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All Journal Jurnal Ilmiah Keperawatan (Scientific Journal of Nursing) Journal of Health, Education, And Literacy (J-Healt) Al-Ittishol : Jurnal Komunikasi dan Penyiaran Islam Jurnal J-PEMAS JITSI : Jurnal Ilmiah Teknologi Sistem Informasi Health & Medical Sciences Al-Tafani: Jurnal Pengabdian Masyarakat Jurnal Penelitian Pendidikan Indonesia (JPPI) The Indonesian Journal of Computer Science Jurnal Ilmiah Kesehatan Mandira Cendikia AT-TAKLIM: Jurnal Pendidikan Multidisiplin
Agustin
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Computer Science & IT Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Education Electrical & Electronics Engineering Engineering Health Professions Languange, Linguistic, Communication & Media Medicine & Pharmacology Neuroscience Nursing Public Health Social Sciences Other

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Optimization of Deep Learning with FastText for Sentiment Analysis of the SIREKAP 2024 Application Handoko; Junadhi; Triyani Arita Fitri; Agustin
The Indonesian Journal of Computer Science Vol. 14 No. 2 (2025): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v14i2.4809

Abstract

This study analyzes public sentiment towards the SIREKAP 2024 application using deep learning. Data was collected from Google Playstore reviews and processed through cleaning, tokenization, and stemming. Word embedding was performed using FastText to capture more accurate word representations, including OOV words. The deep learning models compared were CNN, BiLSTM, and BiGRU. Performance evaluation used accuracy, precision, recall, and F1-score metrics. The results showed that the CNN model with FastText Gensim embedding achieved the highest accuracy of 95.98%, outperforming BiLSTM and BiGRU. This model was more effective in classifying positive and negative sentiments. This study provides insights for developers to improve the performance and public trust in SIREKAP 2024 and opens opportunities for further research with more complex embedding approaches and deep learning models.
Faktor-Faktor Yang Berhubungan Dengan Kejadian Preeklamsia Di Rumah Sakit Bakti Timah Pangkalpinang Tahun 2024 Nengsi Sapitri; Agustin; Ardiansyah
AT-TAKLIM: Jurnal Pendidikan Multidisiplin Vol. 2 No. 5 (2025): At-Taklim: Jurnal Pendidikan Multidisiplin (Edisi Mei)
Publisher : PT. Hasba Edukasi Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.71282/at-taklim.v2i5.281

Abstract

Pregnancy is a physiological process that brings changes to the mother and her environment. With pregnancy, a woman's body system experiences fundamental changes to support the development and growth of the fetus in the womb during a person's pregnancy process. Preeclampsia is a major cause of maternal and perinatal morbidity and mortality worldwide. In Indonesia, the incidence of preeclampsia is the second highest cause of maternal death after bleeding with a percentage of 25%. The aim of this research is to determine the factors associated with the incidence of preeclampsia at the Bakti Timah Pangkalpinang Hospital in 2022-2024. This study used a cross-sectional analytical observation study research design. The population in this study was 2,399 pregnant women at RSBT in 2022- 2023, with a sample of 59. This research was conducted in 09 December 2024-09 January 2025. Data analysis used the Chisquare test. The results of the analysis show that there is a significant relationship between maternal age with p-value = 0.028 POR= 3.989, history of hypertension with p-value = 0.000 POR = 15.938, Parity with p-value = 0.000 POR = 26.571 and obesity with p-value = 0.000 POR=19,333 with the incidence of preeclampsia. The conclusion of this study is that preeclampsia is caused by several factors, namely, age ≤20 years and ≥35 years, mothers who have a history of hypertension if their systolic pressure is ≤140 and diastolic pressure ≥90, mothers who experience parity more than 3 times and mothers who are obese with a BMI of more than 26, so there is a relationship between age, history of hypertension, parity and obesity with the incidence of preeclampsia in pregnant women at the Bakti Hospital. tin base pinang in 2024.
Pokok-Pokok Ajaran Aswaja: Bidang Akidah (Asy’ari Dan Maturidi), Bidang Fiqh (Madzhab Hanafi, Maliki, Syafi’i Dan Hambali), Bidang Tasawwuf (Imam Ghozali, Imam Junaid Al-Baghdady) Muhamad Muliyono; Saifuddin; Agustin; Miftakhul Jannah
Al-Ittishol: Jurnal Komunikasi dan Penyiaran Islam Vol. 6 No. 2 (2025): Al-Ittishol: Jurnal Komunikasi dan Penyiaran Islam
Publisher : Prodi Komunikasi dan Penyiaran Islam

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Abstract

Pokok ajaran aswaja dapat diartikan sebagai sebuah prinsip yang mendasari sebuah pemikiran didalam agama Islam, yang utamanya ada di Indonesia. Sedangkan pengertian aswaja sendiri adalah suatu cara dalam bersikap ataupun berfikir dalam mengamalkan dan memahami sebuah ajaran Islam yang toleran dan seimbang. Pokok-pokok ajaran aswaja diantaranya adalah dalam bidang aqidah. Akidah yang dimaksud adalah sebuah keyakinan. Dalam bidang tersebut, aswaja mengikuti paham yang dirumuskan oleh al-Asy’ari dan Maturidi. Ciri-ciri aswaja dalam bidang akidah adalah mengedepankan antara dalil naqli dan aqli. Naqli yang dimaksud adalah AlQur’an, sedangkan Aqli adalah cara berfikir sehat atau akal sehat. Ciri yang kedua adalah yakin bahwa Tuhan itu Esa atau satu, tidak ada yang bisa menyerupai-Nya. Ciri yang ketiga adalah tidak semena-mena mengkafirkan sesama makhluk karena sebuah perbedaan furu’. Pokok-pokok ajaran aswaja dalam bidang fikih atau kata lain hukum Islam mengikuti madzhab Hanafi, Maliki, Syafi’i dan Hambali. Pada pokok ajaran ini, awaja lebih mengedepankan dan menekankan pentingnya sebuah ijtihad, qiyas dan ijma’ dalam hal menetapkan hukum Islam dan juga tetap menghormati perbedaan keyakinan atau pendapat. Pokok-pokok ajaran aswaja dalam bidang tasawuf atau etika dan spiritual. Yang dimaksudkan adalah dimana aswaja dalam bidang ini bertujuan untuk membersihkan hati dan memperbaiki akhlak. Tokoh dalam bidang tasawauf diantaranya adalah Imam Ghazali dan Imam Junaid. Fokus aswaja dalam bidang tasawuf adalah pembentukan dan penekanan terhadap akhlak mulia.
Evidence-Based Management Approach In Health Service Policy Decision-Making At Clinic of Plantation Company X Hidayat, Asep; Wardani, Ratna; Agustin
Health & Medical Sciences Vol. 2 No. 4 (2025): August
Publisher : Indonesian Journal Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47134/phms.v2i4.460

Abstract

The research comprehensively examines the application of Evidence-Based Management (EBMgt) in decision-making for health service policies at Clinic of Plantation Company X. The main focus is on the influence of six types of evidence: Scientific and Research Evidence, Hospital Facts and Information, Political-Social Development Plans, Professional Managerial Expertise, Ethical-Moral Evidence, and Stakeholder Values and Expectations on policy decisions in the clinic. This study uses a quantitative method with a Structural Equation Modeling (SEM) approach based on Partial Least Squares (PLS). Data were collected through structured questionnaires from 110 respondents comprising managers and decision-makers at the clinic. Instrument validity and reliability were tested before conducting the measurement and structural model analysis. The findings show that all six evidence dimensions significantly affect policy decision-making (p < 0.05). The measurement model met convergent and discriminant validity criteria with AVE and composite reliability values above 0.70. Integrating these evidence dimensions enhances the quality, effectiveness, and accountability of managerial decisions at the clinic. The research highlights the importance of a holistic EBMgt approach combining empirical data, professional expertise, and ethical-social aspects to support effective and responsible policy decisions in healthcare services. The study recommends strengthening the use of multiperspective evidence in clinic policy management to achieve better and sustainable service outcomes.
Analisis Pilkada Medan pada Sosial Media Menggunakan Analisis Sentimen dan Social Network Analyisis Anam, M. Khairul; Firdaus, Muhammad Bambang; Fitri, Triyani Arita; Lusiana; Agustin, Wirta; Agustin
The Indonesian Journal of Computer Science Vol. 11 No. 1 (2022): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v11i1.3027

Abstract

The simultaneous regional head elections were over, but during the campaign until it was decided to become regional head there were many comments, both pro and contra. The city of Medan is one of the regions that will hold the 2020 ELECTION during the pandemic. The Medan City Election has decided that the pair Bobby Nasution and Aulia Rachman have won. This victory certainly gets a variety of comments on social media, especially Twitter. This study conducts sentiment analysis to see the sentiment that occurs, namely seeing negative, positive, or neutral comments. This sentiment analysis uses two methods to see the resulting accuracy, namely Support Vector Machine (SVM) and Naïve Bayes Classifier (NBC). This study also looks at the interactions that occur using Social Network Analysis (SNA). In addition to sentiment analysis and SNA, this study also looks at the existence of BOT accounts used in the #PilkadaMedan. The results obtained from the sentiment analysis show that NBC has the highest accuracy, which is 81, 72% with a data proportion of 90:10. Then on SNA, the @YanHarahap account got the highest nodes, namely 911 nodes. Then from 10326 tweets, 11% were suspected of being BOT by the DroneEmprit Academic system.
Analisis Sentimen Layanan Hotel Menggunakan Algoritma Extra Trees: Studi Kasus pada Ulasan Pelanggan Aprilita, Windi; Junadhi; Agustin; Hadi Asnal
The Indonesian Journal of Computer Science Vol. 13 No. 3 (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.v13i3.4014

Abstract

This research aims to analyze the sentiment of hotel services based on customer reviews using the Extra Trees algorithm. This method was tested on a dataset containing customer reviews about hotel services. The evaluation is done by taking into account the accuracy, precision, recall, and F1 score of the developed model. The results showed that the Extra Trees algorithm was able to achieve an accuracy of 85.05%, with a precision of 84.46%, a recall of 97.00%, and an F1 score of 90.17%. These findings indicate that the Extra Trees algorithm has good performance in analyzing hotel service sentiment based on customer reviews. The implication of this research is to provide guidance to hotels to understand and improve their service quality based on feedback from customers. In addition, this research can also be the basis for further development in the field of sentiment analysis and customer service in the tourism industry.
OPTIMALISASI KINERJA KLASIFIKASI TEKS BERDASARKAN ANALISIS BERBASIS ASPEK DAN MODEL HYBRID DEEP LEARING Salsabila Rabbani; Agustin; Susandri; Rahmiati; M. Khairul Anam
The Indonesian Journal of Computer Science Vol. 13 No. 3 (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.v13i3.4034

Abstract

The conflict between Palestine and Israel has generated strong debates and reactions on social media, including in Indonesia. Public perception of various aspects is certainly important to identify issues in the Palestinian-Israeli conflict. However, the process of manually classifying aspects of the Palestinian-Israeli conflict requires human resources and considerable time. This research aims to explore the views of Indonesians on the Palestinian-Israeli conflict through sentiment analysis based on aspects of Territory, Religion, Politics, and History. Using deep learning technology, specifically a combination model of Convolutional Neural Networks with Long Short-Term Memory (CNN-LSTM), this research analyzes opinion and views data collected from X social media platform (Twitter). This research shows the results of the dataset obtained that the Political aspect dominates more than other aspects. The model evaluation results obtained an accuracy value of 96%, which indicates that the model's ability to classify X users' sentiments towards the Palestinian-Israeli conflict achieved a high level of success.
Klasifikasi Emosi Terhadap Konflik Israel-Palestina Menggunakan Algoritma Gated Recurrent Unit Saputra, Eko Ikhwan; Fatdha, T.Sy. Eiva; Agustin; Junadhi; M. Khairul Anam
The Indonesian Journal of Computer Science Vol. 13 No. 4 (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.v13i4.4106

Abstract

The Israel-Palestine conflict intensified following the October 7, 2023, attack by Hamas on Israel, triggering various emotional reactions on social media. Emotion classification is crucial for understanding public sentiment related to this conflict. This study utilizes 9,917 tweets from platform X (Twitter) to classify emotions such as joy, sadness, anger, fear, disgust, and surprise. The deep learning algorithm used is Gated Recurrent Unit (GRU), developed with three different training and testing data splits: 70:30, 80:20, and 90:10. For text representation, Global Vector (GloVe) word embedding is employed. Given the imbalanced dataset, this study applies the Synthetic Minority Over-sampling Technique (SMOTE) to address class imbalance. The research results indicate that the GRU model with a 90:10 data split without using SMOTE achieves the highest accuracy of 75%, followed by the models with 70:30 and 80:20 splits, which each have an accuracy of 73%.
Penerapan Algoritma Convolutional Neural Network Untuk Klasifikasi Penyakit Kanker Kulit Septhya, Dhini; Rahmaddeni; Susanti; Agustin
The Indonesian Journal of Computer Science Vol. 13 No. 4 (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.v13i4.4262

Abstract

The skin is an important organ that protects the human body, so early treatment is essential to prevent diseases such as skin cancer. Skin cancer is a serious disease that can be fatal ana requires high treatment costs. It ranks thirds after cervical cancer and breast cancer in Indonesia, with causative factors including genetics and exposure to UV radiation. Early detection and proper diagnosis are essential to increase the chances of recovery, so skin cancer classification is necessary to avoid delays in treatment. Deep Learning methods, particularly Convolutional Neural Network (CNN), have been shown to provide significant result in image classification with high accuracy. VGG16 and DenseNet121 are two popular CNN architecture used in image classification. This study aims to compare the performance of skin cancer classification using VGG16 and DenseNet121. The result show that the DenseNet121 architecture provides higher accuracy compared to the VGG16 architecture, with 93% accuracy for train data and 79% for test data, while the VGG16 architecture achieves 80% accuracy for train data and 74% for test data. These results show that the DenseNet121 architecture is superior in skin cancer classification, providing important information for more accurate diagnosis
Pengkajian Fisik Pada Ibu Post Partum :Systematic Review Agustin; Diana Ulfah; Gita Mujahidah; Vina Fuji Lestari; Rizky Meilando
Jurnal Ilmiah Kesehatan Mandira Cendikia Vol. 3 No. 1 (2024)
Publisher : YAYASAN PENDIDIKAN MANDIRA CENDIKIA

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Abstract

Mayoritas sekitar 140 juta kelahiran yang terjadi secara global setiap tahun di kalangan wanita tanpa faktor risiko komplikasi sendiri atau bayi mereka di awal dan selama ini tenaga kerja. Meskipun demikian, waktu kelahiran sangatlah penting untuk kelangsungan hidup wanita dan bayinya, sebagai resiko morbiditas dan mortalitas bisa meningkat jauh jika komplikasi muncul. Penting melakukan pengkajian fisik pada ibu postpartum. Tujuan : untuk mensistensis penelitian-penelitian secara empiris sehingga dapat mengidentifikasi pengkajian fisik pada ibu postpartum. Metode Penelitian : Database yang digunakan dalam adalah Willey, Pubmed, Science Direct, Sprink Link, Cambridge, dan SAGE Journal. Kata kunci yang digunakan adalah adalah physical AND examination AND postpartum AND Mother AND Women. Kriteria inklusi yang diambil yaitu artikel memiliki Found PDF, dipublikasikan full text dan open access, dalam rentang waktu tahun 2010 – 2020, artikel memiliki DOI, penelitian Kuantitatif, serta artikel membahas tentang Pengkajian Fisik Pada Ibu Postpartum. Hasil pencarian didapatkan 20.342 artikel sesuai dengan kata kunci, sebanyak 10.633 dari Wiley Online Library, Pubmed sebanyak 2248, Science Direct sebanyak 251, Springer Link sebanyak 5432 dan SAGE journals sebanyak 1778 artikel. Setelah disesuaikan kriteria inkluasi, maka artikel yang tersisa sebanyak sebanyak 4 artikel, terdiri dari pubmed 1, Willey 1, SAGE journal 1 dan Springe Link 1. Hasil : Proses pencarian didapatkan 4 artikel yang berkaitan dengan pemeriksaan fisik post partum. Dari 4 artikel yang terpilih menjelaskan tentang bagaimana pengkajian fisik pada ibu post partum yang bertujuan untuk mengetahui bagaimana keadaan ibu post partum sehingga apabila ada komplikasi yang terjadi segera ditangani dengan cepat. Kesimpulan dan saran : Pengkajian postnatal pada ibu menjadi bagian penting dalam memberikan perawatan kepada ibu melahirkan. Dalam memberikan perawatan postnatal kepada ibu dimulai dalam waktu satu jam setelah plasenta lahir dan berlanjut hingga enam minggu berikutnya.
Co-Authors Ahlunansar Akbar, Hairil Amaliah Anam, M Khairul Anam, M. Khairul Anisa Maulidya Aprilita, Windi Ardiansyah Arifin, Inayah az zahra Arismunandar Asep Hidayat Diana Ulfah Edwar Ali Edwar Ali Evi Nurjanah, Evi Fatdha, T.Sy. Eiva Firdaus, Muhammad Bambang Gita Mujahidah Gunadi Hadi Asnal, Hadi Hamdani Handoko Harianto, Helfin Herwin Iskandar Zulkarnaen Junadhi Junadhi Kristianto, Yahya Endra Kudadiri, Parlindungan Lusiana M. Jamaris Meilando, Rizky Meiriza, Adellia Miftakhul Jannah Muhamad Muliyono Muzayyana Nengsi Sapitri Nurul Hikma Saleh, Sitti Rahmaddeni Rahmaddeni Rahmiati Ratna Wardani Rizky Meilando Saifuddin Salsabila Rabbani Saputra, Eko Ikhwan Septhya, Dhini Susandri, Susandri SUSANTI Tashid Triyani Arita Fitri Vina Fuji Lestari Wirta Agustin