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All Journal Dinamik Lisanuna: Jurnal Ilmu Bahasa Arab dan Pembelajarannya Sistemasi: Jurnal Sistem Informasi JURIKOM (Jurnal Riset Komputer) JURTEKSI Jurdimas (Jurnal Pengabdian Kepada Masyarakat) Royal IJOEP : International Journal of Ecophysiology Jurnal Teknisi J-Com (Journal of Computer) al-fikrah: Jurnal Manajemen Pendidikan Jurnal Algoritma TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Journal Of Indonesian Social Society RENATA Jurnal Pengabdian Masyarakat Kita Semua Jurnal Cendekia Mengabdi Berinovasi dan Berkarya Lajagoe Journal of Management and Business
Rahmadani, Nurul
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Perancangan E-CRM terhadap Loyalitas Konsumen di Rainbow Cafe Maharani, Putri Zakiyah; Rahmadani, Nurul; Sumantri, Sumantri
Dinamik Vol 30 No 2 (2025)
Publisher : Universitas Stikubank

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35315/dinamik.v30i2.10188

Abstract

Berkembangnya industri kuliner di Indonesia yang pesat menuntut pengusaha untuk beradaptasi dengan cepat, terutama dalam teknologi dan pemasaran. Karena Masih terlalu banyak pengusaha yang masih mengandalkan metode pemesanan dan promosi manual, maka dari itu penerapan Customer Relationship Management (CRM) menjadi solusi yang efektif untuk menarik pelanggan baru dan mempertahankan loyalitas konsumen. Penelitian ini fokus pada penerapan CRM di Rainbow Cafe, yang bertujuan dalam memikat konsumen baru dan meningkatkan loyalitas konsumen di Rainbow Cafe. Metode penelitian yang digunakan adalah analisis kualitatif melalui wawancara dan survei kepada konsumen serta pengusaha. Hasil penelitian menunjukkan bahwa penerapan CRM sangatlah penting dikarenakan dapat meningkatkan interaksi dengan konsumen, mempercepat proses pemesanan, dan meningkatkan kepuasan konsumen. Kesimpulan dari penelitian ini menegaskan bahwa implementasi CRM tidak hanya penting untuk meningkatkan loyalitas konsumen, tetapi juga sebagai strategi yang krusial dalam menghadapi persaingan di industri kuliner yang semakin ketat dan untuk interaksi dengan konsumen lebih efektif.
Optimalisasi Anggaran Operasional UMKM Untuk Meningkatkan Efisiensi Bisnis di Loundry Putri, Rita Dwi; Maison, Witra; Rahmadani, Nurul; Jumailis, Mutia Fitri; Arsyabil, Trisya; Yeni, Fitri
RENATA: Jurnal Pengabdian Masyarakat Kita Semua Vol. 3 No. 2 (2025): Renata - Agustus 2025
Publisher : PT Berkah Tematik Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61124/1.renata.202

Abstract

Kegiatan pengabdian kepada masyarakat ini bertujuan untuk meningkatkan pengetahuan dan keterampilan pelaku UMKM di Kota Solok, khususnya Kelurahan KTK, dalam menyusun dan mengelola anggaran operasional. Sasaran kegiatan ini adalah UMKM Hanifah Laundry Express yang belum memiliki sistem penganggaran yang terstruktur. Kegiatan dilaksanakan melalui sosialisasi, pelatihan, dan pendampingan langsung oleh tim dosen dan mahasiswa pada mata kuliah Akuntansi Manajemen Lanjutan. Hasil kegiatan menunjukkan peningkatan pemahaman sebesar 75% berdasarkan hasil pre-test dan post-test, serta 80% peserta mulai menerapkan pencatatan sederhana dalam operasional harian mereka. Pendampingan ini membuktikan bahwa intervensi sederhana namun terstruktur dapat membantu pelaku UMKM dalam efisiensi biaya dan perencanaan keuangan jangka panjang
Penerapan Business Intelligence Sebagai Solusi Manajemen Bisnis Pada UMKM di Desa Silo Baru Rahmadani, Nurul; Nurwati, Nurwati; Nurhasanah, Nurhasanah; Ghifari, Ghazi Al
Jurdimas (Jurnal Pengabdian Kepada Masyarakat) Royal Vol. 8 No. 3 (2025): Juli 2025
Publisher : STMIK Royal

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

Abstract

MSMEs have a major contribution to the national economy, but the use of information technology in this sector is still low. This community service activity aims to empower MSMEs in Silo Baru Village through the application of the Business Intelligence (BI) concept to improve the effectiveness of business management. The program is implemented in the form of training and technical assistance, which includes a basic understanding of BI, the use of simple accounting applications, digital marketing strategies, and data analysis and visualization techniques. This activity involves MSME actors directly in practice and simulations based on case studies of their respective businesses. Through a participatory and application approach, participants are equipped with the skills to record transactions digitally, monitor business performance, and make data-based decisions. Evaluation is carried out through pre-tests and post-tests, interviews, and observations, where the results show an increase in participants' digital literacy of up to 70% and technical skills of up to 60%. As many as 65% of participants have also implemented BI in daily business processes. This program is expected to be an effective collaborative model in encouraging the sustainable digital transformation of village MSMEs towards increasing competitiveness in the digital economy era.Keywords: MSME; data analysis; business intelligence; business management; digital    marketing  Abstrak: UMKM memiliki kontribusi besar terhadap perekonomian nasional, namun pemanfaatan teknologi informasi di sektor ini masih rendah. Kegiatan pengabdian ini bertujuan untuk memberdayakan UMKM di Desa Silo Baru melalui penerapan konsep Business Intelligence (BI) guna meningkatkan efektivitas manajemen usaha. Program dilaksanakan dalam bentuk pelatihan dan pendampingan teknis, yang mencakup pemahaman dasar BI, penggunaan aplikasi akuntansi sederhana, strategi pemasaran digital, serta teknik analisis dan visualisasi data. Kegiatan ini melibatkan pelaku UMKM secara langsung dalam praktik dan simulasi berbasis studi kasus usaha masing-masing. Melalui pendekatan partisipatif dan aplikatif, peserta dibekali keterampilan untuk mencatat transaksi secara digital, memantau kinerja usaha, serta mengambil keputusan berbasis data. Evaluasi dilakukan melalui pre-test dan post-test, wawancara, serta observasi, dimana hasilnya menunjukkan peningkatan literasi digital peserta hingga 70% dan keterampilan teknis hingga 60%. Sebanyak 65% peserta juga telah mengimplementasikan BI dalam proses bisnis sehari-hari. Program ini diharapkan dapat menjadi model kolaboratif yang efektif dalam mendorong transformasi digital UMKM desa secara berkelanjutan menuju peningkatan daya saing di era ekonomi digital.Kata kunci: UMKM; analisis data; business intelligence; manajemen bisnis; pemasaran digital
تأثير استخدام وسيلة صندوق القراءة على مهارة القراءة الطّلّاب بمدرسة الثّانويّة الحكوميّة ۲ بادنج بنجانج Rahmadani, Nurul; Febrianta, Rita; Anas, Al Baihaqi; Yusra, Oktarina
لســـانـنــا (LISANUNA): Jurnal Ilmu Bahasa Arab dan Pembelajarannya Vol. 13 No. 1 (2023): لســـانـنــا (LISANUNA): Jurnal Ilmu Bahasa Arab dan Pembelajarannya (JANUARI-
Publisher : Fakultas Tarbiyah dan keguruan- UIN Ar-Raniry

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22373/ls.v13i1.18054

Abstract

There are several problems in learning Arabic, namely the teacher does not use different learning media in teaching, especially in reading skills. It will be more interesting if the teacher is creative in using different media, so that it can increase students' enthusiasm and motivate them in learning. The problem is, teachers still have difficulty developing many Arabic learning media that suit the needs of students. The researcher decided to examine the effect of reading box media (a different method than usual) on students' reading abilities. Researchers use experimental research methods because researchers will look for the effect of certain treatments on others in the subjects held. This means looking for the effect of using reading box media on students' reading skills. The number of the research community consisted of 17 students, and the researchers took a random sample in this thesis, namely 17 students. Then the research instrument is observation, test. The researcher used reading box media in the experimental class to understand the text of reading skills in eleventh grade Arabic lessons well and fluently with an average score of 87.76, and in the control class with an average score of 80.06. . The result of calculating T (2.263) is greater than T table (2.037). The researcher concludes that the null hypothesis is rejected and the alternative hypothesis is accepted.
PENERAPAN ALGORITMA NAVE BAYES DALAM PENENTUAN KELAYAKAN PENERIMA BANTUAN PROGRAM KELUARGA HARAPAN Rahmadani, Nurul; Risnawati, Risnawati; Sena, Maulana Dwi
JURNAL TEKNISI Vol 3, No 2 (2023): Agustus 2023
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/teknisi.v3i2.1391

Abstract

Abstract: The Family Hope Program (PKH) aims to improve living standards through education, health and social welfare services. However, the process of selecting beneficiaries is often considered not to be on target and a long process, so a decision-making system is needed in determining the eligibility of the right beneficiaries of the Family Hope Program. This study aims to determine the feasibility of beneficiaries of the Family Hope Program in Petatal Village, Batubara Regency using the Nave Bayes method. The amount of data used in this research is 100 training data and 20 testing data with 8 criteria. The application of the Nave Bayes method in this study obtained an accuracy rate of 100% and an error rate of 0% using Rapid Miner and the Confusion Matrix technique.Keywords: classification; family hope program; nave bayes, PKHAbstrak: Program Keluarga Harapan (PKH) bertujuan untuk meningkatkan taraf hidup melalui layanan pendidikan, kesehatan, dan kesejahteraan sosial. Akan tetapi, dalam proses pemilihan penerimanya seringkali dianggap tidak tepat sasaran dan proses yang lama, sehingga, diperlukan sistem pengambilan keputusan dalam menentukan kelayakan penerima bantuan Program Keluarga Harapan yang tepat. Penelitian ini bertujuan untuk menentukan kelayakan penerima bantuan Program Keluarga Harapan di Desa Petatal, Kabupaten Batubara dengan menggunakan metode Nave Bayes. Jumlah data yang digunakan dalam penelitian ini sebanyak 100 data training dan 20 data testing dengan 8 kriteria. Penerapan metode Nave Bayes dalam penelitian ini memperoleh tingkat akurasi sebesar 100% dan tingkat error 0% dengan menggunakan Rapid Miner dan teknik Confusion Matrix.Kata Kunci: klasifikasi; nave bayes; PKH; program keluarga harapan
Sales Improvement through Web-based CRM Implementation Gunawan, Aditya; Rahmadani, Nurul; Lubis, Iin Almeina
Sistemasi: Jurnal Sistem Informasi Vol 13, No 2 (2024): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v13i2.4032

Abstract

This research focuses on the implementation of Customer Relationship Management (CRM) at Gucci 3 Bunut Store, which is engaged in the leather products industry such as sandals, shoes, and others. The challenges faced by this store in managing sales, marketing, and customer service motivate the design of an effective and efficient CRM system. The CRM used in this research is an operational CRM that focuses on automating the sales and customer service processes. Qualitative research methods, through interviews and observations, were used to understand the needs of customers, employees, and related parties. CRM application development was carried out using the PHP programming language and MySQL database. The research objective was to improve the efficiency and convenience of customer interaction. The implementation results show the ease of obtaining product information and facilitating the ordering process. The implications include increased operational and service efficiency, potentially increasing customer loyalty. This research contributes to the understanding of CRM implementation in the retail sector, creates innovative solutions for Gucci 3 Bunut Store, and supports the improvement of service quality and customer satisfaction.
Clustering Analysis Of Toddler Nutritional Status Using The K-Means Method On Posyandu Data Nanda, Yurizka Sri; Rahmadani, Nurul; Muhazir, Ahmad
JURNAL RISET KOMPUTER (JURIKOM) Vol. 12 No. 4 (2025): Agustus 2025
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v12i4.8947

Abstract

The issue of toddler nutritional status remains a serious concern because it can affect children's health and development, including the risk of stunting and cognitive impairment. At the Tanjung Asri Village Health Center, nutritional status is still recorded manually, which is inefficient and prone to classification errors. This study aims to develop a system for classifying the nutritional status of infants using the K-Means Clustering method based on desktop software to simplify the classification of nutritional status into three categories: malnourished, moderately nourished, and well-nourished. This study uses a quantitative approach with primary data from 100 infants collected through observation and interviews in May and June 2025. The clustering process was performed using RapidMiner with the parameter k = 3. The test results showed that the K-Means method was able to produce accurate centroid centers consistent with manual results. In May 2025, there were 22 infants with poor nutrition, 21 infants with moderate nutrition, and 7 infants with good nutrition, while in June 2025, there were 27 infants with poor nutrition, 8 infants with moderate nutrition, and 15 infants with good nutrition. The developed system has proven effective in supporting the classification and monitoring of infant nutritional status in a more objective and efficient manner.
APPLICATION OF MULTIPLE LINEAR REGRESSION ESTIMATING THE POPULATION OF ASAHAN REGENCY Azhara, Tasya; Rahmadani, Nurul; Nata, Andri
JURTEKSI (jurnal Teknologi dan Sistem Informasi) Vol. 10 No. 1 (2023): Desember 2023
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Royal Kisaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurteksi.v10i1.2466

Abstract

Abstract: Population is a group of people who live or settle in an area for six months or more. Increasing the population in an area results in more problems being faced by the area such as high unemployment rates, poverty and food shortages which result in hunger. BPS Asahan Regency records that there is an increase in population every year. Asahan Regency BPS cannot predict population growth in the following year, so an application is needed to predict population growth. The purpose of this study is to predict population growth in Asahan Regency in the following year based on previous data using the concept of data mining. By applying data mining using multiple linear regression methods can be used to calculate population growth estimates based on previous data. This quantitative research used population data of Asahan Regency from 2016 to 2022. From the calculation of the multiple linear regression model using data from the previous five years, the estimated population growth of Asahan for 2023 was 824,617 people and the process of estimating the population became more systematic and calculated. well with this population estimation system and the process of storing data becomes easier and does not require a lot of paper to print and save.            Keywords: Application; Data Mining; Multiple Linear Regression  Abstrak: Penduduk merupakan sekumpulan orang yang tinggal atau menetap pada suatu wilayah selama enam bulan atau lebih. Bertambahnya jumlah penduduk pada suatu daerah mengakibatkan semakin banyak pula persoalan yang di hadapi oleh daerah tersebut seperti tingkat pengangguran yang tinggi, kemiskinan dan kekurangan pangan yang mengakibatkan kelaparan. BPS Kabupaten Asahan mencatat terjadi adanya pertambahan penduduk pada setiap tahunnya. BPS Kabupaten Asahan tidak dapat memprediksi pertumbuhan penduduk pada tahun berikutnya sehingga dibutuhkan suatu aplikasi untuk memprediksi pertambahan penduduk tersebut. Tujuan penelitian ini adalah untuk memprediksi pertumbuhan penduduk Kabupaten Asahan pada tahun berikutnya berdasarkan data sebelumnya menggunakan konsep data mining. Dengan menerapkan data mining menggunakan metode regresi linier berganda dapat digunakan untuk menghitung estimasi pertumbuhan penduduk berdasarkan data sebelumnya.  Penelitian yang dilakukan secara kuantitatif ini menggunakan data penduduk Kabupaten Asahan dari tahun 2016 sampai tahun 2022. Dari perhitungan model regresi linier berganda menggunakan data lima tahun sebelumnya didapat estimasi pertumbuhan penduduk Asahan untuk tahun 2023 sebesar 824.617 jiwa dan proses estimasi jumlah penduduk menjadi lebih sistematis dan terkalkulasi dengan baik dengan adanya sistem estimasi jumlah penduduk ini dan proses penyimpanan data menjadi lebih mudah dan tidak memerlukan banyak kertas untuk di cetak dan di simpan. Kata kunci: Aplikasi; Data Mining; Regresi Linier Berganda
PREDICTION OF ON-TIME GRADUATION OF UNIVERSITAS ROYAL STUDENTS USING MULTIPLE LINEAR REGRESSION METHOD Rahmadani, Nurul; Kurniawan, Edi; Nurhasanah, Nurhasanah; Damanik, Wahdan
JURTEKSI (jurnal Teknologi dan Sistem Informasi) Vol. 11 No. 3 (2025): Juni 2025
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Royal Kisaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurteksi.v11i3.3893

Abstract

Abstract: On-time graduation is an important indicator in measuring the success of higher education and reflects the effectiveness of the academic process in higher education. Royal University, especially the Information Systems Study Program, still faces challenges in increasing the percentage of students who graduate on time. This study aims to identify factors that influence students' on-time graduation and build a prediction model using the multiple linear regression method. This method was chosen because it is able to analyze the simultaneous influence of several independent numeric variables on one dependent variable, making it suitable for studying the complex relationship between factors that influence student graduation. The independent variables analyzed in this study include GPA, parental income, and student part-time jobs with student graduation as the dependent variable. The results showed that parental income and part-time jobs had a significant positive effect on on-time graduation, while GPA had a negative effect. The model built had an R² value of 0.6153 and a standard error of 4.0653, indicating that the model was quite strong and accurate. These findings recommend Universitas Royal to strengthen the academic monitoring system and support working students, as well as design policies based on students' socio-economic conditions to increase the on-time graduation rate.Keywords: multiple linear regression; on-time graduation; students.  Abstrak: Kelulusan tepat waktu merupakan indikator penting dalam mengukur keberhasilan pendidikan tinggi serta mencerminkan efektivitas proses akademik di perguruan tinggi. Universitas Royal, khususnya Program Studi Sistem Informasi, masih menghadapi tantangan dalam meningkatkan persentase mahasiswa yang lulus tepat waktu. Penelitian ini bertujuan untuk mengidentifikasi faktor-faktor yang memengaruhi kelulusan tepat waktu mahasiswa serta membangun model prediksi menggunakan metode regresi linear berganda. Metode ini dipilih karena mampu menganalisis pengaruh simultan beberapa variabel independen numerik terhadap satu variabel dependen, sehingga sesuai untuk mengkaji hubungan kompleks antar faktor yang memengaruhi kelulusan mahasiswa. Variabel independen yang dianalisis dalam penelitian ini meliputi IPK, penghasilan orangtua, dan pekerjaan sambilan mahasiswa dengan kelulusan mahasiswa sebagai variabel dependen. Hasil penelitian menunjukkan bahwa penghasilan orangtua dan pekerjaan sambilan berpengaruh positif signifikan terhadap kelulusan tepat waktu, sedangkan IPK justru memiliki pengaruh negatif. Model yang dibangun memiliki nilai R² sebesar 0,6153 dan standar error 4,0653, menandakan model cukup kuat dan akurat. Temuan ini merekomendasikan Universitas Royal untuk memperkuat sistem monitoring akademik dan mendukung mahasiswa yang bekerja, serta merancang kebijakan berbasis kondisi sosial-ekonomi mahasiswa guna meningkatkan angka kelulusan tepat waktu.Kata kunci: kelulusan tepat waktu; mahasiswa; regresi linear berganda.
Peran Machine Learning Dalam Pembelajaran Di LKP Bintang Mulia Batu Bara Rahmadani, Nurul; Kurniawan, Edi; Risnawati, Risnawati
Jurdimas (Jurnal Pengabdian Kepada Masyarakat) Royal Vol. 6 No. 3 (2023): Juli 2023
Publisher : STMIK Royal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurdimas.v6i3.2479

Abstract

LKP Bintang Mulia Batu Bara is located in a coastal area which resulted in the guidance participants not being updated on technological advances in the education sector. Even though the times have been very advanced with one of the newest innovations, namely Machine Learning. Machine Learning in the field of education can provide a variety of learning options, so that students can find what is best for them, taking into account the differences of each individual student. Machine Learning can also be used to monitor learning processes that confuse students, so that Machine Learning in education runs in harmony with what students need. The purpose of doing this service is to broaden students' understanding of the role of Machine Learning in learning. This service was held on April 15, 2023, and the participants in this activity were 8 LKP guidance students. So the result of this dedication is that there are many roles that Machine Learning can play in learning, such as playing a role in learning content, the teaching process, giving assignments, the assessment process, and monitoring student learning progress. Keywords: education; learning; Machine LearningAbstrak:  LKP Bintang Mulia Batu Bara terletak di daerah pesisir pantai yang mengakibatkan para peserta bimbingan tidak update mengenai kemajuan teknologi di bidang pendidikan. Padahal perkembangan zaman sudah sangat maju dengan salah satu inovasi terbaru, yaitu Machine Learning. Machine Learning di bidang pendidikan dapat memberikan berbagai pilihan pembelajaran, sehingga siswa dapat menemukan apa yang terbaik bagi mereka, dengan mempertimbangkan perbedaan tiap individu siswa. Machine Learning juga dapat digunakan untuk memonitoring proses pembelajaran yang membingungkan siswa, sehingga Machine Learning dalam pendidikan berjalan selaras dengan yang dibutuhkan siswa. Tujuan dilakukannya pengabdian ini ialah untuk memperluas pemahaman siswa mengenai peran Machine Learning dalam pembelajaran. Pengabdian ini dilaksanakan pada tanggal 15 April 2023, dan yang menjadi peserta dalam kegiatan ini ialah para siswa-siswi bimbingan LKP yang berjumlah 8 orang. Maka hasil dari pengabdian ini ialah banyak peran yang dapat dilakukan Machine Learning dalam pembelajaran, seperti berperan dalam konten pembelajaran, proses pengajaran, pemberian tugas, proses penilaian, serta memantau kemajuan belajar para siswa.Kata kunci: Machine Learning; pembelajaran; pendidikan 
Co-Authors Abda Abda Aditya Gunawan, Aditya AMELIA, NUR Anas, Al Baihaqi Apriliani Ari Putra Arini, Diatri Arditia Arsyabil, Trisya Azhara, Tasya Azmi, Winda Br Str, Adinda Tiara Damanik, Wahdan Damayanti, Sapna Dwi Yuniarti, Wenty Edi Kurniawan Eva Lestari Fitri Yeni, Fitri Ghifari, Ghazi Al Herrin, Paquita Jafier Husnarika Febriani, Husnarika Hutasuhut, Melfa Aisyah Idhasari Jumailis, Mutia Fitri Khothibul Umam Lubis, Iin Almeina Maharani, Dea Maharani, Putri Zakiyah Maison, Witra Manda Sari Marpaung, Nasrun Maya Rini Handayani Muhazir, Ahmad Nanda, Yurizka Sri Nasrun Marpaung Nata, Andri Nurdiana Nurhaliza Nurhasanah Nurhasanah Nurhasanah Nurhasanah Nurjannah Nurwati Nurwati Panjaitan, Arya Armando Putri, Rita Dwi Rahma, Indah Risnawati Risnawati Rita Febrianta Rohminatin, Rohminatin Roihatul Jannah, Hilda Sena, Maulana Dwi Sumantri Sumantri Suparmadi Suparmadi, Suparmadi Suryani, Linda Syafnur, Afdhal Tasya, Puja Islami Widyanti, Maya Yusra, Oktarina