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Comparison of Machine Learning Algorithms for Predicting Stunting Prevalence in Indonesia Pratama, Moh. Asry Eka; Hendra, Syaiful; Ngemba, Hajra Rasmita; Nur, Rosmala; Azhar, Ryfial; Laila, Rahmah
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol 13, No 2 (2024): JULY
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v13i2.2097

Abstract

Stunting is a serious public health problem, especially among under-fives, which can cause serious short- and long-term impacts. Efforts to tackle stunting in Indonesia involve national strategies and development priorities. Therefore, this study aims to compare the performance of machine learning regression algorithms in predicting stunting prevalence in Indonesia. The data collected is secondary data. The data collection was done carefully, taking explicit details regarding the source, scope, extent, and analysis of the dataset, and using a careful sampling methodology. The model evaluation results show that the Random Forest Regression algorithm has the best performance, with a success rate of 90.537%. The application of this model to the new dataset shows that East Nusa Tenggara province has the highest percentage of stunting at 31.85%, while Bali has the lowest percentage at 12.07%. Visualization of the dashboard using Tableau provides a clear picture of the distribution of stunting in Indonesia. In conclusion, this research contributes to the development of science, especially in the field of machine learning and public health, and provides policy recommendations for tackling stunting in Indonesia.
Aplikasi Antrian Pasien Pada Dokter Praktek Umum Menggunakan Metode FIFO (First In First Out) Berbasis Android Hardianti, Hardianti; Hendra, Syaiful; Kasim, Anita Ahmad; Azhar, Ryfial; Angreni, Dwi Shinta; Ngemba, Hajra Rasmita
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol 12, No 1 (2023): MARET
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v12i1.1478

Abstract

Currently, there are so many services in Indonesia. One of the services in the health sector is the practice of general practitioners. Services that occur at the practice of general practitioners, namely dr. Zaki Mubarak and dr. Subhan Habibi, located in Palu, often has complaints because it is still ineffective where getting these services is still done manually by means of patients coming in person and taking a queue based on the order of seats then one by one they will be served. This causes patient discomfort in waiting. To make it easier for patients who want to seek treatment, a system is needed, with this; an Android-based patient queuing application for general practice doctors was made. The application of the method used in building the system is the FIFO queuing method where patients who register earlier get medical services first. Then the average waiting time is calculated where the results obtained will be used as an estimate of the waiting time for the next patient. The application development method in this research used the prototype method and application testing uses the black box testing method. The results of this research are the application of patient queues for general practice doctors based on Android which is built to be able to take queues anywhere and anytime and obtain some information including doctor’s practice schedules, queue numbers, running queues, and estimated waiting times so that patients can estimate arrival time without having to wait long. Based on system testing with black box, the results show that the functional system is running well. Based on the average waiting time calculation, from the 60 queue data tested, the result is that the distance between queue 1 and the order is around 5 minutes.
IMPLEMENTASI ALGORITMA RC4 PADA SISTEM INFORMASI KOPERASI VIRTUAL BAWASLU PROVINSI SULAWESI TENGAH VIRTUAL BAWASLU Ngemba, Hajra Rasmita; Ulhaq, Muhammad Naufal Daffa; Hendra, Syaiful; Azhar, Ryfial; Alamsyah, Alamsyah; Laila, Rahma
PROSISKO: Jurnal Pengembangan Riset dan Observasi Sistem Komputer Vol. 11 No. 1 (2024): Prosisko Vol. 11 No. 1 Maret 2024
Publisher : Pogram Studi Sistem Komputer Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/prosisko.v11i1.8182

Abstract

Koperasi merupakan hal yang penting bagi kemajuan ekonomi Indonesia yang berlandaskan kekeluargaan dan gotong royong. Perkembangan teknologi berupa internet dapat digunakan untuk mempermudah operasional koperasi, dan keamanan data di dalamnya tetap terjaga. Penelitian ini bertujuan untuk meningkatkan kualitas koperasi Bawaslu khususnya di Sulawesi Tengah, dan mempermudah menghubungkan koperasi dengan mitra serta bertujuan untuk mengamankan suatu transaksi yang dilakukan oleh karyawan dengan mitra nantinya tanpa adanya keamanan saat melakukan transaksi maka sangat berbahaya karena pihak-pihak lain yang tidak bertanggung jawab akan memanfaatkan celah keamanan tersebut sehingga dapat merugikan karyawan nantinya. Oleh karena itu penelitian ini menggunakan metode kriptografi dengan menggunakan algoritma RC4. Algoritma RC4 digunakan untuk enkripsi barcode pada saat melakukan transaksi. Jika id dari barcode telah diamankan, maka kecil kemungkinan pihak lain yang tidak bertanggung jawab dapat menggunakan barcode tersebut. Algoritma ini digunakan karena efektif, mudah diimplementasikan, dan ringan. Pengembangan sistem menggunakan bahasa pemrograman PHP dengan menggunakan framework Laravel. Pengujian sistem menggunakan Blackbox dan juga metode BIG-O. Hasil penelitian berdasarkan pengujian bahwa aplikasi dengan menggunakan Algoritma RC4 berjalan dengan baik karena proses enkripsi berhasil
Serli Discovery Learning Dalam Mendukung Pembelajaran Ilmu Pengetahuan Alam Siswa Berbasis Android: Serli Discovery Learning in Supporting Android-Based Natural Science Learning for Students Putri Febrina, Annisa; Ngemba, Hajra Rasmita; Hendra, Syaiful; Anshori, Yusuf; Azizah, Azizah
Technomedia Journal Vol 9 No 1 Juni (2024): TMJ (Technomedia Journal)
Publisher : Pandawan Incorporation, Alphabet Incubator Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/tmj.v9i1.2219

Abstract

The development of information technology, have a positive impact on education by providing flexible learning support. The design and presentation of the learning tool significantly affect students' interest in learning. In the current technological era, students and teachers must consider the accessibility and mobility of learning media. The purpose of this research is to develop the SERLI Application, an android-based Natural Science learning module that can be accessed anywhere by students and teachers. The application development model used is the Hannafin & Peck Model, which consists of  needs analysis,  design  stages, and  implementation & development. The method for evaluating user satisfaction uses the End User Computing Satisfaction method. This method considers variables such as content, accuracy, display format, ease of use, and timeliness. The experts tested the SERLI Application, gave a 86.58% success rate. Student users and teachers also evaluated the application and achieved a 85% success rate. These results are very good. The implementation result of this research is an android-based learning application product that contains a science lesson module. In this application, there is an initial display, namely registration into the application, then the main display of the application which contains modules and practice questions, then the display for the teacher.
Sistem Layanan Ujian Psikotes SIM Menggunakan Computer Based Test Berbasis Website: SIM Psychological Test Service System Using Computer Based Test Based on Website Suryani Putri, Fadiah; Ngemba, Hajra Rasmita; Hendra, Syaiful; Wirdayanti, Wirdayanti
Technomedia Journal Vol 9 No 1 Juni (2024): TMJ (Technomedia Journal)
Publisher : Pandawan Incorporation, Alphabet Incubator Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/tmj.v9i1.2220

Abstract

Psychometric tests are a crucial step in obtaining a Driver's License (SIM) that requires effective cooperation between the Traffic Unit (SATLANTAS), psychological institutions, and applicants. However, the psychometric test service often faces challenges due to lack of accuracy and difficulties in manual verification of test results by psychological facilities. To address this challenge, this research develops a web application to facilitate registration, conduct of psychological tests, and access to test results for applicants. This application also assists administrators in managing psychological test information and providing confirmation to applicants. The development process uses the waterfall SDLC method. In its development, testing uses 2 methods: blackbox and the Delone & Mclean method with a qualitative approach involving 47 respondents. Through this research, a SIM psychometric test service system is produced, consisting of account registration, admin and user login, and psychometric test execution pages. The resulting system, named SINAR-SIMPOLRI, can improve the effectiveness and efficiency of psychometric test services in Palu City, providing more efficient support for test participants and psychological facilities in conducting easier checks.
Analysis of the Use of MTCNN and Landmark Technology to Improve the Accuracy of Facial Recognition on Official Documents Chandra, Ferri Rama; Ngemba, Hajra Rasmita; Hamid, Odai Amer; Lapatta, Nouval Trezandy; Hendra, Syaiful; Nugraha, Deny Wiria; Syahrullah, Syahrullah
Journal of Applied Informatics and Computing Vol. 9 No. 1 (2025): February 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i1.8814

Abstract

A face recognition system consists of two stages: face detection and face recognition. Detection of features such as eyes and mouth is important in facial image processing, especially for official documents such as identity cards. To ensure identification accuracy, this research applies facial landmark extraction technology and MTCNN (Multi-Task Cascaded Convolutional Neural Network). The purpose of this research is to evaluate the accuracy of MTCNN in detecting facial features at the Department of Population and Civil Registration (dukcapil) Palu City, using facial landmarks and waterfall methods as an application development methodology. The evaluation results show that MTCNN has high face recognition accuracy and good positioning ability regardless of what GPU in use as long have right CPU and System Operation. In comparison, the Viola-Jones algorithm is effective for high-speed applications, while SSD offers balanced performance with GPU device requirements for optimal performance. While MTCNN proved to be effective, challenges still exist, such as false positives and false negatives, especially in poor lighting conditions and extreme poses. Image and camera quality, including resolution and facial expression, also affects detection accuracy. These findings suggest that the application of MTCNN can improve face recognition accuracy for official documents, although it requires addressing existing challenges. With this technology, it is expected that errors in facial recognition can be minimized, resulting in more reliable data that meets the standards for issuing identity documents. This research contributes to the development of a more accurate and efficient face recognition system for personal identification applications.
Implementasi Algoritma RC4 Pada Sistem Informasi Pelaporan DUKCAPIL Provinsi Sulawesi Tengah : Implementation of the RC4 Algorithm in the DUKCAPIL Reporting Information System of Central Sulawesi Province Iswandi, A.Avri; Ngemba, Hajra; Hendra, Syaiful; Syahrullah; Nouval Daffa Ulhaq, Muhammad
Technomedia Journal Vol 9 No 2 Oktober (2024): TMJ (Technomedia Journal)
Publisher : Pandawan Incorporation, Alphabet Incubator Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/tmj.v9i2.2233

Abstract

The Population and Civil Registration Service Reporting Information System is an important aspect in managing population data at the provincial level. However, data security in these systems is a major concern, given the sensitivity of the personal information contained therein. This research applies the RC4 algorithm to the reporting information system of the Central Sulawesi Province population and civil registration service to improve data security. This research uses a system development method with a case study approach. Researchers implemented the RC4 algorithm on an existing reporting information system and analyzed its impact on data security. Data was collected through interviews with Population and Civil Registration Service officers, observations, and testing system functionality. The applications built are tested using blackbox and crackstation. The results of black box testing show that the application produces the desired output and is in accordance with the function of the application program created. The results of the crackstation test show that the RC4 algorithm was not successfully solved. The research results show that the application of the RC4 algorithm to the reporting information system of the Central Sulawesi Province Population and Civil Registration Service can significantly increase data security. This algorithm is able to encrypt data sent over the network, thereby preventing unauthorized access and misuse of information
Sistem Terpadu Web Dan Android Sebagai Inovasi Pemasaran Produk Umkm Dan Profil Bisnis Unggulan Kabupaten Sigi : Integrated Web and Android System as Product Marketing Innovation MSMEs and Leading Business Profiles of Sigi Regency Kade Dwi Arsana, I Gusti Ngurah Agung; Wirdayanti; Syahrullah; Ngemba, Hajra Rasmita; Hendra, Syaiful
Technomedia Journal Vol 9 No 2 Oktober (2024): TMJ (Technomedia Journal)
Publisher : Pandawan Incorporation, Alphabet Incubator Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/tmj.v9i2.2267

Abstract

The digital transformation era has fueled enthusiasm for digital living among Indonesian society, driven by the surging use of internet and smartphones. The digital economy has unlocked new opportunities for businesses and entrepreneurship, significantly boosting national economic growth. In this context, MSMEs (Micro, Small, and Medium Enterprises) play a pivotal role as the backbone of Indonesia's economy, holding immense potential to drive national progress. The year 2024 has been designated as the year of digital transformation for MSMEs, with a target of integrating 30 million MSMEs into the digital ecosystem. Sigi Regency, with its 30,554 MSMEs spanning diverse business sectors, is a key focus for the local government's efforts to digitize the MSME sector, aiming to enhance product quality, services, and global competitiveness. To achieve this goal, an integrated web and Android system is proposed, empowering MSMEs to independently manage product data and business profiles, creating a digital gallery to showcase the Sigi MSME catalog.
Penerapan Algoritma K-Nearest Neighbor untuk Menentukan Potensi Ekspor Komoditas Pertanian di Provinsi Sulawesi Tengah Ngemba, Hajra Rasmita; Raivandy, I Made Randhy; Hendra, Syaiful; Ardiansyah, Rizka; Dwi Wijaya, Kadek Agus; Nugraha, Deny Wiria; Irfan, Mohamad
Jurnal Teknologi dan Manajemen Informatika Vol. 9 No. 2 (2023): Desember 2023
Publisher : Universitas Merdeka Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26905/jtmi.v9i2.10235

Abstract

Agriculture is a highly robust sector in Indonesia. This is evidenced in Central Sulawesi Province, where the gross domestic product (GDP) from the agricultural sector, based on constant prices from 2018 to 2021, continues to experience growth. Such conditions suggest that commodities in the agricultural sector have the potential to become export products, enabling a greater economic boost for the region. Before engaging in exports, it is necessary to identify which commodities have potential. One way to determine this is by applying Klassentypology. To simplify the process, it can be implemented in machine learning using the K-Nearest Neighbor algorithm. K-Nearest Neighbor is chosen because this algorithm can handle data containing noise and has good adaptability when given new data. In this research, two machine learning models were developed. The first model is used to classify whether a commodity is advancing or lagging, while the second model is used to classify commodities that grow rapidly and slowly. The highest accuracy obtained from the first model is 96.23%. Meanwhile, the highest accuracy from the second model is 93.49%.
Penerapan Algoritma K-Means Clustering Dalam Pengelompokkan Kepadatan Penduduk: Application of K-Means Clustering Algorithm in Population Density Grouping Delia, Fenita; Rasmita Ngemba, Hajra; Hendra, Syaiful; Syahrullah, Syahrullah; Trezandy Lapatta, Nouval
Technomedia Journal Vol 9 No 3 (2025): February
Publisher : Pandawan Incorporation, Alphabet Incubator Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/tmj.v9i3.2270

Abstract

Uneven population density will have a negative impact if not considered. One way to tackle this problem is with population equity management planning policies. This research focuses on clustering population density areas, which is the ratio between population and area in Central Sulawesi Province. This research clustering is applied with data mining techniques, namely K-Means Clustering. The research stages are data collection, data understanding, data processing, clustering, clustering review, dashboard analysis, and accuracy testing with the tableau application in providing visualization of population density in the region. Based on the results of the algorithm calculation, it produces three clusters, cluster 0 being low population density, cluster 1 being high population density, and cluster 2 being medium population density. Cluster formation is based on the visualization produced by the research dataset through Sum Of Square Error analysis, silhouette coefficient, and elbow method. Clustering is formed, followed by dashboard visualization with the tableau application. The clustering results, based on the SSE calculation, produce a value of 4324505738.747303, meaning the determination of the number of clusters with a significant difference with the calculation of the number of previous groupings. Then the results of the silhouette analysis provide the highest average silhouette value at the number of clusters, namely 3 with a value of 0.6144435666457168, and the elbow method gives the result that the elbow point is at point 3, meaning the optimum number of clusters with 3 clusters.