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All Journal International Journal of Artificial Intelligence Research Jurnal Informatika Universitas Pamulang REMIK : Riset dan E-Jurnal Manajemen Informatika Komputer Abdi Kami : Jurnal Pengabdian Kepada Masyarakat Jurnal Sisfotek Global Jurnal Buana Pengabdian Jurnal Pengabdian Masyarakat Nasional INTERNAL (Information System Journal) Journal Of Computer Science Contributions (JUCOSCO)
Anis Fitri Nur Masruriyah
Universitas Buana Perjuangan Karawang
Religion Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Medicine & Pharmacology Public Health Other

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PEMANFAATAN TEKNOLOGI PRESENSI UNTUK APARATUR DESA PADA DESA BAYURLOR Anis Fitri Nur Masruriyah; Muhammad Baharudin
JURNAL BUANA PENGABDIAN Vol 3 No 1 (2021): JURNAL BUANA PENGABDIAN
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat, Universitas Buana Perjuangan Karawang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (321.592 KB) | DOI: 10.36805/jurnalbuanapengabdian.v3i1.1526

Abstract

Pada era modern seperti saat ini, ternyata masih banyak instansi yang belum memaksimalkan teknologi. Salah satu contoh teknologi yang belum banyak digunakan di beberapa instansi yaitu sistem presensi. Saat ini masih ada presensi yang mengandalkan tanda tangan absen tanpa ada keterangan waktu datang dan pulang. Hal ini berdampak pada kinerja suatu instansi, terlebih instansi yang melakukan pelayanan publik. Tidak jarang ditemui instansi yang karyawannya masih belum hadir di jam operasional dengan berbagai alasan. Sehingga untuk menyelesaikan permasalahan ini, sistem presensi diimplementasikan agar karyawan dan dapat tertib dan melakukan pelayanan secara maksimal. Hasil dari implementasi adalah berkurangnya manipulasi data presensi. Kata kunci— masyarakat, pendidikan, pengabdian, presensi In the modern era nowadays, there are still many agencies that have not maximized technology. One example of technology that has not been widely used in several agencies is the present system. Currently, there is still attendance who relies on the signature of attendance without any information about the time to come and go home. This has an impact on the performance of an agency, especially agencies that provide public services. It is not uncommon to find agencies whose employees are still not present at operational hours for various reasons. So in order to solve this problem, the present system was implemented so that employees were able to be orderly and perform services optimally. The result of the implementation reduced attendance data manipulation. Keywords— community, dedication, education, presence
SOSIALISASI APLIKASI UNTUK MELAKUKAN DETEKSI DINI KECANDUAN PERMAINAN ONLINE PADA SISWA SMK N 1 KLARI KARAWANG Anis Fitri Nur Masruriyah; Deden Wahiddin; Hilda Yulia Novita; Elsa Elvira Awal
ABDI KAMI: Jurnal Pengabdian Kepada Masyarakat Vol 5 No 2 (2022): (Oktober 2022)
Publisher : LPPM Institut Agama Islam (IAI) Ibrahimy Genteng Banyuwangi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29062/abdi_kami.v5i2.1470

Abstract

The global COVID-19 pandemic has an impact on people's activities in the world, including in Indonesia. The policies of each country to overcome this condition also vary, one of which is the Indonesian government which imposes limited face-to-face activities offline. Many activities must be carried out online to minimize the transmission of COVID-19. Finally, this has an impact on many people who spend time with their gadgets to play permainans with cellphones, laptops or other electronic media. Playing permainans has benefits for relaxation from the fatigue of online activities, but if this continues it will result in permainan addiction. So that community service activities for the socialization of permainan addiction detection applications are carried out, so that users are able to control the use of devices when playing permainans. So, if an addiction is detected, you can ask experts for help, for school children you can have an initial consultation with a Counseling Guidance teacher.
The Utilization of Decision Tree Algorithm In Order to Predict Heart Disease Mia Mia; Anis Fitri Nur Masruriyah; Adi Rizky Pratama
JURNAL SISFOTEK GLOBAL Vol 12, No 2 (2022): JURNAL SISFOTEK GLOBAL
Publisher : Institut Teknologi dan Bisnis Bina Sarana Global

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38101/sisfotek.v12i2.551

Abstract

The data on heart disease patients obtained from the Ministry of Health of the Republic of Indonesia in 2020 explains that heart disease has increased every year and ranks as the highest cause of death in Indonesia, especially at productive ages. If people with heart disease are not treated properly, then in their effective period a patient can experience death more quickly. Thus, a predictive model that is able to help medical personnel solve health problems is built. This study employed the Random Forest and Decision Tree algorithm classification process by processing cardiac patient data to create a predictive model and based on the data obtained, showing that the data on heart disease was not balanced. Thus, to overcome the imbalance, an oversampling technique was carried out using ADASYN and SMOTE. This study proved that the performance of the ADASYN and SMOTE oversampling techniques on the C45 algorithm and the Random Forest Classifier had a significant effect on the prediction results. The usage of oversampling techniques to analyze data aims to handle unbalanced datasets, and the confusion matrix is used for testing Precision, Recall, and F1-SCORE, as well as Accuracy. Based on the results of research that has been carried out with the K-Fold 10 testing technique and oversampling technique, SMOTE + RF is one of the best oversampling techniques which has a greater Accuracy of 93.58% compared to Random Forest without SMOTE of 90.51% and SMOTE + ADASYN of 93.55%. The application of the SMOTE technique was proven to be able to overcome the problem of data imbalance and get better classification results than the application of the ADASYN technique.
Development of Health Mask Identification Using YOLOv5 Architecture Ahmad Fauzi; Prasetyo Ajie; Anis Fitri Nur Masruriyah; Deden Wahiddin; Hanny Hikmayanti; April Lia Hananto
International Journal of Artificial Intelligence Research Vol 6, No 1.1 (2022)
Publisher : International Journal of Artificial Intelligence Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v6i1.1.573

Abstract

Coronavirus Disease 2019 (COVID-19) causes the state to suffer losses, especially in the health sector. WHO calls for controlling COVID-19 with health protocols that must be obeyed, one of which is wearing a mask. The use of masks can reduce the transmission of COVID-19. But there are still many people who ignore the protocol to use masks properly. So a system was created to detect the use of masks properly using the YOLOv5 architecture. Aiming to help regulate the use of masks in public areas or open places. The process of this research begins with data collection in the form of images. The collected image data will later be used as a dataset and model training will be carried out using the YOLOv5s model. The accuracy results obtained from this study reached 90.37%
Penerapan Fuzzy Inference System untuk Sistem Pemantauan Kualitas Air pada Budidaya Cheerax Quadricarinatus Budi Arif Dermawan; Adhi Rizal; Anis Fitri Nur Masruriyah
Jurnal Informatika Universitas Pamulang Vol 8, No 1 (2023): JURNAL INFORMATIKA UNIVERSITAS PAMULANG
Publisher : Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/informatika.v8i1.29214

Abstract

Cheerax quadricarinatus (Redclaw) becomes a fishery commodity that has high selling value with various advantages in terms of cultivation. In the Redclaw cultivation process, water quality is one of the indicators that require attention. Flawed water quality affects the conditions when the lobsters molt. In addition, shoddy water quality also impacts the slow growth rate and high mortality during ontogeny. The level of water quality is influenced by the parameters of Temperature, Potential of Hydrogen (pH), Ammonia, and Total Dissolved Solid (TDS). The level of water quality requires monitoring in real-time with the aim of being able to find out the latest conditions according to the category of aquaculture pond. Water quality monitoring is carried out by implementing a Fuzzy Inference System in a Water Quality Monitoring System based on a Wireless Sensor Network (WSN) and the Internet of Things (IoT). The water quality monitoring system is running well, marked by all sensors being able to send parameter values and the monitoring dashboard being able to display all parameter values along with water quality and condition values. The water quality level results show that the pond's cultivation habitat is in a suitable category, indicated by a water quality value of more than 90%. The level of water quality can be represented as suitability for Redclaw habitat to increase growth.
Implementasi Model Klasifikasi Jenis Kanker Payudara Menggunakan Algoritma SVM dan Logistic Regression Berbasis Web Nunung Nurjanah; Arphilia Nur Rani; Hanny Hikmayanti Handayani; Anis Fitri Nur Masruriyah
REMIK: Riset dan E-Jurnal Manajemen Informatika Komputer Vol. 7 No. 4 (2023): Volume 7 Nomor 4 Oktober 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/remik.v7i4.12817

Abstract

Menurut Organisasi Kesehatan Dunia (WHO), ada 7 juta pasien kanker payudara, 5 juta di antaranya meninggal setiap tahun. Berdasarkan data Globocan untuk 2018 menunjukkan tingkat kematian rata-rata 17 per 100.000 orang dan insiden 2,1 per 100.000 orang yang menyerang perempuan di Indonesia. Hal itu, menyebabkan kanker payudara ini merusak genetic pada DNA dari sel epitel payudara menjalar ke ductus. Tujuan penelitian ini untuk mengklasifikasi jenis kanker (jinak atau ganas) yang diderita. Perbedaan penelitian sebelumnya dengan penelitian ini adalah metode pengujian algoritma yang dipilih. Pada penelitian ini menggunakan algoritma SVM dan Logistic Regression dengan SMOTE. Beberapa tahapan yang digunakan pada penelitian ini dimulai dengan pengumpulan data, kemudian pre-processing. Selanjutnya implementasi, evaluasi dan deployment pada sistem. Adapun metode K-Fold Cross Validation digunakan pada  penelitian ini untuk melakukan partisi pada data.  Sedangkan evaluasi model menggunakan confusion matrix. Berdasarkan tujuan penelitian, deployment dilakukan menggunakan flask untuk melakukan mengimplementasikan model pada sistem. Adapun metode pengembangan sistem yang digunakan pada penelitian ini yaitu RAD dengan beberapa tahapan. Tahapan dimulai dengan analisis kebutuhan, prototype dan implementasi. Berdasarkan hasil dari penelitian ini menunjukkan bahwa accuracy yang didapat sebesar 1.0, precision 1.0 dan recall 1.0. Selain itu, accuracy yang didapatkan pada sistem yaitu 90%. Maka dari itu, diharapkan berdasarkan hasil penelitian ini dapat membantu tenaga medis untuk mengklasifikasikan jenis kanker payudara, guna melakukan pengobatan secara cepat dan tepat pada penderita penyakit kanker payudara.
Aplikasi Berbasis Web Berdasarkan Model Klasifikasi Algoritma SVM dan Logistic Regression Terhadap Data Diabetes Nita Fitriyani; Dinda Resna Amalia; Hanny Hikmayanti Handayani; Anis Fitri Nur Masruriyah
REMIK: Riset dan E-Jurnal Manajemen Informatika Komputer Vol. 7 No. 4 (2023): Volume 7 Nomor 4 Oktober 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/remik.v7i4.13001

Abstract

Berdasarkan International Diabetes Federation Atlas Tenth edisi 2021, jumlah penderita diabetes mencapai 537 juta orang dalam rentang usia 20-79 tahun. Jumlah penderita diabetes akan terus meningkat mencapai 643 juta pada tahun 2030, bahkan diperkirakan mencapai 783 juta pada tahun 2045. Diabetes tidak hanya menjadi penyebab 6,7 juta kematian, tetapi juga menguras dana kesehatan hingga 966 miliar USD. Tingkat kadar gula darah yang tinggi secara kronis menjadi tanda penyakit diabetes, keadaan ini terjadi ketika tubuh tidak mampu menghasilkan insulin secara efektif. Penelitian ini bertujuan untuk mengembangkan model klasifikasi penderita penyakit diabetes dengan membandingkan dua Algoritma, Support Vector Machine (SVM) dan Regresi Logistik. Dalam penelitian ini, model dievaluasi menggunakan metode K-Fold cross validation dengan membagi dataset menjadi 10 subset. Salah satu subset dipilih sebagai data uji, sementara subset lainnya digunakan sebagai data latih. Hasil penelitian menunjukkan bahwa klasifikasi terbaik diperoleh pada Algoritma SVM dengan teknik SMOTE. Model ini mencapai rata-rata accuracy sebesar 88,77%, precision 88,50%, dan recall 89,21%. Dengan demikian, model yang dikembangkan menggunakan Algoritma SVM dengan SMOTE dapat diimplementasikan ke dalam sebuah sistem klasifikasi penyakit diabetes. Pembuatan aplikasi ini ditujukan kepada pihak medis untuk membantu dalam menguatkan diagnosa pemeriksaan, apakah seseorang menderita penyakit diabetes atau tidak dengan tingkat akurasi yang baik.
SOSIALISASI HASIL PENELITIAN APLIKASI SISTEM PAKAR DIAGNOSA KECANDUAN GAME ONLINE MENGGUNAKAN METODE CERTAINTY FACTOR Elsa Elvira Awal; Deden Wahiddin; Anis Fitri Nur Masruriyah; Hilda Yulia Novita
PEMANAS: Jurnal Pengabdian Masyarakat Nasional Vol 3, No 1 (2023)
Publisher : PEMANAS: Jurnal Pengabdian Masyarakat Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/pemanas.v3i1.19974

Abstract

Semenjak pandemi Covid-19 masuk di Indonesia, hampir semua kegiatan dilakukan secara daring, termasuk pembelajaran dari tingkat sekolah dasar sampai universitas. Dampak dari pembelajaran daring adalah kebosanan pada peserta didik, oleh sebab itu peserta didik banyak yang melakukan kegiatan lain untuk menghilangkan kebosanan dengan bermain game online. Kondisi mental pada peserta didik rata-rata masih labil sehingga mudah lepas kontrol ketika sedang bermain game online, sehingga banyak peserta didik yang kecanduan game online. Adapun bentuk kegiatan sosialisasi ini dilakukan melalui pengarahan tentang pengetahuan dasar mengenai game, di antaranya dampak positif dan negatif game online. Maka pada kegiatan pengabdian kepada masyarajat ini akan dilakukan sosialisasi aplikasi deteksi kecanduan game online dengan menggunakan metode certainty factor. Hasil dari sosialisasi yang dilakukan pada SMK N 1 Klari adalah memberikan pemahaman terhadap siswa/siswi tentang game online serta memahami dampak berbahaya jika tidak disikapi dengan bijak. Dengan aplikasi yang kamu berikan diharapkan para siswa/siswi mampu menggunakan game dengan sewajarnya.
The Performance Comparison of Classification Algorithm in Order to Detecting Heart Disease Chepy Sonjaya; Anis Fitri Nur Masruriyah; Dwi Sulistya Kusumaningrum; Adi Rizky Pratama
INTERNAL (Information System Journal) Vol. 5 No. 2 (2022)
Publisher : Masoem University

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Heart disease in Indonesia, especially in the productive age, there is always an increase in the number of cases. The main cause of the increase in the number of heart patients is an unhealthy lifestyle and diet. The increase in patients with heart disease also has an impact on decreasing the standard of living. With this in mind, there is a need for research related to comparing classification methods on heart disease datasets. The dataset obtained is not balanced so that an oversampling technique is needed. The oversampling technique used is SMOTE. This research method uses Support Vector Machine (SVM) and Logistic Regression (LR). In order for this research method to be applied successfully, the data acquisition, data pre-processing and data transformation techniques are used to ensure accurate results. The model evaluation technique used is K-Fold Cross Validation. Based on the results of the analysis, it showed that the data partition using k-fold cross validation without oversampling gets the same accuracy value but the precision value is quite low. Conversely, if using the SMOTE technique, the accuracy value is as good as the precision value. The results of the SVM accuracy value get a value of 91.69%. LR is 91.76%. While the results of the SVM precision value of 57.81% and LR 54.82%. If using the SVM oversampling technique, the score is 75.79% and the LR is 75.84%. Meanwhile, the precision value obtained in SVM is 75.74%. At LR by 74.77%.
Pengenalan Prototype Kumbung Jamur Merang Berbasis Internet of Things Pada Desa Gempol Kolot Anis Fitri Nur Masruriyah
Journal Of Computer Science Contributions (JUCOSCO) Vol. 2 No. 1 (2022): Januari 2022
Publisher : Lembaga Penelitian, Pengabdian kepada Masyarakat dan Publikasi Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/0endn253

Abstract

One of the impacts of the COVID-19 pandemic in Karawang Regency is the reduction of employees and cutting costs on mushroom cultivation. This has an impact on the monitoring period for mushrooms, mushroom farmers who have to enter the mushroom kumbung with higher temperature and humidity outside the kumbung. Prior to the pandemic, the monitoring employees took turns checking the condition of the mushrooms, but due to the pandemic and the limited number of employees, farmers were overwhelmed. Based on these problems, the introduction of technology in the form of a prototype of kumbung mushroom based on the internet of things was carried out to help mushroom cultivators. The recommendation given to mushroom farmers is to implement an IoT system to help increase the number of harvests and shorten harvest time. Furthermore, for the implementing team for community service and universities, it is to find a solution to create an economical system. So that mushroom farmers are not burdened with system installation costs.
Co-Authors Adhi Rizal Adi Rizky Pratama Ahmad Fauzi April Lia Hananto Arphilia Nur Rani Budi Arif Dermawan Chepy Sonjaya Deden Wahiddin Dinda Resna Amalia Dwi Sulistya Kusumaningrum Elsa Elvira Awal Hanny Hikmayanti Hanny Hikmayanti Handayani Hilda Yulia Novita Mia Mia Muhammad Baharudin Nita Fitriyani Nunung Nurjanah Prasetyo Ajie