students with limited mobility or busy schedules. The role of the teacher is still important in learning tajwid, especially in providing effective explanations, guidance, and feedback. However, to overcome these shortcomings, integration with independent and technology-based learning methods can help improve the accessibility, flexibility, and quality of tajwid learning. The classification of tajwid laws using image processing allows users to see the results of inputting images of verses of the Al-Qur’an into the type of detected nun sukun tajwid and how to recite it. The initial stage of this system in detecting tajwid laws from uploaded images is the input of images by users, which can be done in two ways, namely by directly taking pictures using a smartphone camera or uploading images from the gallery. This is followed by the OCR process to detect the Arabic text contained in the image and provide diacritics for that Arabic text. Finally, letter classification is carried out after nun sukun and classification of tajwid laws contained in accordance with the detected letters after nun sukun. This system has an accuracy rate of 92.18% from the classification results that have been carried out.

Shrimp farming plays a crucial role to the Indonesian economy, but it is facing challenges from shifting weather patterns and global warming. This research focuses on the development and implementation of a web-based water quality monitoring system for shrimp farming to address these concerns. The research, conducted in collaboration with shrimp farmers in Sidoarjo, East Java, introduces PENS Aquaculture program, which is designed to efficiently monitor pH, salinity, and temperature. The system employs Internet ofThings (IoT) technology, which allows farmers to register several ponds, analyze water parameters, and receive real-time data through tables and graphs. The research takes a mixed-methods approach, integrating quantitative data from IoT devices with qualitative insights gathered through surveys and interviews with shrimp farmers. The study aims to evaluate the influence of IoT technology on shrimp pond quality and its contribution to the production. The findings show that PENS Aquaculture application is helpful in increasing shrimp farming efficiency, providing significant insights for the fisheries and cultural sectors.

Tinggi badan adalah parameter penting saat memasuki sebuah wahana. Penggunaan alat keselamatan saat bermain wahana permainan tidak akan maksimal jika wisatawan tidak memiliki tinggi badan yang sesuai dengan kriteria untuk memasuki wahana tersebut. Dalam penerapannya, seleksi wisatawan yang diperbolehkan masuk ke dalam wahana permainan masih menggunakan pengukuran tinggi badan secara manual. Penelitian ini bertujuan untuk mengurangi resiko terjadinya kecelakaan pada kendaraan dengan mengklasifikasikan dan mengimplementasikan sistem otomasi menggunakan pendekatan deep learning. Penggunaan deep learning yang berkembang saat ini dapat digunakan untuk mengklasifikasikan pengunjung. Penelitian ini mengusulkan proses klasifikasi tinggi badan menggunakan metode Mask R-CNN yang dapat digunakan untuk melakukan klasifikasi lebih dari satu orang, sehingga mempercepat antrean wisatawan pada wahana permainan. Hasil pengujian menunjukkan bahwa model Mask R-CNN yang dibangun berhasil mengklasifikasikan objek dengan memberikan bounding box, masking, dan label yang sesuai dengan objek. Membangun model Mask R-CNN sangat dipengaruhi oleh variatif gambar pada dataset dan proses anotasi gambar di dalam dataset. Evaluasi model menunjukkan hasil perhitungan mAP yang didapatkan sebesar 71%. Penelitian ini telah memenuhi tujuan utama dalam penelitian karena model Mask R-CNN berhasil melakukan klasifikasi yang sesuai.

Stock exchange trading has been utilized to gain profit by constantly buying and selling best-performing stocks in a short term. Deep knowledge, time dedication, and experience are essential for optimizing profit if stock price fluctuations are analyzed manually. This research proposes a new trading prediction system that has the ability to automatically predict the accurate time for buying and selling stock using a combination of technical analysis and support vector machine (SVM). Technical analysis is used to analyze stock price fluctuation based on historical data by utilizing technical indicators such as moving average, Bollinger bands, relative strength index, stochastic oscillator, and Aroon oscillator. SVM maps inputs into higher dimensional spaces using non-linear kernel functions, making it suitable for various technical indicators implementation as inputs in stock trading prediction. Experimentation on five Indonesian stocks reveals that the combination of technical analysis and support vector machine is best suited for continuously fluctuated stocks, with the highest accuracy of 77.8%.

Sebagai bentuk pemerintahan terkecil RT melakukan berbagai fungsi tersebut seperti pelayanan administrasi keuangan dan pendataan kependudukan, Kekayaan RT dan data kependudukan warga harus dikelola secara tertib, transparan, tercatat dan dapat dipertanggung jawabkan. Karena manajemen keuangan masih menggunakan cara pencatatan manual Warga Desa Plosorejo Blitar tidak bisa me-monitoring keuangan secara langsung dan mengalami keresahan jika buku keuangan tersebut mengalami kerusakan. Selain itu tidak efektif nya pengolahan data warga oleh ketua RT karena sering berkeliling desa untuk meminta data warga. Solusi dari permasalahan di atas adalah Membuat website sistem informasi manajemen keuangan dan pendataan warga Desa Plosorejo Blitar,agar mengurangi keresahan warga dan pihak ketua RT jika mengalami kehilangan atau rusaknya catatan keuangan desa,dan juga mengefektifkan,mempercepat sekaligus meringankan tugas ketua RT dalam mengolah data warga. Metode pengujian proyek akhir ini menggunakan black box testing untuk menguji fungsionalitas aplikasi dan skala likert untuk menghitung persentasi kuesioner.

Diphtheria is a serious infectious disease induced by the Corynebacterium Diphtheriae bacteria and often causes outbreaks (extraordinary events) in various regions. Based on data from the Ministry of Health, East Java is the biggest benefactor to diphtheria cases in Indonesia. Diphtheria cases in East Java tend to increase, especially in 2018 there were 753 diphtheria cases in 38 districts. Efforts made to prevent, treat, and control diphtheria outbreaks by the government are to analyze the level of susceptibility to diphtheria. This paper proposes a new approach to analyze the level of diphtheria susceptibility using the analytical hierarchy process (AHP) and natural breaks classification in East Java Province, Indonesia. AHP method is used to obtain diphtheria susceptibility values based on seven criteria, such as the number of sufferers, number of deaths, DPT 1, DPT 2, DPT 3 immunization, population density, and humidity. Natural break classification is used to classify the vulnerability values from AHP into three levels of vulnerability, consisting of low, medium, and high. The results of the grouping are displayed in the form of spatial mapping in the form of a web-based geographic information system (web-GIS) on the determination of the diphtheria vulnerability level using the AHP-natural breaks classification. The GVF evaluation for 2016, 2017, and 2018 are respectively 0.66, 0.67, and 0.65 (more than 0.5), which means that the proposed method achieved accurate and significant classification. Spatial-temporal analysis for 2013-2018 also achieves accurate and significant with a GVF value of 0.77. The spatial-temporal analysis can predict the high potential for vulnerability.