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All Journal Intizar Jurnal Teknologi dan Sistem Komputer Indonesian Journal of Artificial Intelligence and Data Mining ILKOM Jurnal Ilmiah CARADDE: Jurnal Pengabdian Kepada Masyarakat Building of Informatics, Technology and Science International Journal of Advances in Data and Information Systems Journal of Intelligent Computing and Health Informatics (JICHI) Jurnal Pengabdian Masyarakat Intimas (Jurnal INTIMAS): Inovasi Teknologi Informasi Dan Komputer Untuk Masyarakat Prosiding University Research Colloquium Jurnal Pengabdian Masyarakat Sains dan Teknologi Jurnal Pengabdian Informatika (JUPITA) Indonesia Bergerak: Jurnal Hasil Kegiatan Pengabdian Masyarakat Aksi Nyata : Jurnal Pengabdian Sosial dan Kemanusiaan Journal of applied statistics and data mining Profetika: Jurnal Studi Islam
Istiawan, Deden
Institut Teknologi Statistika Dan Bisnis Muhammadiyah Semarang
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Law, Crime, Criminology & Criminal Justice Medicine & Pharmacology Public Health Social Sciences Other

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Penerapan Partition Entropy Index, Partition Coefficient Index dan Xie BeniIndex untuk Penentuan Jumlah Klaster Optimal pada Algoritma Fuzzy C-Means dalam Pemetaan Tingkat Kesejahteraan Penduduk Jawa Tengah Mashfuufah, Syayidati; Istiawan, Deden
Prosiding University Research Colloquium Proceeding of The 7th University Research Colloquium 2018: Mahasiswa (student paper presentation)
Publisher : Konsorsium Lembaga Penelitian dan Pengabdian kepada Masyarakat Perguruan Tinggi Muhammadiyah 'Aisyiyah (PTMA) Koordinator Wilayah Jawa Tengah - DIY

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Abstract

Kemiskinan merupakan salah satu indikator ekonomi untuk melihattingkat kesejahteraan penduduk di suatu daerah. Menurut data BPSpada September 2016, Jawa Tengah tercatat sebagai provinsi dengantingkat kemiskinan tertinggi di Jawa. Dalam strategi penanggulangankemiskinan dibutuhkan data kemiskinan yang akurat sesuaikarakteristik tingkat kesejahteraan, sehingga pemerintah dapatmenghasilkan kebijakan yang tepat sasaran dan tepat guna. Untukpengelompokkan tingkat kesejahteraan kabupaten/kota di JawaTengah diusulkan algoritma Fuzzy C-Means (FCM). FCM memilikikelebihan dalam ketepatan penempatan pusat klaster dan sangat stabilterhadap outlier, namun jumlah klaster dalam FCM harus ditentukanterlebih dahulu sebelum melakukan penelitian. Untuk penentuanjumlah klaster optimal pada algoritma FCM, pada penelitian inidiusulkan Cluster Validity Index (CVI). CVI merupakan sebuah ukuranvaliditas untuk menemukan jumlah klaster optimal yang sepenuhnyadapat menjelaskan struktur data dengan cara mengukur derajatkekompakan dalam satu klaster dan separasi antar klaster. Padapenelitian ini diusulkan CVI Partition Entropy Index (PEI), PartitionCoefficient Index (PCI) dan Xie Beni Index (XBI). Hasil penelitianmenunjukkan jumlah klaster optimal berdasarkan CVI adalah duaklaster. Klaster pertama terdiri dari 22 kabupaten/kota dan klasterkedua terdiri dari 13 kabupaten/kota.
Penerapan Algoritma Self Organizing Maps Untuk Pemetaan Penyandang Kesejahteraan Sosial (PMKS) di Provinsi Jawa Tengah Tahun 2016 Hafiludien, Amrul; Istiawan, Deden
Prosiding University Research Colloquium Proceeding of The 7th University Research Colloquium 2018: Mahasiswa (student paper presentation)
Publisher : Konsorsium Lembaga Penelitian dan Pengabdian kepada Masyarakat Perguruan Tinggi Muhammadiyah 'Aisyiyah (PTMA) Koordinator Wilayah Jawa Tengah - DIY

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Masalah Kesejahteraan Sosial atau Penyandang MasalahKesejahteraan Sosial (PMKS) adalah seseorang atau keluarga karenaadanya suatu hambatan, kesulitan atau gangguan tidak bisamelaksanakan fungsi sosialnya dan karenanya tidak dapat menjalinhubungan yang serasi serta kreatif dengan lingkungannya sehinggatidak dapat memenuhi kebutuhan hidupnya baik jasmani, rohani,sosial secara memadai dan wajar. Pengelompokan daerahberdasarkan indikator Penyandang Masalah Kesejahteraan Sosial(PMKS) sangat penting dilakukan untuk memperoleh gambaranmasalah PMKS sehingga dapat mengambil kebijakan dalam halmenentukan sasaran dan memberikan rekomendasi untuk intervensipenyandang kesejahteraan sosial di tingkat provinsi Jawa Tengah.Banyak penelitian yang telah dilakukan untuk menganalisis datasecara efektif dan efisien, salah satunya dengan data mining. Dalamdata mining salah satu metode yang dapat digunakan untukpengelompokan adalah olgaritma Self Organizing Maps. SelfOrganizing Maps(SOM) diperkenalkan oleh kohonen pada tahun 1982,SOM digunakan untuk mengimplementasikan data berdimensi tinggidan memvisualisasikanya secara teratur kedalam dimensi rendah..Kemampuan dalam visualisasi ini dapat mengatasi masalah dalammetode cluster lain yang sulit jika data berdimensi tinggi.
PENENTUAN PUSAT AWAL KLASTER ALGORITMA K-MEANS UNTUK PEMETAAN TINGKAT KESEJAHTERAAN DI PROVINSI JAWA TENGAH Istiawan, Deden
Prosiding University Research Colloquium Proceeding of The 8th University Research Colloquium 2018: Bidang MIPA dan Kesehatan
Publisher : Konsorsium Lembaga Penelitian dan Pengabdian kepada Masyarakat Perguruan Tinggi Muhammadiyah 'Aisyiyah (PTMA) Koordinator Wilayah Jawa Tengah - DIY

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Abstract

Kesejahteran mempunyai arti yang relatif, dinamis dan kuantitatif. Sampai saat ini rumusanya tidak pernah selesai karena akan terus berkembang seiring dengan perkembangan zaman. Kesejahteraan secara umum adalah suatu keadaan dimana segenap warga negara selalu berada dalam kondisi yang serba kecukupan dalam segala kebutuhannya. Kemiskinan di Provinsi Jawa Tengah masih berada di atas kemiskinan nasional. Pengelompokkan kemiskinan merupakan salah satu cara untuk mengidentifikasi karakteristik tingkat kesejahteraan rakyat pada tiap daerah agar dalam mengambil kebijakan dan strategi pembangunan tepat sasaran dan tepat guna. Algoritma K-means merupakan salah satu algoritma klastering yang paling sering digunakan untuk pengelompokan objek dikarena kemudahan dalam pengaplikasianya dan sangat efisien untuk mengelompokan data yang besar, namun algoritma K-means memiliki kelemahan pada pemilihan pusat awal klaster secara acak, sehingga menyebabkan kinerja algoritma K-means menurun. Pada penelitian ini diusulkan metode penentuan pusat awal klaster pada algoritma K-means. Hasil penelitian menunjukan bahwa metode yang diusulkan memiliki kinerja yang lebih baik daripada algoritma K-means Standar.
Pelatihan Microsoft Excel Dalam Pengembangan Profesional PT. Nusantara Building Industries Huda, Nurul; Istiawan, Deden; Masitha, Alya; Nanda Zhafran Mahendra
Jurnal Pengabdian Informatika Vol. 2 No. 3 (2024): JUPITA Volume 2 Nomor 3, Mei 2024
Publisher : Jurusan Informatika, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Udayana

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Abstract

Kemajuan teknologi saat ini sangat signifikan perkembangannya, sehingga pekerja mendapatkan kemudahan untuk mengatasi berbagai masalah dalam pekerjaan. Teknologi dirancang untuk diterapkan dalam situasi yang nyata untuk memecahkan suatu persoalan dan untuk meningkatkan kinerja di berbagai sektor perusahaan. Perusahaan membutuhkan karyawan yang memiliki skill dalam mengolah data perusahaan, seperti: gaji karyawan, data karyawan, data barang yang masuk dan keluar, dll. Salah satu tools yang paling sering digunakan oleh berbagai perusahaan adalah Microsoft Excel. Microsoft Excel merupakan salah satu tools dari Microsoft Office. Pentingnya mengasah skill karyawan dengan mengadakan pelatihan guna mengembangkan kemampuan yang sudah dimiliki oleh pekerja. Pengabdian masyarakat ini bertujuan untuk mengevaluasi efektivitas pelatihan Microsoft Excel dalam meningkatkan keterampilan teknis dan produktivitas karyawan. Pelatihan ini dirancang untuk memenuhi kebutuhan operasional perusahaan dalam mengolah data bahan bangunan, data karyawan, dan data gaji dengan lebih efisien dan akurat. Berdasarkan hasil survei yang telah diberikan peserta dapat disimpulkan bahwa pelatihan Microsoft Excel ini berjalan dengan sangat baik dan materi yang disampaikan sesuai dengan kebutuhan karyawan PT. Nusantara Building Industries dalam pekerjaannya.
Geospatial Model Optimization for Mapping Social Vulnerability to Natural Disasters Using Fuzzy Geographically Weighted Clustering and Flower Pollination Algorithm Istiawan, Deden; Wulandari, Ratri; Ustyannie, Windyaning
International Journal of Advances in Data and Information Systems Vol. 6 No. 3 (2025): December 2025 - International Journal of Advances in Data and Information Syste
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59395/ijadis.v6i3.1452

Abstract

This study analyzes social vulnerability to natural disasters in Indonesia through a geospatial optimization model integrating Fuzzy Geographically Weighted Clustering (FGWC) with the Flower Pollination Algorithm (FPA). The hybrid FGWC–FPA enhances clustering accuracy by optimizing spatial parameters and addressing the limitations of index-based and non-spatial methods. The model tested two to four clusters, with the optimal configuration producing four distinct vulnerability groups. Cluster 1 (114 districts) exhibits high poverty, weak infrastructure, and low literacy; Cluster 2 (79 districts) reflects demographic pressure and gender-related inequality; Cluster 3 (87 districts) shows low education and poor disaster preparedness; while Cluster 4 (234 districts) represents health- and age-related vulnerability. A comparison with the 2024 Indonesian Disaster Risk Index (IRBI) shows strong spatial consistency, especially in high-risk regions such as Papua, Maluku, and Sulawesi. The FGWC–FPA model provides finer spatial granularity, allowing the identification of region-specific social issues not captured by deterministic index approaches. The findings validate national disaster risk patterns and offer complementary insights for implementing the National Disaster Management Master Plan (RIPB) 2020–2044, supporting regional prioritization, resource allocation, and capacity-building strategies.
RELIGIOUS HARMONY INDEX IN SPECIAL REGION OF YOGYAKARTA Deden Istiawan; Arif Gunawan Santoso; R Rosidin; Ika Safitri Windiarti
Profetika: Jurnal Studi Islam Vol. 24 No. 02 (2023): Profetika Jurnal Studi Islam 2023
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/profetika.v24i02.1900

Abstract

The existence of the Special Region of Yogyakarta as a city of students, culture, and tourism holds diversity both ethnically, culturally, and religiously; therefore, the Special Region of Yogyakarta is called the city of tolerance. The plurality of the Special Region of Yogyakarta may give rise to conflicts and divisions, including inter-religious conflicts if they are not appropriately managed. One of the successes of developing religious harmony can be assessed by looking at the most basic indicators of harmony at the national and regional levels. This study aims to measure inter-religious harmony in the Special Region of Yogyakarta. Variables that become measuring instruments have three dimensions: tolerance, dimensions, and dimensions of cooperation. The study used quantitative methods with a total sample of 400 respondents spread across Yogyakarta City, Bantul Regency, Kulon Progo Regency, and Gunung Kidul Regency. The research findings show that the index of inter-religious harmony in the Special Region of Yogyakarta is 78.90, or in the high level of religious harmony category. For this reason, maintenance must continue improving to achieve a harmonious, harmonious, and harmonious religious life. Although, in general, it is in a high category, there are still sub-dimensions that need special attention, namely caring for the construction of other places of worship and being president or regional head regardless of religion.
Optimization-Based Geospatial Clustering Using Fuzzy Geographically Weighted Clustering and Flower Pollination Algorithm for Stunting Risk Mapping Ngatimin, Ngatimin; Istiawan, Deden; Ustyannie, Windyaning; Riansyah, Rahmat; Sholicah, Ameliatus
ILKOM Jurnal Ilmiah Vol 18, No 1 (2026)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v18i1.3130.151-164

Abstract

Stunting remains a major public health challenge in Indonesia, characterized by significant regional disparities and complex multidimensional determinants. Effective intervention strategies therefore require analytical approaches that are capable of capturing spatial heterogeneity and identifying region-specific vulnerability patterns. This study applies Fuzzy Geographically Weighted Clustering (FGWC) optimized using the Flower Pollination Algorithm (FPA) to map district-level stunting vulnerability and identify priority intervention areas. The analysis covers 514 districts using 21 multidimensional indicators representing health, nutrition, housing conditions, food security, social protection, and demographic characteristics derived from the Central Statistics Agency. The integration of FGWC with FPA enhances clustering performance by incorporating spatial dependence and metaheuristic optimization, enabling the algorithm to produce more stable and geographically sensitive clusters. Cluster validity indices confirm that a four-cluster solution provides the most optimal segmentation of stunting vulnerability. The results reveal distinct regional structures, socioeconomic-driven vulnerability associated with limited asset ownership, high dependence on social assistance and large household size, multidimensional deprivation concentrated primarily in eastern Indonesia, and nutrition-related vulnerability linked to breastfeeding duration and food security. These findings demonstrate that stunting patterns in Indonesia are spatially heterogeneous and influenced by diverse structural factors. The proposed FGWC–FPA framework offers a robust geospatial optimization approach that can support more precise, evidence-based, and region-specific strategies for accelerating stunting reduction.
Edukasi Cara Bermedia Sosial dan Pencegahan Konten Internet Negatif bagi Masyarakat Kelurahan Polaman Deden Istiawan; Khoirul Anam Dahlan
Aksi Nyata : Jurnal Pengabdian Sosial dan Kemanusiaan Vol. 3 No. 3 (2026): Juli : Aksi Nyata : Jurnal Pengabdian Sosial dan Kemanusiaan
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62383/aksinyata.v3i3.3342

Abstract

Rapid development of information and communication technology has significantly increased use of the internet and social media across various segments of society. However, adoption grew of digital technology accompanied by numerous risks, included spread of misinformation, privacy violations, misuse of personal data, cyberbullying, and online fraud. These challenges highlight importance of digital literacy in foster public awareness and promote safe and responsible use of technology. This education aimed to enhance the understanding of residents of Polaman Village regarding safe social media practices, personal data protection, misinformation prevention, and digital fraud awareness. Methods employed included presentations, interactive discussions, case studies, and question-and-answer sessions. Topics covered digital footprints, privacy, personal data protection, cyberbullying, identification of hoaxes, and awareness of fraud schemes involve APK files and suspicious links. Activity was conducted face-to-face and involved community members and village officials as participants. The results indicated an improvement in participants understanding of the importance of protected personal data, identify reliable information, and adopt responsible behavior in digital environments. Participant enthusiasm during discussions also demonstrated that materials presented were highly relevant to current community needs. Therefore, this program successfully increased public awareness of the challenges and risks associated with the digital era.
Pelatihan Berbasis Praktik From Data to Decision: Peningkatan Literasi Data dan Kapasitas Pengambilan Keputusan Strategis Karyawan pada Perusahaan Properti dan Ritel SR Land Group Rowiyani Rowiyani; Nurul Huda; Deden Istiawan; Atika Nurani Ambarwati; Wulan Bhakti Pertiwi
CARADDE: Jurnal Pengabdian Kepada Masyarakat Vol. 9 No. 1 (2026): Agustus
Publisher : Ilin Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31960/caradde.v9i1.3367

Abstract

This community service activity aims to improve data literacy and strategic decision-making capacity among employees of SR Land Group (SRGroup), a business group engaged in property development and shopping-mall management with business units spread across several cities. The activity employed a one-group pretest-posttest evaluation design combined with a practice-based training approach (experiential learning), comprising interactive lectures, demonstrations, hands-on practice, case studies, and a capstone project. The training involved 62 employees from eight business units and various job levels, from staff to board of directors, assigned by SRGroup's management and HR & GA division. Effectiveness was measured through pre-test and post-test questionnaires and a Google Form-based satisfaction survey completed by 39 participants (62.9% response rate) and analyzed using descriptive quantitative statistics. Results showed an increase in the average score from 69.7 (pre-test) to 93.2 (post-test), an improvement of approximately 33.7%. Overall satisfaction was high, with 87.2% of participants reporting being satisfied to very satisfied. Participants were also able to produce simple analytical dashboards using Google Looker Studio as the capstone project output. These findings indicate that practice-based training has the potential to improve data literacy and readiness for data-driven decision-making among cross-divisional employees, although the lack of a comparison group limits causal generalization. The novelty of this activity lies in its cross-divisional, integrated data-literacy training approach implemented within a medium-to-large property and retail company, a segment rarely targeted by community-based data literacy programs.
Co-Authors Adilah Ahmad, Muna Adiyah Mahiruna ALYA MASITHA Amrul Hafiludien Arif Arrahman, Malik Atika Nurani Ambarwati Chaerul Iqbal , Ilham Chintya Devi Panglipuring Sriaji Eko Hari Rachmawanto Firdaus, Lucky Nur Rohman Hafiludien, Amrul Ika Safitri Windiarti Khikmah, Laelatul Khoirul Anam Dahlan Khotimah, Nur Laelatul Khikmah Mahiruna, Adiyah Mashfuufah, Syayidati Nahdluddin Nanda Zhafran Mahendra Ngatimin NGATIMIN, NGATIMIN Nur Cahyani, Annisa Nur Khotimah Nurul Huda Nurul huda Nurul Huda Prayogi, Sukmono Yogi R Rosidin Ratri Wulandari Riansyah, Rahmat Rowiyani Rowiyani Santoso, Arif Gunawan Sholicah, Ameliatus Sukmono Yogi Prayogi Sulistijanti, Wellie Syayidati Mashfuufah Wijayaningrum, Taswati Nova Windyaning Ustyannie Wulan Bhakti Pertiwi Yogi Prayogi, Sukmono Zaenah Zilfi, Elok Maria