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All Journal PAWIYATAN Jurnal Transformatika Jurnal Informatika Upgris JOURNAL OF APPLIED INFORMATICS AND COMPUTING Fokus Ekonomi JURNAL TEKNOLOGI DAN OPEN SOURCE Building of Informatics, Technology and Science Indonesian Journal of Community Services Jurnal TIKOMSIN (Teknologi Informasi dan Komunikasi Sinar Nusantara) Jurnal Program Kemitraan dan Pengabdian Kepada Masyarakat Teknika Jurnal Publika Pengabdian Masyarakat Jurnal Pengabdian Mandiri J-ABDIPAMAS (Jurnal Pengabdian Kepada Masyarakat) Tematik Jurnal Ilmiah Informatika dan Komputer Jurnal Sarjana Ilmu Pendidikan Widya Teknik JUSS (Jurnal Sains dan Sistem Informasi)
Setyoningsih Wibowo
Universitas PGRI Semarang
Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Social Sciences Transportation Other

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KEBERMANFAATAN APLIKASI DAMARJATI BAGI PEMBELAJARAN BAHASA JAWA DI SEKOLAH MENENGAH ATAS DI JAWA TENGAH 'BENEFITS OF THE DAMARJATI APPLICATION FOR LEARNING JAVANES IN HIGH SCHOOLS IN CENTRAL JAVA ' Suyitno, Suyitno; Ngatmini, Ngatmini; Wibowo, Setyoningsih
Jurnal Sarjana Ilmu Pendidikan Vol 2, No 1 (2022): Jurnal Sarjana Ilmu Pendidikan
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/jsip.v2i1.8329

Abstract

The purpose of this study was to analyze user responses and describe the usefulness of the Damarjati application for learning Javanese SMA in Central Java Province. This research is part of development research that refers to the Borg and Gall development model. Research data in the form of student responses were obtained using a questionnaire instrument via google form. The data obtained were analyzed numerically with the percentage technique. The results showed: a) there were 426 (94%) respondents who stated that it was very useful and useful, 413 (92%) respondents stated that it was very easy and easy, 413 (92%) respondents stated that the application display Damarjati is very attractive and attractive to learning Javanese for SMA in Central Java Province; and b) in terms of its usefulness, the Damarjati application can be concluded that it is very useful, reaching a percentage of 94%.Keywords: usefulness, Damarjati application, learning, Javanese
Implementasi Aspal Emulsi Tipe CSS-1 Pada Tanah Lempung Merah Untuk Estimasi Daya Dukung Tanah Pondasi Dengan Metode Regresi Budirahardjo, Slamet; Hartanti, Lusia Permata Sari; Wibowo, Setyoningsih
Widya Teknik Vol. 23 No. 2 (2024): November-Profesi Insinyur
Publisher : Fakultas Teknik, Universitas Katolik Widya Mandala Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33508/wt.v23i2.6070

Abstract

Daerah BSB (Bukit Semarang Baru) Kota Semarang merupakan bagian Kota Semarang Propinsi Jawa Tengah, yang dalam pengembangan kedepannya akan dikembangkan sebagai kawasan industri, perumahan dan pusat perkantoran. Deskripsi daerah BSB merupakan daerah perbukitan, dimana tanahnya adalah tanah merah. Jalan Semarang – Boja merupakan salah satu jalan akses penghubung dari Kota Semarang, khususnya kawasan Semarang bawah menuju daerah BSB dan Mijen. Selain itu Jalan Semarang - Boja juga sebagai jalan alternatif bagi pengguna jalan yang akan menuju ke Kabupaten Kendal dan Kabupaten Semarang. Di lokasi Jalan Semarang – Boja ini sering dijumpai permasalahan kerusakan jalan berupa penurunan, lobang jalan dan pergeseran (sliding).Tujuan dilakukan penulisan implementasi pencampuran aspal emulsi pada tanah dasar (subgrade) di daerah BSB untuk mengetahui sifat asli tanah dasar (subgrade) pada lokasi penelitian, mengetahui ada tidaknya pengaruh pencampuran bahan aspal emulsi pada tanah dasar (subgrade) terhadap sifat tanah dasar asli dan untuk mengetahui besarnya daya dukung tanah pondasi dangkal akibat implementasi pencampuran bahan aspal emulsi kadar 3% dan 6% terhadap berat kering tanah serta masa pemeraman campuran tanah aspal emulsi selama 1 hari dan 3 hari.Metode pengujian tanah yang penulis gunakan merupakan pengujian campuran tanah aspal emulsi di laboratorium yang proses pelaksanaannya mengacu pada peraturan-peraturan SNI tentang uji tanah di laboratorium dan metode regresi yang selanjutnya digunakan untuk estimasi nilai yang diinginkan berdasarkan data-data hasil uji sampel di laboratorium.Hasil uji indek plastisitas sampel tanah asli di daerah BSB Kota Semarang menunjukkan sifat tanah yang mempunyai plastisitas sedang. Terjadinya peningkatan nilai daya dukung tanah pondasi jenis pondasi dangkal rata-rata lebih dari 50% akibat implementasi campuran aspal emulsi CSS-1 pada tanah asli. Implementasi aspal emulsi CSS-1 pada tanah lempung merah daerah BSB Kota Semarang memberikan efek peningkatan nilai daya dukung tanah pondasi jenis pondasi dangkal berbentuk bujur sangkar yang sangat signifikan.
Simulation of the effect of regenerator porosity on the performance of zero centrigade thermoacoustic cooler generated by the single-stage thermoacoustic machine for sustainable refrigeration Farikhah, Irna; Aldiansyah, Edo Putra; Khoiri, Nur; Ristanto, Sigit; Wibowo, Setyoningsih
Widya Teknik Vol. 23 No. 2 (2024): November-Profesi Insinyur
Publisher : Fakultas Teknik, Universitas Katolik Widya Mandala Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33508/wt.v23i2.6115

Abstract

Refrigeration systems are an essential need in everyday life. There are lots of modern industry that uses refrigerator for helps maintain temperature stability from overheating and prevents the product from drying out protected from dirt and insect attacks. However, the refrigeration system used in industry still uses a refrigeration system vapor compression and using chlorofluorocarbon (CFC) refrigerant and hydro-chlorofluorocarbons (HCFCs) which are harmful to the environment. Therefore, it requires thermoacoustic cooling generated by the engine single-stage thermoacoustic. This research was conducted numerically. In this research, the effects are simulated stack porosity on the performance of thermoacoustic cooling generated by a single-stage thermoacoustic machine at 0°C. the porosity was varied from 0.37 to 0.97. It was found that the stack porosity was optimal when the porosity is 0.97 and the performance of the cooler is 52 %. Moreover, the lowest heating temperature for the thermoacoustic machine is 217°C. This temperature can be used for waste heat recovery. 
Perbandingan Model Naïve Bayes, Logistic Regression, SVM, XGBoost, dan SVM-XGBoost untuk Analisis Sentimen Tunaiku Melapa, Yabes Aryanto; Wibowo, Setyoningsih; Sari, Nur Latifah Dwi Mutiara
Building of Informatics, Technology and Science (BITS) Vol 7 No 3 (2025): December 2025
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v7i3.8914

Abstract

Sentiment analysis is used to explore user perceptions of fintech services such as Tunaiku through the evaluation of customer reviews. This study specifically aims to compare the performance of several sentiment classification algorithms to determine the most optimal model for classifying Tunaiku app user reviews. The dataset used in this study is a collection of Tunaiku app user reviews obtained from the Google Play Store, with a total of 18,458 reviews. This study compares the performance of five classification algorithms, namely Naïve Bayes, Logistic Regression, Support Vector Machine (SVM), XGBoost, and a hybrid SVM-XGBoost model. The research stages include text preprocessing, feature extraction using TF-IDF, and the application of a validated classification model using the cross-validation method. Model performance evaluation is carried out based on accuracy, precision, recall, and F1-score metrics. The test results showed that Naïve Bayes (91.96%), Logistic Regression (92.81%), SVM (92.56%), and XGBoost (92.52%) provided good performance, while the hybrid SVM-XGBoost model produced the best performance with the highest accuracy of 93.05%. These findings indicate that the hybrid approach is more effective in analyzing user review sentiment and has the potential to be a basis for decision-making in improving Tunaiku's service quality according to user needs.
Classification of Melinjo Fruit Ripeness Using a Convolutional Neural Network (CNN) Based on Digital Images Kurniawan, Anggi Ade; Wibowo, Setyoningsih; Mutiara Sari, Nur Latifah Dwi
Journal of Applied Informatics and Computing Vol. 10 No. 1 (2026): February 2026
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v10i1.11744

Abstract

The subjective and ineffective manual sorting of melinjo fruit, a key ingredient in Indonesian cuisine, results in inconsistent quality. This study aims to create and evaluate an automated classification system for judging the ripeness of Gnetum gnemon fruit in order to solve these issues and offer a reliable and objective quality control method. The approach was to create a customized Deep Convolutional Neural Network (Deep-CNN). The model was trained and evaluated using a simple dataset of 5,718 images that were separated into three maturity levels: raw, semi-ripe, and fully ripe. Twenty percent of the dataset was used for testing, and the remaining 80 percent was used for training. Image preparation techniques like contrast enhancement and scaling to 250x250 pixels were applied in order to optimize the model's input data. The evaluation was conducted using a test dataset consisting of 1,144 photos. After eight epochs of training with the Adam optimizer, the generated Deep-CNN model demonstrated remarkable efficacy with a final classification accuracy of 99.91%. The high level of performance that remained throughout the testing phase confirmed the model's strong ability to accurately identify the ripeness levels of melinjo fruit. The previously unresolved issue of automated melinjo classification is addressed in this work with a tailored and remarkably accurate (99.91%) solution. Its primary advantage is that it provides a trustworthy and unbiased technical alternative to subjective hand sorting. This directly meets industry needs by offering a scalable method to improve operational effectiveness, standardize product quality, and increase the commercial value of melinjo fruit of agricultural products.
Performance Comparison of K-Means Algorithm and BIRCH Algorithm in Clustering Earthquake Data in Indonesia with Web-Based Map Visualization Baromim Triwijaya; Setyoningsih Wibowo; Nur Latifah Dwi Mutiara Sari
JURNAL TEKNOLOGI DAN OPEN SOURCE Vol. 8 No. 1 (2025): Jurnal Teknologi dan Open Source, June 2025
Publisher : Universitas Islam Kuantan Singingi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36378/jtos.v8i1.4400

Abstract

This study applies the K-Means and BIRCH algorithms to cluster earthquake data in Indonesia based on geographic coordinates (latitude and longitude), depth, and magnitude from 2008 to 2023. Due to its position at the intersection of three major tectonic plates, Indonesia is highly prone to earthquakes, making the mapping of vulnerable regions essential for disaster risk reduction. K-Means is selected for its simplicity and clustering effectiveness, while BIRCH is known for its scalability and efficiency in processing large datasets. The clustering process involves data preprocessing and normalization, followed by determining the optimal number of clusters using the Elbow method. Initial findings indicate that K-Means produces more distinct and well-separated clusters than BIRCH, with Silhouette Scores of 0.3501 and 0.2247, respectively. However, after expanding the dataset to 121,123 records and incorporating additional attributes such as mag_type, phasecount, and azimuth_gap, BIRCH demonstrated a significant improvement in performance, achieving a Silhouette Score of 0.3489—surpassing K-Means, which dropped to 0.1293. These results suggest that BIRCH is more effective for clustering large and complex datasets. The final clustering results are visualized on a web-based map to support spatial analysis and the identification of earthquake-prone zones.
Comparative Analysis of K-Nearest Neighbors and Support Vector Machine for Student Stress Prediction Lutfi Khoirul Umam; Setyoningsih Wibowo; Agung Handayanto
Journal of Applied Informatics and Computing Vol. 10 No. 4 (2026): August 2026
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v10i4.13224

Abstract

Student stress has emerged as an important issue because it can negatively affect both academic achievement and mental well-being. The growing development of machine learning techniques has enabled the creation of predictive models that can classify stress levels using various student-related factors. This research evaluates and compares the effectiveness of the K-Nearest Neighbors (KNN) and Support Vector Machine (SVM) algorithms in predicting student stress categories. The dataset was sourced from Kaggle and contains questionnaire-based data, including variables such as sleep quality, frequency of headaches, academic achievement, study workload, participation in extracurricular activities, and stress level classifications. The study followed several stages, including data preprocessing, feature normalization, model development, and performance assessment. Model evaluation was conducted using accuracy, precision, recall, F1-score, and confusion matrix metrics. To validate the practical implementation of the models, both algorithms were incorporated into a web-based application built with the Flask framework and supported by a MySQL database. The experimental results revealed that the KNN algorithm delivered superior classification performance compared to SVM. KNN obtained an accuracy score of 88.46% and a weighted F1-score of 0.89, whereas SVM achieved 46.15% accuracy with a weighted F1-score of 0.41. These findings suggest that KNN is more effective in identifying patterns within the student survey data. In addition, the successful deployment of the prediction system demonstrates that conventional machine learning methods can be utilized to provide real-time assessments of student stress levels and support mental health monitoring efforts.
The Application of K-Nearest Neighbours Algorithms for the Classification of Fashion Trend Saputro, Nugroho Dwi; Wibowo, Setyoningsih; Darmaputra, Mochamad Fadjar
JUSS (Jurnal Sains dan Sistem Informasi) Vol. 2 No. 1 (2019): Jurnal Sains dan Sistem Informasi
Publisher : Prodi Sistem Informasi FST Universitas Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22437/juss.v2i1.6500

Abstract

The commerce department in indonesia has been formulating indonesia economic development plan creative explain about the evolution of the year 2025 creative economy, The shift from agriculture to the industrial era and the era of information and now entering the era of economic globalization. The development of industries create a pattern of work the production and distribution of cheap and more efficient. Fashion industry is one of the creative economy development Creative economy in many countries today encourage the people. Fashion or mode of itself is the activity associated with the design, the production of, consultation and the distribution of the product of fashion .Producers fashion industry composed of fashion clothing and accessories, fashion industry bag manufacturers, shoes and accessories. In clothes creation, the trend of being important aspect .Designers indonesia today still follow the trend of europe are affected by the type of the season. Decision-making on the basis of the data and accurate information will result in a decision to fashion trend clasification on creative industries can be done by adopting the approach of data mining. According to Tan Pang-Ning data mining is a process that done automatically to find information that is useful in a repository big data.
MULTI-OBJECTIVE OPTIMIZATION ON THE BASIS BY RATIO ANALYSIS METHOD SEBAGAI SISTEM PENDUKUNG KEPUTUSAN PENERIMAAN ASISTEN LABORATORIUM (STUDI KASUS PRODI TEKNIK SIPIL UNIVERSITAS PGRI SEMARANG) Setyoningsih Wibowo; Slamet Budirahardjo
Jurnal Transformatika Vol. 17 No. 1 (2019): July 2019
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v17i1.1311

Abstract

Sistem pendukung keputusan suatu sistem guna mempermudah dalam penyelesaian masalah juga sebagai pengambilan suatu keputusan. Metode MOORA (Multi-Objective Optimization by Ratio Analysis) adalah sistem pendukung keputusan dimana metode ini memperhitungkan kalkulasi yang kompleks dan dalam penentuan alternatifpun sangat selektif. Dalam penerimaan asisten laboratorium menjadi masalah yang serius karena banyak factor yang harus dipertimbangkan dan diputuskan. Asisten laboratorium bertugas membantu kepala laboratorium dan dosen pengampu dalam proses pelaksanaan praktikum, menjaga dan merawat peralatan serta menjaga kebersihan laboratorium. Selama ini penerimaan asisten laboratorium dilakukan dengan wawancara dan ujian tertulis kemudian baru dilakukan seleksi secara manual. Pada penelitian ini kami mengambil contoh kasus yang sering dialami oleh Prodi Teknik Sipil. Dari rangkaian proses metode MOORA yang digunakan sebagai sistem pendukung keputusan dalam penerimaan asisten laboratorium disimpulkan bahwa metode ini sangat cocok diimplementasikan karena hasil keluaran sesuai dengan target yang diharapkan. Dan nantinya bisa diterapkan di semua fakultas di Lingkungan Universitas PGRI Semarang sebagai sistem dalam sebuah seleksi.
PKM OPTIMALISASI LAHAN PEKARANGAN SEBAGAI LUMBUNG HIDUP PASCA COVID 19 DI RT. 08 RW. X KELURAHAN KEMBANGARUM KECAMATAN SEMARANG BARAT, KOTA SEMARANG Rifki Hermana; Slamet Budirahardjo; Setyoningsih Wibowo
TEMATIK Vol. 2 No. 1 (2022): Januari
Publisher : Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/tmt.v2i1.4201

Abstract

Sebagian besar warga RT. 08 RW. X Kelurahan Kembangarum Kecamatan Semarang Barat Kota Semarang bermata pencaharian diluar rumah, mayoritas warga bekerja sebagai karyawan swasta dan pekerja buruh. Saat kondisi wilayah Semarang diberlakukannya PPKM (Pemberlakuan Pembatasan Kegiatan Masyarakat). Terutama di wilayah Semarang Barat termasuk zona merah, untuk mencegah semakin luasnya penyebaran maka wilayah tersebut di isolasi sehingga kondisi menjadi perhatian penuh bagi kelurahan setempat. Warga dihimbau untuk tidak banyak melakukan aktifitas diluar rumah. Dengan adanya pembatasan kegiatan diluar rumah maka kebutuhan pokokpun sangat terbatas pula untuk dapat terpenuhi. Hasil diskusi dengan warga, menemukan solusi kegiatan apa yang perlu dilakukan agar pada saat diberlakukannya PPKM warga tidak hanya berdiam diri dirumah. Solusi yang dihasilkan adalah PPKM versi warga RT. 08 yaitu Pengen Panen Kita Menanam. Kami tim pengabdian masyarakat melakukan pendampingan pemanfaatan lahan pekarangan sebagai solusi lumbung pangan bagi keluarga dengan bertanam sayuran, selain sayuran kami juga membudidayakan jahe merah, mengingat manfaat jahe merah yang sangat bagus bagi kesehatan sebagai penangkal covid-19 dan sebagai penguat imun dan karena harga jahe merah yang sangat mahal dan tidak terjangkau warga. Adapun edukasinya adalah menciptakan inovasi pemanfaatan lahan pekarangan di rumah masing-masing dengan sistem Vertikal Garden dan budidaya jahe merah menggunakan polybag/karung. Optimalisasi ini difokuskan pada edukasi tentang vertical garden, sehingga warga yang hanya mempunyai lahan sempit masih bisa menciptakan lumbung hidup sendiri dirumah. Edukasi meliputi pemilihan jenis tanaman yang akan ditanam dengan memperhatikan kebutuhan sinar matahari dan umur panen yang pendek. Kesimpulan warga semakin paham bahwa dengan pengoptimalkan lahan pekarangan dengan system vertical garden sangat menghemat lahan dengan hasil memuaskan. Warga sangat senang dengan hasilnya karena dapat memenuhi kebutuhan pangan sehari-hari. Selain bisa panen dilahan pekarangan sendiri, hasilnya juga organic, menyehatkan dan bergizi. Dengan berbudidaya jahe merah warga dapat menyediakan rempah secara mandiri untuk menjaga stamina dan sebagai penangkal covid-19. Pemahaman tentang pengoptimalah lahan pekarangan dan berbudidaya jahe merah, warga menjadi sadar bahwa lahan sempit bukan menjadi halangan warga untuk betah beraktifitas dirumah. Slogan PPKM (Pengen Panen Kita Menanam) bagi warga sangatlah tepat sekali.  Kata kunci: vertical garden, budidaya, jahe merah
Co-Authors Agung Handayanto Agung Handayanto Aldiansyah, Edo Putra Ari Tri Jaka Harjanta Bagus Priyatno Bambang Agus Herlambang, Bambang Baromim Triwijaya Darmaputra, Mochamad Fadjar Febrian Murti Dewanto Fitri Yulianti Hartanti, Lusia Permata Sari Iksan, Helmi Irna Farikhah Khoiriya Latifah, Khoiriya Kurniawan, Anggi Ade Mega Novita Melapa, Yabes Aryanto Mohamad Fajarianditya Nugroho Muhammad Khoirul Lutfi Mutiara Sari, Nur Latifah Dwi Ngatmini Ngatmini Noora Qotrun Nada, Noora Qotrun Nugroho Dwi Saputro Nugroho Dwi Saputro, Nugroho Dwi Nur Khoiri Nur Latifah Dwi Mutiara Sari Nur Latifah Dwi Mutiara Sari Rifki Hermana Sigit Ristanto Slamet Budirahardjo Slamet Budirahardjo Sri Wahyuni Suyitno Suyitno Tri Widiastuti Waliyansyah, Rahmat Robi Yusuf Ma'iin Rohmatulloh