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All Journal Jurnal Simetris JOURNAL OF APPLIED INFORMATICS AND COMPUTING Journal of Dinda : Data Science, Information Technology, and Data Analytics Madiun Spoor : Jurnal Pengabdian Masyarakat
Buang Budi Wahono, Buang Budi
Fakultas Sains dan Teknologi, Program Studi Teknik Informatika Universitas Islam Nahdlatul Ulama Jepara
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Materials Science & Nanotechnology Social Sciences

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PERANCANGAN TATAKELOLA TEKNOLOGI INFORMASI UNTUK PENINGKATAN LAYANAN SISTEM INFORMASI KESEHATAN (STUDI KASUS DINAS KESEHATAN KABUPATEN JEPARA) Wahono, Buang Budi
Simetris: Jurnal Teknik Mesin, Elektro dan Ilmu Komputer Vol 6, No 1 (2015): JURNAL SIMETRIS VOLUME 6 NO 1 TAHUN 2015
Publisher : Universitas Muria Kudus

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (329.332 KB) | DOI: 10.24176/simet.v6i1.244

Abstract

ABSTRAK Perkembangan teknologi saat ini tak bisa dibendung lagi. Kemajuan disetiap bidang tak lepas dari teknologi sebagai penunjangnya, terutama teknologi informasi. Namun sebelum perluasan penggunaan, tentunya perlu sebuah evaluasi ataupun audit tatakelola teknologi inforrmasi yang ada. Untuk membangun dan mengembangkan sistem informasi dan dokumentasi ini diperlukan pengelolaan data yang baik. Penelitian ini bertujuan mengetahui sejauh mana pengelolaan data untuk layanan publik yang telah diterapkan pada Dinas Kesehatan Kabupaten Jepara dan memberikan rekomendasi tatakelola yang seharusnya di masa mendatang setelah mengetahui kesenjangan antara tatakelola saat ini dengan tatakelola yang diharapkan sesuai dengan framework yang digunakan. Framework yang digunakan dalam penelitian ini adalah COBIT versi 4.1 pada domain Deliver and Support (DS) khususnya DS11 yaitu manajemen data dan proses kontrol yang berhubungan, yaitu PO2 (Define the Information Architecture), DS4 (Ensure Continuous Service), DS5 (Ensure Systems Security) dan DS13 (Manage Operations). Dari hasil uji ini dapat diambil kesimpulan bahwa PO2 berpengaruh signifikan terhadap DS11, AI4 tidak berpengaruh signifikan terhadap DS11, DS1 berpengaruh signifikan terhadap DS11, DS4 berpengaruh signifikan terhadap DS11, DS5 berpengaruh signifikan terhadap DS11, DS11 tidak berpengaruh signifikan terhadap DS13, DS11 berpengaruh signifikan terhadap ME1. Kata kunci: keterbukaan informasi publik; tatakelola teknologi informasi; COBIT, manajemen data.
Evaluation of Telecommunication Customer Churn Classification with SMOTE Using Random Forest and XGBoost Algorithms Wakhidah, Lisa Nusrotul; Zyen, Akhmad Khanif; Wahono, Buang Budi
Journal of Applied Informatics and Computing Vol. 9 No. 1 (2025): February 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i1.8740

Abstract

Competition in the telecommunications industry, particularly among Internet Service Providers (ISPs), significantly influences customer churn, which negatively impacts revenue, profitability, and business sustainability. An effective approach to mitigate churn involves identifying potential churners early, enabling companies to implement strategic retention measures. However, predicting churn can be challenging due to the limited data available on churned customers. This study aims to predict customers likely to terminate or discontinue their subscriptions, focusing on addressing data imbalance using the Synthetic Minority Over-Sampling Technique (SMOTE). The dataset, sourced from Kaggle, comprises 21 attributes and 7,034 entries. The pre-processing phase includes data cleaning, feature encoding, and the implementation of Random Forest and XGBoost algorithms after data balancing with SMOTE. The findings reveal that the XGBoost algorithm achieves a prediction accuracy of 82%, outperforming Random Forest with 81%. Key factors influencing churn include Contract, TotalCharges, and tenure. The study concludes by emphasizing the significance of contract flexibility and the need to prioritize customers with high total costs or extended subscription periods to reduce churn rates. Future research is encouraged to investigate alternative methods for handling data imbalance and to explore advanced machine learning algorithms to further enhance prediction accuracy and the effectiveness of customer retention strategies.
PKM PENGUATAN LITERASI NUMERASI SISWA SD MELALUI PELATIHAN MEDIA DIGITAL PADA KELOMPOK IBU BELAJAR MATEMATIKA Wakit, Ahmat; Hidayati, Nor; Wahono, Buang Budi; Arif, Muhammad Nor; Fauziah, Atha
Madiun Spoor : Jurnal Pengabdian Masyarakat Vol 5 No 1 (2025): April 2025
Publisher : Politeknik Perkeretaapian Indonesia Madiun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37367/jpm.v5i1.442

Abstract

This community service program is in the form of training and mentoring for the Mathematics Learning Mothers Community (KIBM) of Kerso Village. This community service was carried out in the odd semester of the 2024/2025 academic year. KIBM is a group of mothers who have children who are undergoing elementary education or equivalent. The purpose of KIBM is to improve the basic mathematics skills of KIBM, the level of parental confidence in accompanying children in learning, increase parental involvement in accompanying children and improve numeracy literacy skills. The implementation methods used include preparation, socialization, training, and evaluation. The results achieved from this activity are the basic mathematics skills of the mathematics learning mothers group increased, the mothers' confidence in guiding their sons and daughters' learning increased, the involvement of mothers in accompanying children in learning increased, and the implementation of training can improve numeracy literacy skills.
MODEL E-BUSINESS MENGGUNAKAN PIECES FRAMEWORK UNTUK PENINGKATAN DAYA SAING UMKM BERBASIS MOBILE APPLICATION Azizah, Noor; Wahono, Buang Budi
Simetris: Jurnal Teknik Mesin, Elektro dan Ilmu Komputer Vol 11, No 2 (2020): JURNAL SIMETRIS VOLUME 11 NO 2 TAHUN 2020
Publisher : Fakultas Teknik Universitas Muria Kudus

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24176/simet.v11i2.5185

Abstract

Usaha Kecil dan Menengah (UKM) merupakan salah satu bidang yang memberikan kontribusi yang segnifikan dalam memacu pertumbuhan ekonomi Indonesia. Di sisi yang lain, perkembangan teknologi dan internet juga berkembang sangat cepat. Oleh karena itu, pengelolaan bisnis dengan memanfaatkan teknologi digital yang ada saat ini menjadi bagian penting dalam meningkatkan daya saing UMKM agar mampu berkompetisi dengan pelaku industri yang lain. Tujuan dari penelitian ini adalah membangun sebuah e-business yang digunakan untuk meningkatkan performa bisnisnya dalam rangka mencapai keunggulan kompetitifnya agar mampu berdaya saing dengan para kompetitor yang lain. Tools yang digunakan untuk menganalisa kebutuhan sistem menggunakan PIECES Framework yang meliputi performance, informations, economics, control, efficency, dan services. Adapun data primer diperoleh dari 50 responden untuk mengukur tingkat kepuasan penggunaan sistem e-business dalam pengelolaan bisnis UMKM.  Hasilnya diperoleh rata-rata kepuasan pengguna, 3,92 yang artinya sistem e-business yang dikembangkan sangat penting dan pengguna merasa puas dalam penggunaan sistem tersebut
Implementation of Random Forest Algorithm with RFE and SMOTE on Cardiotocography Dataset Nur Taqwimi, Muhammad Ahsani; Wahono, Buang Budi; Mulyo, Harminto
Indonesian Journal of Data Science, IoT, Machine Learning and Informatics Vol 5 No 2 (2025): August
Publisher : Research Group of Data Engineering, Faculty of Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/dinda.v5i2.1818

Abstract

Having a healthy baby is a dream for mothers. However, the high rate of maternal and fetal mortality is still a serious problem, so more accurate fetal health monitoring is needed to prevent pregnancy complications. One of the devices used is Cardiotocography (CTG), which produces data on fetal conditions. The CTG dataset used in this study faces challenges in the form of class imbalance and a high number of features, which can reduce classification performance. This study aims to overcome these challenges by implementing the Random Forest algorithm combined with the Synthetic Minority Oversampling Technique (SMOTE) technique for class balancing and Recursive Feature Elimination (RFE) for feature selection. The dataset used is "Fetal Health Classification" from the Kaggle platform, which consists of 2,126 data with three classes: Normal, Suspect, and Pathological. The test results show that the RFE method is able to reduce the number of features from 22 to 18, while SMOTE increases the proportion of minority data. The model built produces good classification performance with an accuracy value of 95%, precision 93%, recall 89%, and F1-score 91%. The ROC-AUC value for the Normal class is 0.9881, Suspect 0.9789, and Pathological 0.9985. Although the model is able to predict the Normal and Pathological classes with high accuracy, the performance on the Suspect class still needs to be improved. Overall, the integration of Random Forest with SMOTE and RFE has proven effective in improving the accuracy of fetal health classification.
Co-Authors Ahmat Wakit Akhmad Khanif Zyen, Akhmad Khanif Arif, Muhammad Nor Fauziah, Atha Mulyo, Harminto Noor Azizah Nur Taqwimi, Muhammad Ahsani Wakhidah, Lisa Nusrotul