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All Journal Jurnal Ilmu Komputer Jurnal Teknologi Informasi dan Ilmu Komputer JITK (Jurnal Ilmu Pengetahuan dan Komputer) Techno Nusa Mandiri : Journal of Computing and Information Technology Jurnal Riset Informatika JUSIM (Jurnal Sistem Informasi Musirawas) EVOLUSI : Jurnal Sains dan Manajemen INTI Nusa Mandiri Jurnal Pengabdian Masyarakat Asia Jurnal AbdiMas Nusa Mandiri IMTechno: Journal of Industrial Management and Technology Abdiformatika: Jurnal Pengabdian Masyarakat Informatika Academic Journal of Computer Science Research (AJCSR) Jurnal Inovasi Pengabdian dan Pemberdayaan Masyarakat Jurnal Pengabdian Kreatif Cemerlang Indonesia Akademika
Duwi Cahya Putri Buani
Universitas Nusa Mandiri
Arts Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Physics Public Health Social Sciences Other

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APLIKASI PENCARIAN ORANG HILANG (PORTALANG) MENGGUNAKAN PEMINDAI WAJAH BERBASIS ANDROID: Face Recognition;TensorFlow;Artificial Intelligence. Yudhistira Primatama; Angger Eka Rhamadani; Fathurrahman Dwi Ramtomo; Buani, Duwi Cahya Putri
JURNAL AKADEMIKA Vol 14 No 1 (2021): Jurnal Akademika
Publisher : LP2M Universitas Nurdin Hamzah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53564/akademika.v14i1.687

Abstract

Artificial intelligence (AI) , is clear evidence that today's technology is very advanced, this technology can be used in any fields that require artificial intelligence. Such as medicine, tourism, industry, even government and tools that help us in our daily work. One example of Artificial Intelligence is Face Recognition which will recognize recognized faces (added). This technology will be used to help find missing people, who need facial data, which requires an Android smartphone to capture facial images through the camera, which will then be processed by TensorFlow Machine Learning which will immediately store the data. received (input). The light intensity factor, image clarity, will play an important role in the results of the Tensor Flow process, the better the light intensity, the clarity of the image, the more accurate facial recognition will be.
SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN KARYAWAN TERBAIK MENGGUNAKAN METODE SAW (STUDI KASUS KELURAHAN JATIWARINGIN: SAW;Simple Additive Weighting;Villages;Employees;Achievers. Sartika, Bella; Cahya Putri Buani, Duwi
JURNAL AKADEMIKA Vol 14 No 2 (2022): Jurnal Akademika
Publisher : LP2M Universitas Nurdin Hamzah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53564/akademika.v14i2.857

Abstract

Simple Addictive Weighting (SAW) method is a definition of the term weighted sum. From this method the basic concept is to determine a weighted summation of the performance rankings on each alternative used in each attribute. The assessment will be more precise because it is based on the value of criteria and the weight of preferences that have been determined. The purpose of this study is to analyze the results of calculations using a decision support system adrift of the selection of outstanding employees in JatiwaringinPondokgede Village as the end result becomes the best assessment. Based on calculations using the Simple Additive Weighting (SAW) method, researchers obtained the best employees as many as 7 people with the highest score obtained by 1. And get 5 employees with the lowest score. By applying the Simple Additive Weight (SAW) method through a more efficient employee performance selection process so that from the village side more quickly decide in choosing the performance of outstanding employees. Decision on the use of Simple Additive Weighting (SAW) methods in agencies and skilled and creative workforces. For 5 employees who get the lowest grades are expected to get more coaching. In order to create better behavior than that.
PENERAPAN DECISION TREE UNTUK KLASIFIKASI GANGGUAN TIDUR DENGAN HYPERPARAMETER TUNING DAN SMOTE Putri Buani, Duwi Cahya
JUSIM (Jurnal Sistem Informasi Musirawas) Vol 10 No 1 (2025): JUSIM : Jurnal Sistem Informasi Musi Rawas JUNI
Publisher : LPPM UNIVERSITAS BINA INSAN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32767/jusim.v10i1.2538

Abstract

Tidur memiliki peran yang sangat penting dalam menjaga kesehatan fisik dan mental seseorang. Kurang tidur dapat berdampak buruk pada tingkat konsentrasi, daya ingat, serta meningkatkan risiko berbagai penyakit seperti obesitas, diabetes, hipertensi, dan penyakit jantung. Menurut data dari National Sleep Foundation, sebanyak 65% masyarakat Amerika merasa tidak puas dengan kualitas tidur mereka dan mengalami gejala depresi. Oleh karena itu, identifikasi gangguan tidur menjadi langkah krusial dalam meningkatkan kualitas hidup individu. Penelitian ini bertujuan untuk mengembangkan model klasifikasi gangguan tidur dengan menerapkan algoritma Decision Tree yang disempurnakan melalui hyperparameter tuning menggunakan RandomizedSearchCV. Selain itu, penelitian ini juga mengadopsi teknik Synthetic Minority Over-sampling Technique (SMOTE) guna menangani masalah ketidakseimbangan data dalam dataset gangguan tidur, sehingga model yang dihasilkan dapat memberikan prediksi yang lebih akurat dan adil terhadap kategori gangguan tidur.
PENINGKATAN KAPASITAS KWT SERUNI MELALUI PARTICIPATORY ACTION RESEARCH DALAM URBAN FARMING DAN HIDROPONIK Solecha, Kusmayanti; Buani, Duwi Cahya Putri; Indriyani, Furi; Emiliana, Meutia Raissa; Apriliani, Resti Dhea Putri
Jurnal AbdiMas Nusa Mandiri Vol. 7 No. 2 (2025): Periode Oktober 2025
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/abdimas.v7i2.7265

Abstract

This community service program aims to enhance the capacity and self-reliance of the Seruni Women Farmer Group (KWT Seruni) in supporting food security through training on urban farming and hydroponic cultivation, implemented using a Participatory Action Research (PAR) approach. The program engaged lecturers, students, and group members in stages of socialization, training, technology implementation, mentoring, and sustainability planning. Evaluation results indicated a 12% improvement in participants’ understanding based on pre-test and post-test scores, demonstrating the program’s effectiveness in strengthening technical competence. Technological implementation, including the construction of a seed house and the use of pH and TDS meters, resulted in 1,500 high-quality seedlings and a hydroponic pakcoy harvest of 18.4 kg. Participants successfully applied practical skills independently, particularly in nutrient management and the cultivation of economically valuable crops. The program also fostered an internal training system for new members and generated socio-economic benefits, such as increased household income and strengthened women’s roles in agriculture. Overall, this activity aligns with SDGs 1, 2, 5, and 12.
DIGITALISASI PENCATATAN KADER JUMANTIK MELALUI APLIKASI SMART DBD ZERO DI KELURAHAN PAMULANG TIMUR Putri Buani, Duwi Cahya; Angraeni Putri, Sukmawati; Setiaji, Setiaji
Jurnal AbdiMas Nusa Mandiri Vol. 7 No. 2 (2025): Periode Oktober 2025
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/abdimas.v7i2.7438

Abstract

Community service was carried out in partnership with RW 11, Pamulang Timur Sub-district, South Tangerang, as an effort to support the technology-based Dengue Hemorrhagic Fever (DBD) prevention program. The activity was conducted through two stages: training on the use of the SMART DBD Zero application and counseling on DBD prevention. The SMART DBD Zero application is designed to assist Jumantik cadres (larvae monitoring cadres) in recording and reporting mosquito larvae findings more quickly, accurately, and integrally. Meanwhile, counseling was carried out to increase public knowledge regarding the symptoms, transmission, and DBD prevention steps through the 3M Plus principle. The goals of the community service activity were to increase the digital literacy of Jumantik cadres regarding technology, increase the knowledge of Jumantik cadres regarding DBD prevention with 3M Plus, and increase the effectiveness and efficiency of recording mosquito larvae using a website application. The methods used were needs identification, socialization of activities, training on the SMART DBD Zero application, 3M Plus Counseling, and activity evaluation. The results of the activity evaluation used Likert scale questionnaires, pre-tests, and post-tests. The pre-test results showed that the initial level of public knowledge was 55%, which significantly increased to 97% on the post-test following the counseling. Meanwhile, satisfaction with the application training and DBD prevention counseling was above 90%, with a dominant category of strongly agree.
Peningkatan Sumber Daya Manusia melalui Pelatihan Pembuatan Blog Bagi DKM Masjid Jami Darul Hikmah Nuraeni, Nia; Buani, Duwi Cahya Putri; Astuti, Puji; Hayuningtyas, Ratih Yulia
Abdiformatika: Jurnal Pengabdian Masyarakat Informatika Vol. 3 No. 1 (2023): Mei 2023 - Abdiformatika: Jurnal Pengabdian Masyarakat Informatika
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59395/abdiformatika.v3i1.185

Abstract

Pengabdian kepada masyarakat ini berupa pelatihan dan pendampingan dalam pembuatan blog menggunakan Blogspot kepada anggota DKM Mesjid Jami Darul Hikmah. Blog merupakan salah satu media penyebaran informasi sekaligus media untuk mendokumentasikan ide, gagasan, dan kegiatan-kegiatan yang dimiliki oleh penggunanya. Keterbatasan informasi mengenai teknologi informasi di dalam lingkungan DKM Mesjid Jami Darul Hikmah membuat kami tergerak untuk memberikan pemahaman baru tentang teknologi informasi dan perkembangannya. Tujuan dari pengabdian masyarakat ini adalah untuk memberikan informasi yang konkrit kepada masyarakat khususnya DKM Mesjid Jami Darul Hikmah, memberikan informasi dan ilmu yang positif sehingga nantinya dapat bermanfaat dalam kehidupan bermasyarakat. Metodologi yang digunakan berupa pelatihan yang dimulai dengan diskusi teori tentang bagaimana memulai membangun blog, menggunakan blogspot dan mempraktekan cara membuat desain, perencanaan dan penerapan blogspot. Diharapkan hasil yang akan diperoleh adalah DKM masjid jami darul hikmah dapat membuat blog dengan desain yang menarik untuk kebutuhan lingkungan sekolah dan masyarakat sekitar.
Implementasi Algoritma Random Forest Untuk Menentukan Penerima Bantuan Raskin Kurniawan, Ilham; Buani, Duwi Cahya Putri; Abdussomad, Abdussomad; Apriliah, Widya; Saputra, Rizal Amegia
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 10 No 2: April 2023
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.20236225

Abstract

Kemiskinan adalah salah satu perhatian mendasar dari setiap pemerintah. Program Beras Keluarga Miskin (Raskin) merupakan  salah satu program pemerintah. Skema raskin mempunyai tujuan meminimalisir beban rumah tangga tidak mampu sebagai bentuk bantuan untuk menaikkan ketahanan pangan melalui perlindungan sosial. Tujuan penelitian ini adalah menemukan akurasi tertinggi di antara algoritma klasifikasi prediktif yang diusulkan penerima bantuan raskin menggunakan tools python machine learning dan di implementasikan melalui suatu website. Klasifikasi adalah metode penambangan data yang menentukan kategori pada kelompok data untuk mendukung prediksi dan analisa yang semakin akurat. Beberapa algoritma klasifikasi pembelajaran mesin seperti, SVM, NB dan RF, digunakan pada penelitian ini demi menentukan penerima bantuan raskin. Eksperimen dilakukan menggunakan dataset Raskin Kelurahan Gunungparang, Kota Sukabumi yang bersumber dari Kelurahan Gunungparang. Kinerja algoritma klasifikasi dievaluasi dengan beragam metrik seperti Precision, Accuracy, F-Measure, dan Recall. Akurasi diukur melalui contoh yang dikelompokan dengan benar atau salah. Hasil yang diperoleh menunjukkan algoritma klasifikasi RF memiliki nilai precision, recall, f-measure dengan nilai 97%, nilai accuracy sebesar  97,26% dan nilai ROC 0,970, lebih baik dari algoritma klasifikasi lainnya yaitu perbedaan sebesar 5,11% dengan algoritma klasifikasi support vector machine dan 8,87% dengan algoritma klasifikasi naive bayes. Akurasi sangat baik digunakan sebagai acuan kinerja algoritma apabila jumlah False Negative dan False Positive jumlah nya mendekati. Hasil penelitian ini dibuktikan secara akurat dan sistematis menggunakan Receiver Operating Characteristic (ROC). Abstract The problem of poverty is one of the fundamental concerns of every government. The Raskin  program is one of the government's programs. The Raskin scheme has the aim of minimizing the burden on poor households in the form of assistance to improve food security by providing social protection. The purpose of this study is to find the highest accuracy among the predictive classification algorithms proposed by Raskin beneficiaries using python machine learning tools and implemented through a website. Classification is a data mining method that determines categories in data groups to support more accurate predictions and analysis. Therefore, three machine learning classification algorithms such as, support vector machine, naive bayes and random forest, were used in this experiment. to determine recipients of Raskin assistance. The experiment was carried out using the Raskin dataset, Gunungparang Village, Sukabumi City, which was sourced from Gunungparang Village. The performance of the classification algorithm is evaluated by various metrics such as Precision, Accuracy, F-Measure, and Recall. Accuracy is measured by correctly and incorrectly grouped samples. The results obtained show that the random forest classification algorithm has precision, recall, f-measure values with a value of 97%, an accuracy value of 97.26% and an ROC value of 0.970, better than other classification algorithms, namely the difference of 5.11% with the support vector classification algorithm. machine and 8.87% with naive bayes classification algorithm. Very good accuracy is used as a reference for algorithm performance if the number of False Negatives and False Positives is close. These results were proven accurately and systematically using Receiver Operating Characteristics (ROC).
Application of XGB Classifier for Obesity Rate Prediction Cahya Putri Buani, Duwi; Nuraeni, Nia
Jurnal Riset Informatika Vol. 6 No. 1 (2023): December 2023
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v6i1.260

Abstract

According to the Ministry of Health, the percentage of the population in Indonesia who are overweight is 13.5% for adults aged 18 years and over, while 28.7% are obese with BMI>=25 and obese with BMI>=27 as much as 15.4%. Meanwhile, at the age of children 5-12 years, 18.8% were overweight and 10.8% were obese. From these data, early detection of obesity levels is needed. From these data, prevention is needed so that the percentage of the population who experience obsediness can decrease, one of the efforts that can be done is to do early detection of obesity, to do early detection of obesity can be done using Machine Learning. In this study, it was discussed about the prediction of obestias levels using 7 (seven) models, namely Naive Bayes (NB), Random Forest (RF), K-NN, Decision Tree Classifier (DTC), SVM, XGB Classifier (XGB), Logistic Regression (LR) from the seven models used to predict the obesity level of XGB Classifier (XGB) which has the highest accuracy, namely Accurasy 0.96, with an f1-score of 0.96,  Precission and recall 0.96.
PENGEMBANGAN SISTEM DIGITALISASI ARSIP SURAT DI LINGKUNGAN PUSAT KEUANGAN MABES POLRI SELONG BEBASIS WEBSITE: Archiving System, Data Security, Document Digitization, Waterfall, Website Buani, Duwi Cahya Putri; Johansyah, Septian Dwi Nur
JURNAL AKADEMIKA Vol 18 No 1 (2025): Jurnal Akademika
Publisher : LP2M Universitas Nurdin Hamzah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53564/1saqa649

Abstract

The conventional letter archiving system still employed by government institutions such as the Financial Center of the National Police Headquarters (Mabes Polri) Selong faces several limitations, including document loss risks, slow retrieval processes, and restricted physical storage capacity. To address these issues, this study developed a web-based letter archiving system using the Waterfall development model. The system was designed to replace manual processes with a more structured, accurate, and efficient digital workflow. Key features of the system include account registration, login authentication, document management, category and file management, user administration, and theme customization. System testing demonstrated that all eight core features operated successfully. Performance evaluation using GTmetrix achieved a 90% performance score with an average page load time of 2.2 seconds. Security testing confirmed that the system is free from malware and blacklist threats, with only two medium-level risks identified out of forty test cases. The results indicate that the proposed system effectively enhances administrative efficiency and provides a reliable digital archiving solution to support correspondence management within government institutions.
Co-Authors Abdussomad, Abdussomad Achyar Ibnu Hadjar Agnes Deny Pratama Al Fitra, Razky Gilang Alexandre, Michael Andriyanto Mantovandi Angger Eka Rhamadani Anggraeni Putri, Sukmawati Angraeni Putri, Sukmawati Apriliani, Resti Dhea Putri Deni Fitriani Eka Fitriani Emiliana, Meutia Raissa Estu Mulia Warna Diyanti Fathurrahman Dwi Ramtomo Fikriyansyah , Muhamad Furi Indriyani Ilham Kurniawan Ilham Kurniawan Ilham Ramadhan Indah Suryani Indah Suryani Indah Suryani - STMIK Nusa Mandiri Jakarta Ispandi Ispandi Johansyah, Septian Dwi Nur Karim Kamali , Muhammad Kusmayanti Solecha Lukman Hakim Mitchell Nere Nasrudin Nia Nuraeni Nia Nuraeni Nining Suryani Puji Astuti Puji Astuti Rahmawati, Ami Ratih Yulia Hayuningtyas Rizal Amegia Saputra Rizal Khoirul Amri Rizka Ayu Lestari Rizky Maulana Sartika, Bella Saudur Setiaji Setiaji, Setiaji Stefanus Yogi Gunawan Suandi, Arfian Rifki Sukmawati Anggraeni Putri Sukmawati Anggraeni Putri Widya Apriliah Widya Apriliah, Widya Yohanes Christofer Lodewico Abineno Yudhistira Primatama