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All Journal Journal of Applied Data Sciences Kresna: Jurnal Riset dan Pengabdian Masyarakat Journal Of World Science Prosiding Amal Insani Foundation (Indonesian of Interdisciplinary Journal) Bridge: Jurnal Publikasi Sistem Informasi dan Telekomunikasi
Asro Asro
Universitas Primagraha
Religion Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Social Sciences Other

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Strategi Pengembangan Bisnis Laundry Berbasis Online Asro Asro; Iis Istiharoh; Dewi Kania
Prosiding Amal Insani Foundation Vol. 2 (2023): PROSIDING NASIONAL
Publisher : Amal Insani Foundation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56721/prosalif.v2.2023.58

Abstract

In the modern digital era, technology and social media are crucial in supporting businesses, including the laundry business. This business falls under the category of Micro, Small, and Medium Enterprises (MSMEs) that operate in the service sector. Xilaundry, located in Serang Regency, Banten Province, exemplifies how MSMEs utilize technology in their operations. Xilaundry uses social media platforms such as Whatsapp, Instagram, and Facebook for marketing and promotional strategies. Two payment methods are available for customers: conventional (pay on the spot) and digital (ATM, Mobile Banking, OVO, and Gopay). Xilaundry implements a SWOT analysis for its business strategy development. The results show that Xilaundry's business is feasible to run. Xilaundry's finances record a monthly turnover of IDR 6,570,800 and a cash expenditure of IDR 2,890,000. This generates a net profit of around IDR 2,743,800 per month. Thus, Xilaundry can generate a net income of approximately IDR 34,680,000 in a year. In the SWOT and social media context, Xilaundry can leverage its strength in using social media for marketing and promotion (Strength). However, they must maintain service quality to avoid weaknesses in service (Weakness). The opportunity that Xilaundry can take is the increase in social media and digital payment users (Opportunity). At the same time, threats can come from competitors who use social media in their marketing strategies (Threat).
Classification of Traffic Congestion in Indonesia Using the Naive Bayes Classification Method Abdul Robi Padri; Asro Asro; Indra Indra
Journal of World Science Vol. 2 No. 6 (2023): Journal of World Science
Publisher : Riviera Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58344/jws.v2i6.285

Abstract

The purpose of this research is to analyze the accuracy of congestion data using Google Colab in detecting congestion by the province in Indonesia the author tries to test strategies for dealing with congestion in the Indonesian region by utilizing the Naïve Bayes method. In this journal, apply with Google Collab . This research uses data that comes from crawling data on Twitter. Using the Naive Bayes method to find the shortest route is efficient and not congested. Implementation of online school transportation using the naive Bayes method in minimizing travel costs to pick up students can reduce traffic jams, reduce accidents, reduce student tardiness, and minimize travel costs. The Naive Bayes method can be used to identify relevant information about traffic jams in Indonesia through Twitter data with a good degree of accuracy. These results can assist decision-making and strategic planning in overcoming the problem of traffic congestion in Indonesia. Therefore, this research implies that it can help improve the accuracy of traffic congestion data in Indonesia. By using Google Colab, more advanced analysis methods and machine learning algorithms can be applied to process the existing traffic data. Additionally, utilizing Google Colab allows for fast and efficient data processing.
The Public Sentiment Analysis on the 2024 Presidential Election Using Naive Bayes Classifier (NBC) and Support Vector Machine (SVM) On Social Media Data Asro Asro; Nur Azizah; Sudaryono Sudaryono
Prosiding Amal Insani Foundation Vol. 1 (2024): PROSIDING INTERNASIONAL
Publisher : Amal Insani Foundation

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Abstract

This study aims to evaluate the effectiveness of the Naive Bayes Classifier (NBC) and Support Vector Machine (SVM) in analyzing public sentiment from YouTube comments related to the 2024 Indonesian Presidential Election. A total of 1,800 comments, collected from November 2023 to March 2024, were analyzed to test these models. The results show that SVM, with the highest accuracy of 76.33% and precision and F1-Score of 75.29% and 72.67% on the 10% test data, outperformed NBC, which recorded a highest accuracy of 72.19% under similar conditions. These findings highlight the importance of using more sophisticated methods in sentiment analysis to understand the complex and diverse dynamics of public opinion. This study provides valuable insights for stakeholders in developing effective communication strategies and offers a foundation for advancing sentiment analysis methodologies in political contexts.
Strategi Dinamis Menggunakan MongoDB untuk Analisis Sentimen Terhadap Komentar YouTube Pilkada Gubernur Indonesia 2024 Asro Asro; Alwin Hartono Limaran; Agung Wicaksono; Patah Herwanto
KRESNA: Jurnal Riset dan Pengabdian Masyarakat Vol 4 No 2 (2024): Jurnal KRESNA November 2024
Publisher : DRPM Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/kresna.v4i2.149

Abstract

Penelitian ini mengkaji penggunaan MongoDB dalam melakukan analisis sentimen terhadap komentar YouTube terkait Pilkada Gubernur Indonesia 2024. Studi ini mengumpulkan 40,396 komentar melalui YouTube Data API, yang kemudian diproses menjadi 27,102 komentar relevan setelah melalui tahapan preprocessing yang menyeluruh, meliputi case folding, tokenisasi, normalisasi, dan stemming. Tiga algoritma analisis sentimen digunakan dalam penelitian ini: Naive Bayes, Logistic Regression, dan Support Vector Machine (SVM). Di antara ketiganya, Logistic Regression menunjukkan kinerja terbaik dengan tingkat akurasi mencapai 91.39%. Analisis ini memberikan wawasan berharga tentang sentimen publik, secara efektif menangkap sikap dan opini terhadap calon gubernur. Untuk meningkatkan interpretasi hasil, penelitian ini menggunakan teknik visualisasi data seperti Word Cloud dan grafik frekuensi. Representasi visual ini memberikan pemahaman yang lebih jelas tentang frekuensi dan konteks penggunaan kata-kata kunci, sehingga membantu dalam pengembangan strategi komunikasi politik yang efektif dan responsif. Penelitian ini berkontribusi dalam bidangnya dengan mendemonstrasikan potensi MongoDB dalam memproses dan menganalisis data media sosial skala besar untuk analisis sentimen politik. Temuan-temuan ini memiliki implikasi signifikan untuk memahami tren pemilih dan membentuk kampanye politik dalam konteks Pilkada Gubernur Indonesia 2024.
Analisis Literatur Review Perencanaan Strategi Sistem Informasi Menggunakan Metode Pieces Framework Asro Asro; Meisa Monica; Novi Rukhviyanti; M. Yusron
KRESNA: Jurnal Riset dan Pengabdian Masyarakat Vol 4 No 2 (2024): Jurnal KRESNA November 2024
Publisher : DRPM Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/kresna.v4i2.182

Abstract

Perencanaan strategis sistem informasi merupakan kunci penting untuk mengoptimalkan penggunaan teknologi informasi dalam organisasi. Framework PIECES, yang mencakup dimensi Performa, Informasi dan Data, Ekonomi, Kontrol dan Keamanan, Efisiensi, serta Layanan, diarahkan untuk mengatasi masalah umum seperti inefisiensi proses, kekurangan data relevan, dan tantangan keamanan. Penelitian ini bertujuan untuk menganalisis bagaimana metodologi PIECES dapat diaplikasikan dalam strategi sistem informasi melalui tinjauan literatur yang ekstensif. Studi ini melakukan analisis kritis terhadap berbagai penerapan framework PIECES dalam konteks yang berbeda, mencari untuk menilai adaptasi dan efektivitasnya dalam mengatasi tantangan operasional dan regulasi. Hasilnya diharapkan memberikan wawasan mendalam tentang efektivitas PIECES dalam merumuskan strategi informasi yang responsif dan adaptif di era digital. Analisis ini menggali lebih dalam bagaimana penerapan strategis framework dapat memfasilitasi peningkatan keamanan informasi dan efisiensi operasional, serta adaptasi terhadap perubahan teknologi dan regulasi.
Utilizing Sentiment Analysis for Reflect and Improve Education in Indonesia Henderi, Henderi; Asro, Asro; Sulaiman, Agus; Kurniawan, Tri Basuki; Dewi, Deshinta Arrova; AlQudah, Mashal
Journal of Applied Data Sciences Vol 6, No 1: JANUARY 2025
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v6i1.527

Abstract

This study explores the potential of sentiment analysis in providing valuable insights into education in Indonesia based on comments from the YouTube platform. Utilizing the Naive Bayes Classifier method, this research analyzed 13,386 processed comments out of 17,920 original comments. The results show that 53.8% of comments were negative, while 28.5% were positive, and 17.7% were neutral, reflecting diverse perspectives on existing educational issues. The Accuracy of this model reached up to 72.51% with testing on various sample sizes (10%-30%), indicating the model's effectiveness in identifying sentiments. Although the model tends to classify comments as unfavorable, this opens opportunities for introspection and improvement within the educational system. Further analysis with a word cloud revealed dominant keywords, indicating areas that require more attention in public discussions about education. By leveraging this sentiment analysis, the study offers practical and valuable guidance for policymakers to reflect on and enhance educational strategies and policies in Indonesia. This research measures public reactions and aims to foster more constructive and inclusive discussions about the sustainable development of education in Indonesia.
TINJAUAN MANAJEMEN SISTEM MUTU DAN KEAMANAN PANGAN PADA PT. PUSAKA WALET NATURAL INDONESIA Yusron, M.; Asro, Asro
DESANTA (Indonesian of Interdisciplinary Journal) Vol. 5 No. 2 (2025): Maret 2025
Publisher : Desanta Publisher

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Abstract

Penelitian ini bertujuan untuk menganalisis pelaksanaan tinjauan manajemen sistem manajemen mutu dan keamanan pangan berbasis HACCP pada PT. Pusaka Walet Natural Indonesia tahun 2024. Metode yang digunakan adalah pendekatan kualitatif deskriptif dengan strategi studi kasus. Data dianalisis melalui teknik analisis isi terhadap dokumen Management Review 2024. Hasil penelitian menunjukkan bahwa kebijakan mutu dan keamanan pangan telah diimplementasikan secara konsisten sesuai standar SNI CXC 1-1969 dan regulasi ekspor ke Tiongkok. Perusahaan melakukan pembaruan prosedur titik kendali kritis, validasi laboratorium, audit internal, serta tindakan korektif terhadap ketidaksesuaian produk. Ketersediaan bahan baku, kecukupan personil, pemeliharaan infrastruktur, dan pengetahuan organisasi mendukung keberlanjutan mutu produk. Rencana tindak lanjut seperti pembangunan laboratorium internal dan pengujian rutin kandungan Aluminium setiap batch memperkuat kesiapan perusahaan menghadapi tuntutan pasar global. Tinjauan manajemen terbukti berperan strategis sebagai sarana evaluasi, pengendalian, dan perbaikan berkelanjutan pada industri sarang burung walet.
Analisis Literatur Review Perencanaan Strategi Sistem Informasi Menggunakan Metode Metode Five Competitive Force Pada CV. Bio Chitosan Indonesia Susan Juli Safitri; Gelar Alam Ramdhaniawan; Asro Asro; Novi Rukhviyanti
Bridge : Jurnal Publikasi Sistem Informasi dan Telekomunikasi Vol. 2 No. 4 (2024): Bridge: Jurnal Publikasi Sistem Informasi dan Telekomunikasi
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/bridge.v2i4.263

Abstract

The rapid development of science and technology, in line with the progress of time, has led to the increased use of personal computers, playing a crucial role in assisting human tasks. Additionally, the use of technology in work processes helps to improve speed and accuracy compared to not using technology. Today, Systems Information and Technology (SI/IT) are not only needed as tools to support an organization's operational activities but also as an essential aspect of business strategy to achieve organizational goals. Computer-based information systems have now become a primary necessity for fulfilling information needs. Many sectors have utilized computer information systems as a means to simplify tasks. Therefore, this journal will discuss "Information System Strategy Planning using the Five Competitive Forces."
Co-Authors Abda Abda Abdul Robi Padri Agung Wicaksono Alwin Hartono Limaran Dewi Kania Dewi, Deshinta Arrova Gelar Alam Ramdhaniawan Henderi . Iis Istiharoh Indra Indra Kurniawan, Tri Basuki M Yusron M. Yusron Mashal Alqudah Meisa Monica Nur Azizah Patah Herwanto Sudaryono Sudaryono Sulaiman, Agus Susan Juli Safitri