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All Journal Jurnal Keperawatan Jiwa (JKJ): Persatuan Perawat Nasional Indonesia Sistemasi: Jurnal Sistem Informasi JOIV : International Journal on Informatics Visualization Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) MULTINETICS Jurnal Keperawatan Widya Gantari Indonesia Dinasti International Journal of Education Management and Social Science Indonesian Journal of Electrical Engineering and Computer Science Khatulistiwa Nursing Journal Jurnal Locus Penelitian dan Pengabdian Eduvest - Journal of Universal Studies Majalah Cendekia Mengabdi Journal Of Engineering Sciences (Improsci) The Indonesian Journal of Computer Science Jurnal Gawat Darurat
Budi, Indra
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Aerospace Engineering Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Veterinary

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Efektivitas Pemberian Edukasi Asupan Serat terhadap Penurunan Kadar Gula Darah Sewaktu (GDS) pada Pasien Diabetes Melitus Tipe II Wati, Eka Setya; Tjomiadi, Cynthia Eka Fayuning; Budi, Indra; Rahman, Subhannur
Jurnal Keperawatan Jiwa Vol 12, No 4 (2024): November 2024
Publisher : Universitas Muhammadiyah Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jkj.12.4.2024.839-846

Abstract

Diabetes Melitus tipe 2 masuk dalam penyakit metabolik yang morbiditasnya cukup tinggi dengan kriteria hiperglikemia. Jika kasus hiperglikemia dibiarkan bisa menimbulkan beberapa penyebab seperti kerusakan pada berbagai organ tubuh, komplikasi Kesehatan yang melumpuhkan dan mengancam jiwa seperti penyakit kardiovaskular, neuropati, dan penyakit mata yang menyebabkan retinopati serta kebutaan. Salah satu tindakan yang dilakukan untuk mengatasi masalah Hiperglikemia yang dialami penderita diabetes melitus tipe 2 adalah dengan edukasi diet asupan serat. Tujuan untuk mengetahui Efektivitas Pemberian Edukasi Asupan Serat Terhadap Penurunan Kadar Gula Darah Sewaktu (GDS) Pada Pasien Diabetes Melitustipe II Di Puskesmas Pekauman Banjarmasin. Penelitian ini menggunakan metode kuantitatif dengan jenis Pre-Experimental Design desain penelitian One Group Pretest-Posttest Design. Jumlah sampel 30 responden dengan Teknik purposive sampling. Pengambilan data pada pagi hari dengan glucometer yang diuji dengan uji statistik Wilcoxon. hasil penelitian didapatkan mayoritas responden berjenis kelamin perempuan dengan rentang usia 51-60 tahun. Nilai pretest menunjukkan mayoritas responden memiliki kadar GDS >200mg/dL dan post-test mayoritas memiliki kadar GDS dengan rentang 140-199mg/dL. Melihat hasil ini terjadi penurunan kadar gula darah. Hasil ini diperkuat dengan nilai p= 0,000 yang menunjukkan ada perbedaan yang signifikan pada penurunan kadar GDS. Terdapat efektivitas pemberian edukasi asupan serat terhadap penurunan kadar gula darah sewaktu.
Waspada Gadget Untuk Tumbuh Kembang Anak Fetriyah, Umi Hanik; Budi, Indra; Wijaksono, M. Arief; Asmadiannor, Asmadiannor; Rosalina, Nadya; Melda, Melda; Cloudia, Lorenza; Agustina, Mely; Munawarah, Munawarah; Dewi, Ni Gusti Agung Ayu Sri; Habibi, Nur Hakidah; Nataly, Onevia Berlian; Virdasari, Sweetryani
Majalah Cendekia Mengabdi Vol 2 No 4 (2024): Majalah Cendekia Mengabdi
Publisher : CV. Wadah Publikasi Cendekia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63004/mcm.v2i4.447

Abstract

Pendahuluan: Anak-anak tentunya sangat senang jika memperoleh gadget dari orang tuanya. Penggunaan gadget secara berlebihan oleh anak-anak dapat berdampak negatif pada pola perilaku dan perkembangan mereka. Anak-anak yang terus-menerus menggunakan gadget cenderung mengalami ketergantungan, mengurangi waktu untuk belajar dan berinteraksi sosial, serta menghadapi risiko kesehatan seperti kerusakan jaringan saraf akibat radiasi gadget. Meskipun gadget bisa merangsang kreativitas dan kecerdasan, dampak negatifnya, termasuk menurunnya daya aktif dan kepedulian sosial anak, lebih dominan. Oleh karena itu, penting untuk membatasi waktu penggunaan gadget sesuai usia—anak di bawah 18 bulan sebaiknya tidak menggunakan gadget kecuali untuk panggilan video, anak usia 2-5 tahun maksimal 1 jam per hari dengan pengawasan, dan anak usia 6 tahun ke atas maksimal 1-2 jam per hari dengan batasan ketat—untuk memastikan tumbuh kembang yang sehat. Tujuan: Tujuan dari Pengabdian Kepada Masyarakat yaitu untuk memberikan Edukasi kepada siswa kemudian memberikan pengetahuan secara langsung tentang Waspada Gadget Untuk Tumbuh Kembang Anak di SDN Pengambangan 6 Banjarmasin. Metode: Metode pengumpulan data pada kegiatan Pelatihan berupa pemberian pengetahuan dan keterampilan, serta memberikan Pre-Test dan Post-Test kepada siswa kelas 5 dan 6 SDN Pengambangan 6 Banjarmasin untuk mengukur tingkat pengetahuan. Hasil: Hasil Pelatihan ini melibatkan 25 siswa dalam kegiatan satu hari yang mencakup pre-test, materi, sesi tanya jawab, dan post-test. Hasil menunjukkan peningkatan pengetahuan siswa tentang waspada gadget untuk tumbuh kembang anak, dengan persentase pemahaman kategori Tinggi meningkat dari 20% menjadi 92% dan kategori Rendah dari 20% menjadi 0%. Program ini berhasil meningkatkan pemahaman siswa tentang Waspada Gadget Untuk Tumbuh Kembang Anak. Simpulan: Pada kegiatan Edukasi ini dapat disimpulkan bahwa para peserta memahami dan mampu menerapkan Waspada Gadget Untuk Tumbuh Kembang Anak.
Hubungan Pengetahuan Keluarga tentang Perawatan Pasca Stroke dengan Family Readiness dalam Penerimaan Kembali Pasien Pasca Stroke Izzuddin, Muhammad Sulthan; Santoso, Bagus Rahmat; Budi, Indra; Basit, Mohammad
Jurnal Keperawatan Jiwa Vol 12, No 4 (2024): November 2024
Publisher : Universitas Muhammadiyah Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jkj.12.4.2024.893-900

Abstract

Pentingnya keluarga harus tahu perawatan pasien pasca stroke Pada fase perawatan pasien pasca stroke dan pemulihan setelah pulang dirumah. keluarga harus terlibat secara aktif dan menyeluruh karena kekuatan dan motivasi dari diri sendiri bahkan dari orang terdekat sangat dibutuhkan oleh pasien. Kesiapan keluarga akan mempengaruhi berhasil atau tidaknya perawatan yang dijalani oleh pasien. Keluarga merupakan tempat rehabilitasi pertama pada saat pasien kembali ke rumah. Tujuan untuk mengetahui ada tidaknya hubungan antara Pengetahuan Keluarga Tentang Perawatan dengan Family Readiness dalam Penerimaan Kembali Pasien Pasca Stroke. Rancangan  dalam  penelitian  yaitu menggunakan Kuantitatif Deskriptif dengan pendekatan cross sectional dan pengambilan sampel menggunakan total sampling dengan jumlah 30 responden di RSUD Ulin Banjarmasin. Uji Analisa menggunakan uji Kolmogorov-Smirnov. Menunjukkan bahwa tidak terdapat hubungan antara Pengetahuan Keluarga Tentang Perawatan Pasca Stroke dengan Family Readiness Dalam Penerimaan Kembali Pasien Pasca Stroke dengan nilai p value 0,0787. Meningkatkan pengetahuan tentang perawatan stroke dan kesiapan  untuk lebih aktif dalam melakukan  perawatan kepada anggota keluarga mereka yang menderita stroke setelah  pulang dari rumah sakit. 
Pengalaman Perawat dalam Tatalaksana Rujukan Pasien dengan Cardiac Arrest di Kabupaten Hulu Sungai Utara: Studi Fenomenologi Heryadi, Abdi Taofan; Mohtar, M. Sobirin; Budi, Indra
Jurnal Gawat Darurat Vol. 6 No. 2 (2024): Jurnal Gawat Darurat: Desember 2024
Publisher : LPPM Sekolah Tinggi Ilmu Kesehatan Kendal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32583/jgd.v6i2.3588

Abstract

Kejadian cardiac arrest merupakan kondisi kegawatdaruratan dari penyakit jantung yang sering terjadi. Penanganan pasien cardiac arrest pada fase akut harus meliputi pengenalan dan aktivasi sistem respon gawat darurat, resusitasi jantung paru yang berkualitas, layanan gawat darurat dasar dan lanjut pada fase transportasi, serta perawatan paska henti jantung fase lanjut. Pasien dirujuk dalam keadaaan kritis mempunyai resiko saat transport. Kemampuan setiap anggota melakukan prosedur tindakan yang tepat dan benar akan berefek pada outcome pasien. Mengetahui pengalaman perawat dalam tatalaksana rujukan pasien dengan cardiac arrest di Kabupaten Hulu Sungai Utara. Penelitian kualitatif dengan desain pendekatan fenomenologi. Partisipan penelitian ini adalah perawat yang pernah melakukan rujukan pasien cardiac arrest berjumlah 7 orang. Penelitian dilakukan bulan Februari 2023. Persepsi tentang cardiac arrest adalah kondisi henti jantung, henti nafas ditandai penurunan kesadaran. Data dianalisa dengan narrative analysis. Respon pertama menemui pasien cardiac arrest, cek nadi, cek nafas pasien. Intervensi selama trasnfortasi rujukan berusaha semampunya membantu pasien dan pemeriksaan TTV secara berkala. Golden period tindakan rujukan secepatnya dan merujuk pasien dengan kondisi sudah stabil, lamanya waktu dibutuhkan persetujuan dari keluarga. Faktor keterlambatan terkendala dengan kondisi jalan saat melakukan tindakan, lamanya waktu perjalanan dan persetujuan dari keluarga. Respon emosional saat melakukan rujukan merasa gugup, panik dan takut. Makna merujuk pasien bagi perawat merasa lega, tenang dan bersyukur pasien sudah sampai ke rumah sakit. Pengalaman perawat selama rujukan pasien dengan cardiac arrest memberikan makna yang mendalam. Sangat cemas ketika masih diperjalanan dan sangat puas ketika sudah sampai di rumah sakit.
Improving Sentiment Analysis and Topic Extraction in Indonesian Travel App Reviews Through BERT Fine-Tuning Irmawan, Oky Ade; Budi, Indra; Santoso, Aris Budi; Putra, Prabu Kresna
Jurnal Nasional Pendidikan Teknik Informatika : JANAPATI Vol. 13 No. 2 (2024)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v13i2.77028

Abstract

Abstract The increasing use of the internet in Indonesia has an influence on the presence of Online Travel Agents (OTA). Through the OTA application, users can book transportation and accommodation tickets more easily and quickly. The increasingly rigorous competition is causing companies like PT XYZ to be able to provide solutions to the needs and problems of their customers in the field of online ticket booking. Many customers submit reviews of the use of the PT XYZ application through Playstore and Appstore, and it needs a technique to group thousands of reviews and detect the topics discussed by customers automatically. In this study, we classified reviews from Android and iOS applications using BERT that had been adjusted through fine-tuning with IndoBERT, as well as modeling topics using LDA to evaluate the coherence score of each sentiment. The result of the comparison of hyperparameter models for the most optimal classification is epoch 4 with a learning rate of 5e-5. The accuracy obtained is 0.91, with an f1-score of 0.74. In addition, testing was carried out to compare BERT with other traditional machine learning. The best performing algorithm was Logistic Regression using TF-IDF word embeddings, achieving an accuracy of 0.890 and an F1-score of 0.865. Therefore, it can be inferred that the accuracy achieved by the fine-tuned classification model of IndoBert is sufficiently high for application in the PT XYZ review classification. Using a coherence score, we found 29 positive topics, 6 neutral topics, and 3 negative topics that were considered the most optimal. This finding can be used as evaluation material for PT XYZ to provide the best service to customers.
Toponym Extraction and Disambiguation from Text: A Survey Windiastuti, Rizka; Krisnadhi, Adila Alfa; Budi, Indra
JOIV : International Journal on Informatics Visualization Vol 9, No 1 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.1.2763

Abstract

Toponym is an essential element of geospatial information. Traditionally, toponyms are collected in a gazetteer through field surveys that require significant resources, including labor, time, and money. Nowadays, we can utilize social media and online news portals to collect event locations or toponyms from the text. This article presents a survey of studies that focus on the extraction and disambiguation of toponyms from textual documents. While toponym extraction aims to identify toponyms from the text, toponym disambiguation determines their specific locations on the earth. The survey covered articles published between January 2015 and April 2023, presented in English, and gathered from five major journal databases. The survey was conducted by adopting the Kitchenham guidelines, consisting of an initial article search, article selection, and annotation process to facilitate the reporting phase. We employed Mendeley as a reference management tool and NVivo to categorize certain parts of the articles that are the focal points of interest in this survey. The primary focus of the survey was on the methods or approaches performed in the research articles to extract and disambiguate toponyms. Additionally, we also discuss some general challenges in toponym research, different applications for toponym extraction and disambiguation, data sources, and the use of languages other than English in the studies. The survey confirms that each approach has its limitations. Extracting and disambiguating toponyms from text is complex and challenging, especially for low-resource languages. We also suggest some research directions related to toponym extraction and disambiguation that could enrich the gazetteer.
Measuring mobile banking service quality using Topic Modeling and Term Ranking: A case study of an Indonesian digital bank Anggraini, Veny; Budi, Indra; Santoso, Aris Budi; Putra, Prabu Kresna
The Indonesian Journal of Computer Science Vol. 13 No. 6 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i6.4517

Abstract

The rapid expansion of digital transactions in Indonesia is driving the transformation of both traditional and digital banks. Since digital banks operate without physical branches, all banking services are via mobile banking apps. This study examines mobile banking service quality using text mining techniques like topic modeling and term ranking to analyze 11,815 user reviews from app stores and assess customer satisfaction through ratings. The research involves extracting and preprocessing reviews, identifying key topics, and linking them to satisfaction levels. Seven service dimensions were found: customers were satisfied with Enjoyment, Debit Card Delivery, and Feature-Free Transactions but dissatisfied with Accessibility, Data Privacy, Loan Services, and Touchless Customer Support. Debit Card Delivery and Feature-Free Transactions were highlighted as significant factors in Indonesia's digital banking market. With limitations in analyzing user reviews in Bahasa Indonesia, the findings are specific to the Indonesian digital banking context and may not be applicable elsewhere.
Leveraging LSTM Predictions for Enhanced Portfolio Allocation with Markowitz Mean-Variance Optimization Sahid, Irfanda Husni; Budi, Indra
The Indonesian Journal of Computer Science Vol. 13 No. 6 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i6.4573

Abstract

This research investigates the application of Long Short-Term Memory (LSTM) networks for predicting expected returns and integrating these predictions into the Markowitz Mean-Variance Optimization (MVO) framework. The study utilized historical data from eight Indonesian stocks: BBCA, BBRI, TLKM, EXCL, UNVR, ICBP, ASII, and SMGR. The dataset covered the period from 2018 to 2024. The LSTM model was employed to predict cumulative returns over a 90-day horizon, and its performance was compared to the Exponentially Weighted Moving Average (EWMA) method. The findings indicate that LSTM achieved lower Root Mean Squared Error (RMSE) than EWMA for four stocks (BBCA, BBRI, UNVR, ICBP), while EWMA demonstrated better performance for the remaining four stocks. MVO results revealed that LSTM-based predictions achieved an average return of 4.285%, surpassing EWMA's 1.856% but falling short of the 12.298% obtained using actual returns. These results highlight the potential of LSTM models to enhance portfolio allocation strategies.
Optimizing Climate Forecasts Across 16 Zones Using Regression-Based Machine Learning Models Ardin; Budi, Indra
The Indonesian Journal of Computer Science Vol. 14 No. 1 (2025): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v14i1.4593

Abstract

The XYZ Climatology Station faces challenges in improving the accuracy of decadal rainfall forecasts, with an average achievement of 57.4% in 2022 and 58.8% in 2023, below the organizational performance target of 70% accuracy as set in its strategic objectives. This study aims to develop machine learning-based predictive models for 16 climate zones to enhance forecast accuracy. Five regression algorithms—Multiple Linear Regression, Support Vector Regression, Extra Trees Regression, Random Forest Regression, and Decision Tree Regression—were tested under two scenarios: input variable variations (VR) and time series data length (TS). Results showed that the VR scenario increased average accuracy to 71.7% (2022) and 69.4% (2023), while the TS scenario achieved 73.1% (2022) and 72.6% (2023). Support Vector Regression and Extra Trees Regression demonstrated the best performance in most zones. These models are expected to be operationalized to improve climatological information services and better meet public and stakeholder needs.
Analisis Sentimen Berbasis Aspek Aplikasi Brimo berdasarkan Ulasan Pengguna di Google Playstore Azarya, Yosia; Budi, Indra
The Indonesian Journal of Computer Science Vol. 14 No. 1 (2025): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v14i1.4613

Abstract

BRI is focused through their mobile banking superapp known as BRImo. However, based on discussions with the BRImo application research team, The user reviews available on the Google Play Store application service page could be classified based on the PACMAD usability aspects and sentiment using several classification models, including Random Forest, Decision Tree, and Extreme Gradient Boosting, with TF-IDF employed as the feature extraction method. Additionally, the Random Oversampling and Synthetic Minority Oversampling Technique (SMOTE) methods were applied as supplementary treatments to address the issue of imbalanced classes in BRImo application user review data. Topic modeling was also conducted using the LDA method to identify keywords and the main discussion topics for each PACMAD usability aspect and its sentiment, resulting in clear topics that can serve as a focus for the development of the BRImo application. The research findings indicate that the XGBoost classification model, combined with the SMOTE sampling method, demonstrated the best performance in classifying PACMAD usability aspects and sentiments, achieving F1-scores of 86.55% and 89.59%, respectively. Furthermore, the key topics for each PACMAD usability aspect and their associated sentiments were identified.
Co-Authors Abdul Gofur Agustina, Mely Angelo, Michael David Anggraini, Veny Ani Widiastuti, Ani Ardin Arianto, Dian Asmadiannor, Asmadiannor Azarya, Yosia Bagus Rahmat Santoso, Bagus Rahmat Cloudia, Lorenza Dekatama, Alifdaffa Nurfahmi Dewi, Ni Gusti Agung Ayu Sri Elly Nurachmah Habibi, Nur Hakidah Halim, Dicky Harwenda, Reyhan Widyatna Heryadi, Abdi Taofan Ibrohim, Muhammad Okky Insani, Faiz Nur Fitrah Irmawan, Oky Ade Istiqomah, Relaci Aprilia Izzuddin, Muhammad Sulthan Krisnadhi, Adila Alfa Kurniawan, Sandy M. Sobirin Mohtar Melda, Melda Mohammad Basit, Mohammad Mubina, Basma Fathan Munawarah Munawarah, Munawarah Muthmainnah, Miftahul Nataly, Onevia Berlian Octovianto, Christofer Permana, Yandi Dwi Prabu Kresna Putra, Prabu Kresna Prayogo, Devin Putri, Irzanes Rakhmadhani, Irzal Ramadiah, Amanah Rizka Windiastuti, Rizka Rosalina, Nadya Sahid, Irfanda Husni Santoso, Aris Budi Sekarsari, Rita Subhannur Rahman, Subhannur Tiastama, Sheren Afryan Tjomiadi, Cynthia Eka Fayuning Umi hanik Fetriyah, Umi hanik Virdasari, Sweetryani Wati, Eka Setya Wijaksono, M. Arief