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All Journal Jurnal INKOM JIPM (Jurnal Ilmiah Pendidikan Matematika) Jurnal Penelitian Pendidikan IPA (JPPIPA) Al-Albab Syntax Literate: Jurnal Ilmiah Indonesia BENTANG : Jurnal Teoritis dan Terapan Bidang Rekayasa Sipil Paedagoria : Jurnal Kajian, Penelitian dan Pengembangan Kependidikan Minda Baharu Jurnal Abdimas PHB : Jurnal Pengabdian Masyarakat Progresif Humanis Brainstorming Metahumaniora Auladuna : Jurnal Prodi Pendidikan Guru Madrasah Ibtidaiyah SCAFFOLDING: Jurnal Pendidikan Islam dan Multikulturalisme Al-Aqidah: Jurnal Studi Islam Syntax Idea MADROSATUNA : Jurnal Pendidikan Guru Madrasah Ibtidaiyah Jurnal Inovasi Pendidikan dan Sains JURNAL KOMUNIKASI DAN BISNIS Jurnal Inovasi, Evaluasi dan Pengembangan Pembelajaran (JIEPP) Bulletin of Information Technology (BIT) Literasi Nusantara SITTAH: Journal of Primary Education Maternity and Neonatal : Jurnal Kebidanan Amare Jurnal Farmasi Indonesia TOFEDU: The Future of Education Journal Coreid Journal Midang Ta'dibiya: Jurnal Agama dan Pendidikan Islam Journal of Elektronik Sistem InformasI Kabuyutan: Jurnal Kajian Iilmu Sosial dan Humaniora Berbasis Kearifan Lokal Tadibiya; Jurnal Agama dan Pendidikan Islam Serat: Journal of Literature and Cultural Studies THORIQOTUNA: Jurnal Pendidikan Islam
Nana Suryana
Balai Pengkajian dan pengembangan Komunikasi dan Informatika Bandung
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Journal : Coreid Journal

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Information Systems Strategic Planning in Improving Organizational Operational Management with Ward and Peppard Fachrully, Fachrully Adira Muhammad; Suryana, Nana
CoreID Journal Vol. 2 No. 2 (2024): July 2024
Publisher : CV. Generasi Intelektual Digital

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60005/coreid.v2i2.31

Abstract

The Sarijadi Village Karang Taruna is one of the social institutions in the Sarijadi Village area which plays a role in improving social welfare for the community, of course by holding activities such as social services. To support these activities, Karang Taruna needs more contributions from its own community, both in the form of suggestions and criticism, as well as relevant data. Not only does that data exist, but data such as attendance lists, schedule boards, minutes, and so on are needed for future needs. In collecting this data, Karang Taruna must have good and structured operational management so that the data it already has can be stored properly and minimize data loss. In improving operational management, Karang Taruna can use an information system, so that the resources they have can be used efficiently and effectively. In developing an organization's operational management information system, a good and structured information system strategic planning is required. In writing this article, the researcher used the Ward and Peppard research method. Where by using this method, information system strategic planning, Karang Taruna can better understand its external environment, help adapt, and improve operational management. Several strategic planning techniques such as Value Chain Analysis, Five Forces Analysis, and SWOT Analysis are used to analyze the internal and external environment. In the end, this research can produce recommendations for organizations in establishing an IS/IT unit and improving operational management for organizational sustainability.
Natural Language Processing and Random Forest for Mental Health Symptom Identification Using Social Media Data Sugara, Sigit; Dauni, Popon; Putri, Novianti Indah; Saputra, Yogi; Suryana, Nana
CoreID Journal Vol. 3 No. 3 (2025): November 2025
Publisher : CV. Generasi Intelektual Digital

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60005/coreid.v3i3.145

Abstract

This study explores the implementation of machine learning models, specifically Natural Language Processing (NLP) and Random Forest, for detecting mental health symptoms based on text analysis of web-sourced data. The research addresses the challenges of analyzing highly subjective and dynamic text in social media content to identify patterns associated with anxiety, depression, and stress. The methodology involves several preprocessing steps including case folding, cleansing, language normalization, negation conversion, stopword removal, and tokenization, followed by TF-IDF weighting and Random Forest classification. The model evaluation revealed a high accuracy rate of approximately 80%, although achieving a confidence level of 75% proved challenging. This research demonstrates that despite the inherent difficulties in predicting subjectively variable text, the machine learning approaches employed show satisfactory performance in identifying mental health symptoms, offering potential for early detection and intervention systems.
Co-Authors Abdillah , Mursyid Abdul Hamid Adistiani, Salma Sopia Afrianda, Rio AGUSTIANA, ALIEF aida fitria Annisa, Dian Annisa, Fitri Artha Mefia, Elsa Kirana Arujisaputra, Erwin Teguh Arvio, Yozika Asep Salahudin Aziz, Faisal Babang Robandi Baha Udin Budi, Asep Cecep Hilman DARMANSYAH . Dasim Budimansyah Datau, Sjahriani Dauni, Popon Didi Rosiyadi Dina Pratiwi Dwi Santi Drajat, Dera Nurkhusniah Dwiyanti, Fasha Eko Darma Fachrully, Fachrully Adira Muhammad Fajar Prihesnanto, Fajar Fernandez, Alex Hadikaryana, Oscar Hasanah Pratiwi Harahap Herlina, R. Lisye Hidayatullah, Mochammad Irfan Husain, Adam Indah N. D., Mutiara Irman Hariman Kafiul Khuluq, Muhammad Shahinshah Kriswanda Krishnapatria Makkulau, Andi Maryani, Neneng Mauliza, Rully Mauriraya, Kartika Tesya Mochamad Irfan Hidayatullah Mumuh, Mumuh Munggaran, Nita Anjung Murdianto, Yudi Novianti Indah Putri Nugraha, Agus Nur Afiah, Nur Nurachadijat, Kun Nuriman Pakpahan, Ferry Parsaulian Pasra, Nurmiati Prima Agustina Mariamurti Purwadi Purwadi R., Satrya Salam, Faiz Abdul Santoso, Try Riduwan Setiyani Setiyani Sikumbang, Sri Rintani Soraya Uli, Elisabeth Sugara, Sigit Suharyanto Suhena, Ena Sulaeman Deni Ramdani Sulistiani, Denita Supriyatna, Deddy Taufik, Cevi Mochamad W, Warkianto Wahyu Sopandi Waway Tiswaya Y., Indriarto Yadi Ruyadi Yessy Yanitasari Yogi Saputra, Yogi Yudiana, Yudiana Yusransyah, Yusransyah Zulaita