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All Journal Jurnal Transformatika Journal of Natural Sciences and Mathematics Research Vision: Journal for Language and Foreign Language Learning Phenomenon : Jurnal Pendidikan MIPA SINTECH (Science and Information Technology) Journal Jurnal Sisfokom (Sistem Informasi dan Komputer) JSiI (Jurnal Sistem Informasi) IJID (International Journal on Informatics for Development) JURIKOM (Jurnal Riset Komputer) EDUMATIC: Jurnal Pendidikan Informatika Aiti: Jurnal Teknologi Informasi TEPIAN Jurnal Teknik Informatika (JUTIF) Walisongo Journal of Information Technology
Wenty Dwi Yuniarti, Wenty Dwi
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Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Materials Science & Nanotechnology Mathematics Physics

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The Study of Iron Metal (Fe) Content in Water Morning Glory Plants (Ipomoea Aquatica Forsk) using Atomic Absorption Spectrophotometry (AAS) Method Kholifah, Khusnul; Fadllan, Andi; Yuniarti, Wenty Dwi
Journal Of Natural Sciences And Mathematics Research Vol 1, No 2 (2015): Volume 1, Nomor 2, 2015
Publisher : Faculty of Science and Technology, State Islamic University Walisongo Central Java

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21580/jnsmr.2015.1.2.1621

Abstract

There are several hazardous material compounds in water morning glory that cannot be consumed. This study aimed to Fe content in water morning glory taken from different locations using Atomic Absorption Spectrophotometry (AAS) method. The data were acquired through documentation method, observational method and experimental method. All of the data were analysed by quantitative approach and descriptive analysis. The number of samples taken was 3 pieces of water morning glory per location. From the AAS method, the results showed that Fe concentrations in all samples varied. The average of Fe content in water taken from Industrial area was 0,258 ppm, from green house was 0 ppm, and from rural area was 0,175 ppm. The numbers of Fe content in water morning glory taken from industrial area were 10,78 ppm, 9,0 ppm, 9,3 ppm; from green house were 1,9 ppm, 4,4 ppm, 2,4 ppm; and from rural area were 6,4 ppm, 4,94 ppm, 4,98 ppm. The results of the study showed that Fe content in water or water morning glory taken from green house and rural area was below the threshold level of metal contamination, meanwhile in industrial area, the Fe content was almost approaching the threshold level of metal contamination. In the industrial area, the water morning glory could be used to reduce water pollution, not as food sources because of the high content of Fe. Meanwhile, in green house and rural area, water morning glory might be consumed by people because of the low content of Fe. © 2015 JNSMR UIN Walisongo. All rights reserved.
Mind Map Kolaboratif Memanfaatkan Groupware Berbasis Cloud Storage Yuniarti, Wenty Dwi
Phenomenon : Jurnal Pendidikan MIPA Vol 6, No 1 (2016): Jurnal Pendidikan MIPA
Publisher : Sains and Technology Faculty, Walisongo State Islamic University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21580/phen.2016.6.1.948

Abstract

Groupware adalah aplikasi atau perangkat lunak komputer yang dirancang untuk mendukung kolaborasi dari beberapa pengguna (Alan Dix dkk, 2004: 663). Saat ini groupware berkembang, bukan sekedar sebagai perangkat lunak multi user yang dapat mengakses data sama, berbagi dokumen atau rich-media, namun dengan teknologi cloud storage, groupware mendukung penyimpanan dokumen secara online sebagai artifak atau hasil kerja kolaboratif.Dalam pembelajaran, kolaborasi diwujudkan dengan kelompok atau kelompok kecil siswa, berinteraksi, terkoordinasi dan memungkinkan mengeksplorasi secara bersama suatu permasalahan atau tugas bermakna dalam semua fungsi proses pembelajaran. Salah satu elemen penting dalam fungsi proses pembelajaran adalah ketrampilan siswa dalam mengorganisasikan pengetahuan dan informasi. Ada beberapa cara yang dapat dilakukan guru dalam menfasilitasi tumbuhnya ketrampilan tersebut. Selain teknik mencatat, pendekatan mind map tau peta pikiran dapat digunakan menfasilitasi siswa dalam pengorganisasian informasi sehingga mempermudah pemahaman siswa atas suatu topik yang berjumlah banyak dengan waktu terbatas. Cara baru yang lebih modern dalam menfasilitasi pengorganisasian informasi adalah menggunakan groupware.Kajian ini membahas pemanfaatan groupware MindMup 2.0 untuk mengorganisasikan pengetahuan topik cabang ilmu elektronika menurut aturan Law of Mind Map,  dilakukan dalam kelompok kecil, dalam pembahasan ini dilakukan oleh empat siswa, dilakukan secara kolaboratif, sinkronous, tanpa friksi (zero friction) dengan dukungan teknologi cloud storage, Google Drive.
Identifikasi Potensi Keberhasilan Studi Menggunakan Naïve Bayes Classifier Yuniarti, Wenty Dwi; Faiz, Achmad Nur; Setiawan, Bagus
Walisongo Journal of Information Technology Vol 2, No 1 (2020): Walisongo Journal of Information Technology
Publisher : Universitas Islam Negeri Walisongo Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21580/wjit.2020.2.1.5204

Abstract

Penelitian ini bertujuan melakukan prediksi keberhasilan studi dengan metode klasifikasi naïve bayes classifier. Varibel input yang diperkirakan mempengaruhi keberhasilan studi adalah Jalur Masuk (1), Asal Kota (2), Asal Provinsi (3), Penghasilan Orang Tua (4), Pekerjaan Orang Tua (5), Indeks Prestasi Kumulatif (6) serta Riwayat Status Mahasiswa (7). Pengetahuan potensi keberhasilan studi diperoleh dari variasi empat variabel target (class) yaitu IPK Tahun Pertama dan Kedua, Status Mahasiswa Terkini, IPK Mata Kuliah (Makul) Non-Keprodian serta IPK Makul Keprodian. Proses diawali data preprocessing dan diperoleh 5.934 data bersih. Data dibagi 80% training, 20% testing, dengan Correctly Classified Instances 97,53%. Penggalian pengetahuan dengan naïve bayes classifier memperoleh akurasi 99,41% untuk prediksi variabel input 1,2,3,4,5,6,7 dengan target keberhasilan IPK Tahun pertama dan kedua, 96.96 %, untuk target Status Mahasiswa Terkini, 95.87% untuk target IPK Makul Keprodian, dan 97.89 % untuk target IPK Makul Non-Keprodian. Penggunaan metode naïve bayes classifier dalam klasifikasi potensi keberhasilan studi ini memberikan akurasi 95.8% sampai dengan 99.41% untuk 4 target berbeda.  Bagi perguruan tinggi, perlu penguatan pada proses perekrutan mahasiswa, serta perlu diperhatikan bahwa faktor ekonomi orang tua memberikan andil bagi kelangsungan proses studi.
UTILIZING LEARNING PLATFORM FOR PAPERLESS CLASSROOM Yuniarti, Wenty Dwi
Vision: Journal for Language and Foreign Language Learning Vol 3, No 2 (2014)
Publisher : Faculty of Education and Teacher Training, Universitas Islam Negeri Walisongo Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21580/vjv3i2295

Abstract

Technology, in the present time, has been integrated in a variety of human activities, not least in learning. Learning platform provides the integration of technology-based learning environment. Learning platform places technology as “substitute” for a variety of learning activities that previously had to be done manually and must be presented physically to any other form that the virtual tools while providing a social area in order to maintain the importance of the relationship between teacher and student.Through virtual tools, learning platforms provide a learning environment that models the interactions within the class as a whole starting from the preparation of lesson plans, presentation materials, use of media, assignments, group work, assessment, management of the rating value to students. Support for learning administrative aspects are available through the authorization feature and access scope management that aims to clarify the roles, forms of participation and the interaction process of each of group involved in the learning, both students, teachers and system administrators.The variety of learning platform is available either in the form of open source or limited use, either in the form of package systems such as Learning Management System via Moodle and cloud-based tools such as Google’s Classroom, etc. Haiku learning. The following section will describe the use of virtual tools in a learning platform for implementing learning environment as a whole. One thing that can not be avoided and instead be more value in the use of learning platforms are the creation of a new paradigm of learning without paper. Except giving a new form for efficient and optimal learning, in the perspective of the present paperless classroom certainly economical and environmentally friendly.
Opini Publik Pasca-Pemilihan Presiden: Eksplorasi Analisis Sentimen Media Sosial X Menggunakan SVM: Indonesia Adib, khoirul; Handayani, Maya Rini; Yuniarti, Wenty Dwi; Umam, Khotibul
SINTECH (Science and Information Technology) Journal Vol. 7 No. 2 (2024): SINTECH Journal Edition Agustus 2024
Publisher : Prahasta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/sintechjournal.v7i2.1581

Abstract

Pemilihan Presiden di Indonesia seringkali menjadi pemicu perubahan dramatis dalam dinamika opini publik, terutama di era digital yang dipenuhi dengan suara yang tersebar di media sosial. Penelitian ini bertujuan untuk memetakan perubahan sentimen publik pasca-pemilihan Presiden dengan menggunakan analisis media sosial, dengan fokus pada aplikasi X yang memiliki 24 juta pengguna aktif di Indonesia. Metode Support Vector Machine (SVM) digunakan untuk menganalisis dan mengklasifikasikan sentimen dengan akurat berdasarkan kata tweet yang sedang tren setelah pemilihan Presiden. Penelitian ini bertujuan untuk memberikan pemahaman yang lebih dalam tentang perubahan opini publik pasca-pemilihan presiden, dengan menggambarkan dinamika sentimen masyarakat yang tercermin dalam media sosial. Kontribusi dari penelitian ini adalah pemetaan yang akurat tentang perubahan opini publik, yang dapat memberikan wawasan yang berharga bagi pembuat kebijakan, analis politik, dan praktisi media sosial dalam merespons kebutuhan masyarakat di era digital ini. Hasil pengujian dengan menggunakan 3850 dengan karateristik dataset dengan menggunakan tiga kelas kata tweet yang sedang tren dari platform X menunjukkan tingkat akurasi tertinggi pada klasifikasi "Pemilu Damai" dengan 97.3%, "Hak Angket" dengan 96.5%, dan "Pemilu Curang" dengan 94.0%.
Sistem Pendukung Keputusan Penerima Bantuan Kartu Indonesia Pintar dengan Metode Weighted Product Yuniarti, Wenty Dwi; Damayanti, Laili Zanura; Nur'aini, Siti
Jurnal Transformatika Vol. 20 No. 2 (2023): January 2023
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v20i2.5877

Abstract

Education is a bridge to educate the nation s life. The government has launched various programs for equitable distribution and expansion of access to education, one of which is Program Indonesia Pintar (PIP). Smart Indonesia Card (KIP) is a marker for PIP recipients. The implementation of PIP is considered effective if KIP is given on target. SMK An Najah has implemented PIP. Each period, SMK An Najah faces many applicants with complex requirements documents. Unfortunately, the determination of KIP aid recipients is still done manually, so it takes a long time and has the potential for inaccurate targets. This study proposes the use of a computer-based decision support system using the Weighted Product (WP) method to determine KIP recipients. WP uses a multiplication technique to connect attributes ratings that have been raised to the power of weight. Based on the evaluation using User Acceptance Testing (UAT), it is known that the decision support program can be used with an acceptance rate of 79.15% or in the worthy category.
Analysis of Fuzzy Logic Modification for Student Assessment in e-Learning Wardoyo, Retantyo; Yuniarti, Wenty Dwi
IJID (International Journal on Informatics for Development) Vol. 9 No. 1 (2020): IJID June
Publisher : Faculty of Science and Technology, UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/ijid.2020.09105

Abstract

The phenomenon of the rapid transfer of learning to online systems, such as e-Learning, has occurred massively. Institutions must ensure that student assessments run well. The characteristics of learning in e-Learning require an appropriate assessment method. The fuzzy logic method can be an option. Research shows that fuzzy logic is capable of providing flexible and objective performance evaluation. Fuzzy logic is a method that can overcome the uncertainty of transparency and objectivity of student assessments. In general, fuzzy logic applications are carried out by standards. Modification is an attempt to reveal the flexibility and to optimize the use of fuzzy logic. This study presents an analysis of fuzzy logic modification for the assessment of Algorithm and Data Structures courses held in e-Learning. These modifications include (i) modification of the parameter score with score compatibility, (ii) consequent modification of the fuzzy rules and (iii) modification of the implication process. The study results show that although the use of fuzzy logic requires more complicated procedures and tools, it can present various kinds of assessment as an option for educators to assess students in e-Learning.
Identifikasi Polaritas Sikap Pengguna Aplikasi X terhadap Coretax di Indonesia Menggunakan Algoritma Naïve Bayes Prasilda, Dina Rahma; Yuniarti, Wenty Dwi; Handayani, Maya Rini; Umam, Khothibul
JURIKOM (Jurnal Riset Komputer) Vol 12, No 3 (2025): Juni 2025
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v12i3.8548

Abstract

The Core Tax Administration System (Coretax) was launched by the Directorate General of Taxes (DGT) in January 2025 as a technology-based integrated tax system. While its initial goal was to improve tax efficiency and compliance, Coretax faced technical challenges, including system errors, slow processing speed, and criticism from the public. The main platform used to address these challenges is the X app (formerly known as Twitter). This research aims to understand the public's views and responses to Coretax's services by analyzing user sentiment patterns seen on social media. The research identifies the polarity of user attitudes by utilizing natural language processing (NLP) and Naïve Bayes algorithms, applied to a dataset of 1,628 tweets collected between January and March 2025. The analyzed data reflects a wide range of public reactions that include both positive and negative opinions towards the Coretax implementation, both in terms of functionality and ease of use. The results show that the model has an accuracy rate of 93.07%, a precision value of 95%, a recall value of 96%, and an F1-Score value of 96%. The results of this study are expected to be able to provide precise mapping related to changes in public opinion towards Coretax, so that it can be a valuable source of information for application developers, policy makers in the field of taxation, and analysis in the technology sector in responding to the needs and expectations of society in the digital era.
Implementation of Enhanced Confix Stripping Stemming and Chi-Squared Feature Selection on Classification UIN Walisongo Website with Naïve Bayes Classifier Muhadzib Al-Faruq, Muhammad Naufal; Yuniarti, Wenty Dwi; Handayani, Maya Rini; Umam, Khotibul
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 3 (2025): JUTIF Volume 6, Number 3, Juni 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.3.4670

Abstract

Academic news classification on university websites remains a challenge due to the growing volume of content and lack of efficient categorization systems. At UIN Walisongo Semarang, this problem hinders students, faculty, and the public from easily accessing relevant information. This study aims to develop an automated academic news classification system to address this issue. We applied a Naïve Bayes Classifier model, enhanced with Term Frequency weighting, the Enhanced Confix Stripping Stemmer for Indonesian language preprocessing, and Chi-Squared feature selection to identify the most informative terms. The dataset consisted of 880 academic news articles from UIN Walisongo’s website, split into 704 training and 176 testing documents. The system achieved 95% accuracy on the test set. To evaluate generalizability, we used a separate evaluation set of 12 new articles, obtaining 83.3% accuracy. The preprocessing stage played a vital role in reducing morphological complexity, while Chi-Squared scoring improved the relevance of selected features. This research highlights the importance of robust text classification techniques in academic information systems, particularly in Indonesian language contexts where language morphology poses unique challenges. The proposed model demonstrates strong performance, scalability, and potential for integration into academic portals to improve information retrieval. This study contributes significantly to the field of Natural Language Processing and applied machine learning in academic settings, especially for Indonesian-language content. It provides an effective solution for automated academic content management in institutional information systems.
User Opinion Mining on the Maxim Application Reviews Using BERT-Base Multilingual Uncased Safitri, Sindy Eka; Yuniarti, Wenty Dwi; Handayani, Maya Rini; Umam, Khothibul
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol. 14 No. 3 (2025): JULY
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v14i3.2391

Abstract

Online transportation applications such as Maxim are increasingly used due to the convenience they offer in ordering services. As usage increases, the number of user reviews also grows, serving as a valuable source of information for evaluating customer satisfaction and service quality. Sentiment analysis of these reviews can help companies understand user perceptions and improve service quality. This study aims to analyze the sentiment of user reviews on the Maxim application using the BERT-Base Multilingual Uncased model. BERT was chosen for its ability to understand sentence context bidirectionally, and it has proven to outperform traditional models such as MultinomialNB and SVM in previous studies, with an accuracy of 75.6%. The dataset used consists of 10,000 user reviews with an imbalanced distribution: 4,000 negative, 2,000 neutral, and 4,000 positive reviews. The data was split into 90% training data (9,000 reviews) and 10% test data (1,000 reviews). From the 9,000 training data, 15% or 1,350 reviews were allocated as validation data, resulting in a final training set of 7,650 reviews. Evaluation results show that BERT is capable of classifying sentiment into three categories positive, neutral, and negative, with an accuracy of 94.7%. The highest F1-score was achieved in the positive class (0.9621), followed by the neutral class (0.9412), and the negative class (0.9246). The confusion matrix shows that most predictions match the actual labels. These findings indicate that BERT is an effective and reliable model for performing sentiment analysis on user reviews of online transportation applications such as Maxim.
Co-Authors Andi Fadllan Bagus Setiawan Damayanti, Laili Zanura Faiz, Achmad Nur Joan Angelina Widians, Joan Angelina Khoirul Adib Kholifah, Khusnul Khothibul Umam Khotibul Umam Maizaliyanti, Annisa Maya Rini Handayani Muhadzib Al-Faruq, Muhammad Naufal Muhammad Rafid Pratama Nur'Aini, Siti Prasilda, Dina Rahma Retantyo Wardoyo Safitri, Sindy Eka Tejawati, Andi Tsuroyya, Kamiliya Umam, Khothibulu