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PERANCANGAN APLIKASI PENJUALAN TAPIS LAMPUNG BERBASIS ANDROID MENGGUNAKAN ALGORITMA STRING MATCHING Hafsah Mukaromah; Kiki Rizki Amelia
Aisyah Journal Of Informatics and Electrical Engineering Vol 1 No 1 (2019): Aisyah Journal Of Informatics and Electrical Engineering
Publisher : Aisyah Journal Of Informatics and Electrical Engineering (A.J.I.E.E)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (4.059 KB) | DOI: 10.30604/jti.v1i1.8

Abstract

Berbagai masalah yang dialami pelanggan pada saat akan melakukan pembelian tapis seperti, tidak mengetahui tapis apa yang dicari, keterbatasan informasi mengenai produk tapis yang dicari dan jumlah persediaan produk. Hal ini disebabkan belum tersedianya katalog elektronik berbasis mobile yang dapat membantu dan mempermudah pelanggan dalam mencari informasi mengenai produk tapis. Maraknya pengguna smartphone android di kalangan masyarakat dengan berbagai kelebihannya seharusnya permasalahan di atas tidak harus terjadi lagi. Penelitian ini bertujuan untuk menyediakan layanan yang dapat membantu dan mempermudah pelanggan dalam mencari dan melakukan pembelian produk tapis online melalui smartphone android. Pada aplikasi ini menerapkan algoritma pencocokan string Brute Force pada search box sebagai algoritma dalam aplikasi pencarian produk tapis. Hasil pencarian yang ditampilkan berupa detail produk tapis beserta lama waktu pencarian. Metode yang digunakan dalam pengembangan aplikasi ini adalah metode prototype dan menggunakan UML (Unified Modeling Language) sebagai alat bantu pemodelan sistem. Hasil dari penelitian pada toko Ninda Tapis Lampung dapat disimpulkan bahwa dengan adanya aplikasi penjualan tapis online dapat mempermudah pelanggan dalam mencari informasi produk dan melakukan pemesanan produk tapis secara online.
PENERAPAN SMART FARMING UNTUK BUDIDAYA CABAI DALAM GREENHOUSE Hafsah Mukaromah; Anas Ikhsanudin; Febri Arianto; Ningsiah; Sri Lestari
Aisyah Journal Of Informatics and Electrical Engineering (A.J.I.E.E) Vol. 5 No. 2 (2023): Aisyah Journal Of Informatics and Electrical Engineering
Publisher : Aisyah Journal Of Informatics and Electrical Engineering (A.J.I.E.E)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30604/jti.v5i2.227

Abstract

Budidaya tanaman cabai saat ini menjadi salah satu budidaya favorit dan sangat diminati oleh petani. Permintaan yang besar dan secara terus menerus menjadikan harga cabai masih menempati urutan teratas produk pertanian hortikultura yang sering mengalami fluktuasi harga. Terdapat beberapa jenis cabai yang dibudidayakan di Indonesia diantaranya cabai rawit, cabai merah keriting, dan cabai besar. Penelitian ini dilaksanakan melalui 2 (dua) tahapan agar diperoleh hasil yang baik. Adapun 2 (dua) tahapan tersebut yaitu Sistem Smart Greenhouse dan Sistem Fertigasi. Berdasarkan pengamatan kami, sistem fertigasi telah berfungsi dengan baik dan tanaman mendapatkan nutrisi dan air yang cukup. Berdasarkan pengukuran yang kami lakukan dengan menggunakan pressure gauge pada setiap ujung barisan tanaman, didapatkan informasi bahwa pada setiap ujung baris tanaman mempunyai tekana air yang sama besar, sehingga dapat dipastikan setiap tanaman mendapat nutrisi dan air dengan volume yang sama. Berdasarkan penelitian kami, dengan menggunakan sistem fertigasi yang terintegrasi dapat meningkatkan kualitas pertumbuhan dan perkembangan tanaman. Sistem fertigasi yang telah diimplementasikan juga semakin memudahkan petani dalam mengontrol sistem penyiraman dan pemberian nutrisi tanaman karena sdh dilengkapi dengan modul IOT berupa Haiwell IOT cloud HMI yang dapat dikontrol secara remote baik menggunakan jaringan Wifi maupun internet.
Komparasi Teknik Bagging Dan Adaboost Pada Decision Tree Dan Naive Bayes Untuk Prediksi Stroke Mukaromah, Hafsah; Wasilah
JUPITER (Jurnal Penelitian Ilmu dan Teknologi Komputer) Vol 16 No 1 (2024): Jurnal Penelitian Ilmu dan Teknologi Komputer (JUPITER)
Publisher : Teknik Komputer Politeknik Negeri Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.10790777

Abstract

Stroke, also known as cerebrovascular accident (CVA), is a condition where there is a sudden disruption in brain function due to circulation problems, which can result in paralysis or even death of brain cells. There are two main types of stroke: ischemic, caused by blockage of blood vessels, and hemorrhagic, caused by bleeding into the brain. In Indonesia, stroke is the leading cause of death with an increasing incidence rate. Therefore, early prevention and treatment efforts are crucial in managing this condition. Data mining and machine learning have become important tools in predicting the risk of stroke. In this study, ensemble techniques, particularly bagging and adaboost, were applied to decision tree and naive bayes algorithms to improve accuracy in predicting stroke. The results showed that the use of ensemble techniques, especially adaboost, significantly improved the performance of the naive bayes algorithm, with an increase in accuracy of up to 7.42%. The combination of decision tree algorithm with bagging achieved the highest accuracy in predicting stroke, reaching 96.91%, followed by the combination of decision tree with adaboost and naive bayes with adaboost. These results indicate that ensemble techniques can significantly improve the performance of stroke prediction algorithms, with an emphasis on using adaboost for naive bayes algorithm and bagging for decision tree.
PERBANDINGAN KINERJA ALGORITMA NAÏVE BAYES DAN DECISION TREE UNTUK PREDIKSI PENYAKIT BATU GINJAL Mukaromah, Hafsah
Jurnal Rekayasa Perangkat Lunak Vol. 4 No. 1 (2025): Jurnal Rekayasa Perangkat Lunak (J-Rapa)
Publisher : Universitas Aisyah Pringsewu

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

Abstract

Kidney stones consist of calcium crystals and are mineral deposits that can form in the urinary tract. The prevalence of kidney stones is estimated to be 21.11%, with the Standard Age Prevalence in men and women being 24.3% and 18.7%, respectively. This study involved participants with an average age of 52.15 years, and a higher prevalence of kidney stones was observed in women aged 40-50 years and individuals with a moderate socioeconomic status. Logistic regression results indicate that the likelihood of kidney stones is higher in individuals with diabetes, hypertension, fatty liver, and overweight. The Basic Health Research (Riskesdas) data for the year 2013 shows the prevalence of Kidney Failure and Kidney Stones in Indonesia. Therefore, a profound understanding of the factors causing kidney stone formation is crucial. This research was conducted to compare the performance of the naive Bayes and decision tree algorithm models. Based on the experimental results, the decision tree algorithm showed a higher accuracy rate of 72.50% and an AUC value of 0.740%, while naive Bayes had an accuracy rate of 68.57% and an AUC value of 0.697. These results support the conclusion that the decision tree has better predictive performance than naive Bayes.
A User-Driven E-Audit System for Improving Transparency and Efficiency in Regional Government Supervision Aminudin, Nur; Hidayat, Nurul; Feriyanto, Dwi; Mukaromah, Hafsah; Septasari, Dita; Awaliyani, Ikna
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 4 (2025): JUTIF Volume 6, Number 4, Agustus 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.4.5145

Abstract

Internal audit processes in regional government institutions often face challenges such as time inefficiency, low transparency, and poorly digitized documentation. This study aims to develop an E-Audit system to enhance the effectiveness of internal supervision in a regional inspectorate environment. Employing a user-centered design approach and a structured system development methodology, this research involved key roles—auditors, technical controllers, and follow-up teams—throughout the design and testing stages. The developed system integrates three core phases of the audit process—planning, reporting, and follow-up—into a single, modular, and interactive digital platform. Implementation results indicate a significant improvement in audit efficiency, with a reduction of more than 50% in process duration compared to manual methods. The system also enhances documentation consistency through digital audit trails, role-based dashboards, and automatic reporting features. User acceptance testing revealed a high level of satisfaction, with users highlighting the system’s ease of use, increased accuracy, and alignment with daily audit tasks. Additionally, user feedback emphasized the need for integrated notification features and inter-unit communication tools, indicating readiness for more advanced digital transformation. Overall, this study provides practical value as a model for digital audit implementation at the regional government level while contributing to the advancement of Computer Science through the application of software engineering principles and information systems to support digital government oversight. The developed E-Audit model can serve as a reference for designing real-time collaborative public auditing systems relevant to the development of information systems engineering and computational governance.