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All Journal PAWIYATAN Jurnal Transformatika Jurnal Informatika Upgris JOURNAL OF APPLIED INFORMATICS AND COMPUTING Fokus Ekonomi 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
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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MODELING IN PREDICTING ENTREPRENEURIAL INTENTION Wibowo, Setyoningsih; Sijabat, Rauly; Widiastuti, Tri
Fokus Ekonomi : Jurnal Ilmiah Ekonomi Vol 20, No 1 (2025): June 2025
Publisher : STIE Pelita Nusantara Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34152/fe.20.1.49-60

Abstract

Job opportunities for college graduates are increasingly limited. On the other hand, the number of intellectual unemployment is increasing. The mindset of students who are still job seekers oriented rather than creating jobs (job creators) makes the imbalance between labor demand and supply worse. The study of the variable explanatory variables of entrepreneurial intention has been carried out, although the results are not conclusive and the involvement of mediating variable or the moderation is still limited. Finding and re-explaining variable that can explain the problem regarding the low entrepreneurial interest is a decent job to be examined again in this study. This study was conducted on final-level student respondents at accredited A colleges in Semarang through interviews by using questionnaires. The data obtained were analyzed using the Binary Logistic Regression Test. The results show that attitude and contextual factors are the variables that can explain the entrepreneurial interest clearly. The self-confidence variable is actually not able to moderate the influence of attitude and contextual factors on the entrepreneurial interest. This study also shows that autonomy and authority are dimensions that have dominant influence in explaining attitudinal factor and academic support is the dominant dimensions in explaining contextual factor.
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
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) Wibowo, Setyoningsih; Budirahardjo, Slamet
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.
Implementasi Algoritma Linear Congruent Method Pada Pengacakan Soal Kuis dalam Aplikasi Mobile Learning Anemia Berbasis Android (MobiliA) Herlambang, Bambang Agus; Wibowo, Setyoningsih; Choirunnisa, Choirunnisa; Setyawati, Vilda Ana Veria
Jurnal Transformatika Vol. 18 No. 2 (2021): January, 2021
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v18i2.2382

Abstract

Anemia is a lack of blood condition with reduction in hemoglobin as one of indicator.  According to data from the Basic Health Research in 2013, the prevalence of anemia sufferers in Indonesia was high at 37.1%. The figure was almost close to severe public health problems with an anemia prevalence limit of more than 40%. However, this was not accompanied by low public knowledge about anemia.Therefore, researcher created an anemia mobile learning application based on android to increase people knowledge about anemia in everytime.There were quizzes randomly issued using the Linear Congruent Method algorithm. Linear Congruent Method algorithm, which was an algorithm that produced random permutations from a finite set. Testing Linear Congruent Method (LCM) algorithm was able to produce an effective randomization problem, where there was no repetition of the same value if the value of the declared variable meets the determination parameters of the existing LCM Algorithm i.e. the increment value and modulus must be relatively prime.  
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.
Co-Authors Abda Abda Agung Handayanto Aldiansyah, Edo Putra Ari Tri Jaka Harjanta Bagus Priyatno Bambang Agus Herlambang, Bambang Febrian Murti Dewanto Fitri Yulianti Hartanti, Lusia Permata Sari Hermana, Rifki Iksan, Helmi Irna Farikhah Khoiriya Latifah, Khoiriya Kurniawan, Anggi Ade Mega Novita Melapa, Yabes Aryanto Mohamad Fajarianditya Nugroho Mutiara Sari, Nur Latifah Dwi Ngatmini Ngatmini Noora Qotrun Nada, Noora Qotrun Nugroho Dwi Saputro Nur Khoiri Nur Latifah Dwi Mutiara Sari Sigit Ristanto Slamet Budirahardjo Slamet Budirahardjo Sri Wahyuni Suyitno Suyitno Tri Widiastuti Vilda Ana Veria Setyawati Waliyansyah, Rahmat Robi Yusuf Ma'iin Rohmatulloh