Article Per Year (5 Year)
p-Index From 2021 - 2026
1.066
P-Index
This Author published in this journals
All Journal JURIKOM (Jurnal Riset Komputer) Jurnal Pengabdian kepada Masyarakat Almantiq Karsa Bhakti : Journal of Community Service
Dwi Issadari Hastuti
Unknown Affiliation
Religion Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Environmental Science Languange, Linguistic, Communication & Media Public Health Social Sciences Other

Published : 6 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 6 Documents
Search

 1 
Pengelompokan Siswa Smk Diponegoro Berdasarkan Kedisiplinan Pembayaran Spp Menggunakan Algoritma K-Nearest Neighbors Entropy Azizah, Umi; Hastuti, Dwi Issadari; sahri, sahri
Multidisciplinary Applications of Quantum Information Science (Al-Mantiq) Vol. 5 No. 2 (2025): Multidisciplinary Applications of Quantum Information Science (Al-Mantiq)
Publisher : Al-Mantiq

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32665/almantiq.v5i2.5313

Abstract

Discipline in the payment of tuition fees is an important aspect of school financial management, especially in private educational institutions. This research aims to optimize student grouping based on tuition payment discipline by applying the K-Nearest Neighbors (K-NN) algorithm integrated with the Entropy method as a feature weighting technique. The data used is historical data of tuition payments of students of SMK Diponegoro with attributes such as gender, number of siblings, profession and salary of parents, and status of aid recipients. After going through the preprocessing and normalization stages, the K-NN algorithm is applied with a value of K = 10 and distance calculation using Euclidean Distance. Test results with confusion matrix show an accuracy of 75.86%, recall 80%, and precision 61.54%. This proves that the K-NN algorithm optimized with the Entropy method is quite effective in classifying students into the “Right” or “Late” category in paying tuition fees.
Analisis Penerapan Program Customer Reward Menggunakan K-Means Barata, Mula; Novitasari, Dwi Tiyas Novitasari; Hastuti, Dwi Issadari; Rochmatin, Novia Nur; Muzakka, Mochammad Arifuddin; Andiyani, Putri
Multidisciplinary Applications of Quantum Information Science (Al-Mantiq) Vol. 4 No. 1 (2024): Multidisciplinary Applications of Quantum Information Science (Al-Mantiq)
Publisher : Al-Mantiq

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32665/almantiq.v4i1.2698

Abstract

Penelitian ini bertujuan menganalisis konsumen untuk memberikan program reward berdasarkan kepuasan dan loyalitas mereka dalam pusat perbelanjaan [Mall]. Penelitian dilakukan dengan cara mengumpulkan data, kemudian menganalisis hasilnya menggunakan metode clustering yang relevan. Analisis regresi menunjukkan hubungan yang kuat antara variabel-variabel tersebut, dan penelitian ini memberikan bukti kuat untuk pusat perbelanjaan [mall] dan perusahaan sejenis, supaya menggunakan metode ini untuk meningkatkan kepuasan pelanggan mereka. Hasil ini dapat membantu perusahaan dalam merancang strategi reward yang lebih efektif dan sesuai dengan preferensi konsumen. Penelitian ini memberikan kontribusi pada literatur tentang manajemen customer dan strategi pemasaran dengan menyelidiki peran mereka dalam meningkatkan kepuasan dan loyalitas . Implikasi praktis dari penelitian ini dapat membantu perusahaan untuk memaksimalkan manfaat dari investasi mereka dalam program reward, dengan memastikan bahwa program tersebut tidak hanya menarik bagi customer tetapi juga efektif dalam menciptakan loyalitas jangka panjang.
PEMANFAATAN ARTIFICIAL INTELLIGENCE DALAM PEMBELAJARAN DASAR: HASIL PENGABDIAN DI MI PLUS AL-FATIMAH BOJONEGORO Ita Aristia Sa’ida; Guruh Putro Dirgantoro; Dwi Issadari Hastuti; Niken Sukmawati; Elsa Azia Ulhaq
J-ABDI: Jurnal Pengabdian kepada Masyarakat Vol. 5 No. 6 (2025): Nopember 2025
Publisher : Bajang Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53625/jabdi.v5i6.11805

Abstract

The rapid development of Artificial Intelligence (AI) offers significant opportunities to enhance the quality of learning, particularly at the elementary and madrasah levels. However, teachers’limited digital literacy and lack of experience in utilizing AI-based tools often hinder the integration of technology into classroom practices. This community service program aims to strengthen teachers’ competencies in implementing AI to support teaching and learning at MI Plus Al-Fatimah, Bojonegoro. The program was conducted through four stages: socialization, training, classroom implementation with mentoring, and evaluation. Various AI-based teaching products were produced, including digital learning materials, interactive assessments, infographics, and instructional videos. Evaluation results show a substantial improvement in teachers’ digital literacy and confidence, with an average increase of 65% between pre-test and post-test scores. Teachers reported that AI tools improved efficiency in preparing teaching materials, enhanced classroom engagement, and helped diversify instructional strategies. This program demonstrates that AI integration can serve as an effective capacity-building mechanism for teachers, promoting innovative, adaptive, and technology-driven learning environments. The findings suggest that continuous training, infrastructural support, and clear implementation guidelines are necessary to sustain AI adoption in schools and broaden its impact across educational settings.
Pemberdayaan UMKM Melalui Pelatihan Olahan Keripik Gedebog Pisang sebagai Produk Unggulan Lokal Dwi Issadari Hastuti
Karsa Bhakti : Journal of Community Service Vol 1 No 1 (2025): Karsa Bhakti : Journal of Community Service
Publisher : CV. Agrapana Media

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65789/kb-jocs.v1i1.14

Abstract

Kegiatan pengabdian kepada masyarakat ini bertujuan untuk meningkatkan keterampilan dan pengetahuan warga Desa Sidorejo, Kecamatan Padangan, Kabupaten Bojonegoro dalam mengolah bahan lokal menjadi produk bernilai ekonomi. Melimpahnya tanaman pisang di wilayah tersebut mendorong dilakukannya pelatihan pembuatan keripik gedebog pisang sebagai inovasi pemanfaatan limbah pertanian. Metode pelaksanaan meliputi sosialisasi dan penyuluhan tentang potensi ekonomi lokal, pelatihan praktik langsung pembuatan keripik, serta evaluasi hasil melalui pre-test dan post-test. Hasil kegiatan menunjukkan adanya peningkatan signifikan dalam aspek pengetahuan, keterampilan teknis, dan motivasi kewirausahaan masyarakat, dengan rata-rata peningkatan sebesar 70%. Peserta mampu menghasilkan produk olahan yang berkualitas, memiliki daya saing, serta berpotensi menjadi usaha rumah tangga yang berkelanjutan. Kegiatan ini tidak hanya memberikan dampak ekonomi, tetapi juga memperkuat semangat kolaboratif dan kemandirian masyarakat dalam mengembangkan UMKM berbasis sumber daya lokal.
Penguatan Literasi dan Numerasi Melalui Pembelajaran Interaktif di SDN Sidorejo Dwi Issadari Hastuti
Karsa Bhakti : Journal of Community Service Vol 1 No 2 (2025): Karsa Bhakti : Journal of Community Service
Publisher : CV. Agrapana Media

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65789/kb-jocs.v1i2.23

Abstract

This community service activity aims to improve the literacy and numeracy skills of elementary school students through an interactive and enjoyable learning approach. The program is carried out at SDN Sidorejo, involving lecturers, students, and school teachers as collaborative partners. The main issues faced are the low reading interest of students and difficulties in understanding basic arithmetic operations. The implementation method is conducted in three stages: planning, execution, and evaluation. In the planning stage, the team conducts a needs analysis and prepares learning media in the form of picture books, number cards, and educational games. The execution stage includes activities such as reading together, educational storytelling, and numeracy games like 'Quick Number Guess' and 'Math Puzzle' designed to foster students' enthusiasm for learning. Evaluation was conducted through pre-tests and post-tests to measure the effectiveness of the activities in improving students' abilities. The results showed an increase in the average literacy score from 63 to 84 and numeracy from 58 to 81, amounting to an improvement of 21% and 23%, respectively. In addition to having a positive impact on enhancing students' competencies, these activities also enriched teachers' insights in developing creative teaching methods that can be implemented sustainably. Thus, this community service activity successfully created an active, collaborative, and enjoyable learning environment and contributed to strengthening literacy and numeracy culture at the elementary school level.
Perbandingan Algoritma Machine Learning untuk Klasifikasi Kopi Menggunakan Data Sensor Electronic Nose dan Tongue Dwi Issadari Hastuti; Mula Agung Barata; Ifnu Wisma Dwi Prastya
JURNAL RISET KOMPUTER (JURIKOM) Vol. 13 No. 1 (2026): Februari 2026
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v13i1.9349

Abstract

Coffee is a leading Indonesian commodity with a diversity of aromas and flavors influenced by variety and region of origin. However, the process of identifying and classifying coffee types is still often carried out conventionally through sensory testing, which is subjective, time-consuming, and dependent on panelist expertise. This situation encourages the need for a more objective and consistent automated approach based on sensor technology and machine learning. This study aims to compare the performance of several machine learning algorithms, namely Logistic Regression, Support Vector Classifier (SVC), and Random Forest, in classifying Indonesian coffee types using multisensor Electronic Nose and Electronic Tongue data. The data used comes from gas, temperature, and pH sensors with a total of 1,503 samples representing ten coffee classes. The preprocessing stage includes data cleaning using the Interquartile Range (IQR) method to remove outliers and noise reduction using the Moving Average method. The results show that the application of data cleaning and noise reduction significantly improves the performance of all classification models. Among the algorithms tested, Random Forest showed the most stable and superior performance in classifying coffee types. These findings confirm that the combination of appropriate data preprocessing and appropriate algorithm selection plays a crucial role in improving the accuracy of machine learning-based coffee classification systems.
Co-Authors Andiyani, Putri Barata, Mula Elsa Azia Ulhaq Guruh Putro Dirgantoro Ifnu Wisma Dwi Prastya Ita Aristia Sa'ida Mula Agung Barata Muzakka, Mochammad Arifuddin Niken Sukmawati Novitasari, Dwi Tiyas Novitasari Rochmatin, Novia Nur Sahri Sahri Umi Azizah, Umi