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All Journal Jurnal Akuatika Infotech Journal JURNAL ILMIAH GEOMATIKA MAJALAH ILMIAH GLOBE JITTER (Jurnal Ilmiah Teknologi Informasi Terapan) Krea-TIF: Jurnal Teknik Informatika Jambura Geoscience Review JATI (Jurnal Mahasiswa Teknik Informatika) Jurnal Teknik : Majalah Ilmiah Fakultas Teknik Unpak Journal International Inspire Education Technology (JIIET) Jurnal Penelitian dan Pengabdian Masyarakat Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Jurnal Pengabdian Masyarakat Inovatif Jurnal Pengabdian Masyarakat Inovatif Jurnal Rekayasan Lingkungan dan Biosistem
Iksal Yanuarsyah
Universitas Ibn Khaldun Bogor
Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Earth & Planetary Sciences Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Social Sciences Transportation Other

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POTENSI PENYEBARAN PENYAKIT INFEKSI SALURAN PERNAFASAN AKUT (ISPA) DENGAN METODE K-MEANS CLUSTERING Andry Liu, Wahyu; Yanuarsyah, Iksal; Fatimah, Fety
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 9 No. 2 (2025): JATI Vol. 9 No. 2
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v9i2.13171

Abstract

Infeksi Saluran Pernafasan Akut (ISPA) merupakan salah satu penyakit yang prevalensinya tinggi dan berdampak signifikan terhadap kesehatan masyarakat, terutama di daerah dengan kondisi lingkungan yang kurang mendukung. Permasalahan yang ada di wilayah Gunung Putri salah satunya yaitu potensi terdampak ISPA masih tinggi. Penelitian ini bertujuan untuk mengidentifikasi potensi penyebaran ISPA di wilayah tertentu dengan menggunakan metode K-means clustering, sebuah teknik analisis data yang kuat dan efektif untuk mengelompokkan data berdasarkan kedekatan jarak. Metode K-means clustering digunakan untuk menganalisis data kejadian ISPA yang dikumpulkan dari berbagai sumber, termasuk data demografis, lingkungan, dan kesehatan masyarakat. Data ini kemudian diproses dan dianalisis untuk mengidentifikasi klaster-klaster atau kelompok wilayah dengan tingkat insiden ISPA yang tinggi. Dalam penelitian ini, setiap titik data mewakili insiden ISPA di lokasi tertentu, yang kemudian dikelompokkan menjadi beberapa klaster berdasarkan pola penyebaran geografisnya. Berdasarkan metode K-Means Clustering data sebaran ISPA di wilayah gunung putri terdapat 3 klaster yaitu 20% aman, 50% sedang dan, 30% bahaya wilayah dengan tingkat bahaya ditandai dengan warna merah, yang menunjukkan area dengan risiko ISPA paling tinggi. Wilayah ini meliputi bagian selatan Kecamatan Gunung Putri, termasuk Tlanjung Udik dan sekitarnya. Sebaliknya, wilayah yang lebih aman dari penyebaran ISPA ditandai dengan warna biru dan tersebar di beberapa area, terutama di wilayah tengah hingga utara seperti Nagrak. Area dengan warna merah dan coklat perlu menjadi prioritas dalam penanganan kesehatan, baik dalam hal pengendalian polusi maupun penyediaan fasilitas kesehatan.
MODEL ANALISIS SPASIAL POTENSI LONGSOR MENGGUNAKAN METODE RELATIVE DIFFERENCE NDVI (rdNDVI) MELALUI PLATFORM GOOGLE EARTH ENGINE: STUDI KASUS: KECAMATAN CIAWI Rahmatullah, Andhika; Yanuarsyah, Iksal; Hermawan, Erwin
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 9 No. 4 (2025): JATI Vol. 9 No. 4
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v9i4.14005

Abstract

Tanah longsor adalah bencana alam yang kerap terjadi di wilayah dengan lereng curam dan curah hujan tinggi, termasuk Kecamatan Ciawi, Kabupaten Bogor, sehingga memerlukan peta potensi longsor yang akurat sebagai dasar mitigasi. Permasalahan yang diangkat dalam penelitian ini meliputi: keterbatasan informasi spasial untuk mengidentifikasi area rawan longsor di Kecamatan Ciawi, akurasi deteksi potensi longsor berbasis citra satelit, dan kebutuhan visualisasi hasil dalam format WebGIS. Penelitian ini bertujuan untuk mengidentifikasi area berpotensi longsor menggunakan metode Relative Difference NDVI (rdNDVI), mengukur akurasi klasifikasi potensi longsor, dan mengembangkan sistem informasi potensi longsor berbasis WebGIS. Metode yang digunakan mencakup pengolahan citra Sentinel‑2A pra‑kejadian (2020–2021) dan pasca‑kejadian (2023–2024) pada platform Google Earth Engine, perhitungan rdNDVI dengan normalisasi akar kuadrat dan threshold lereng > 10 %, validasi melalui survei lapangan, serta desain UML, pembangunan aplikasi dengan TypeScript di Visual Studio Code, pengujian black‑box, dan deployment di Vercel. Hasil menunjukkan bahwa dengan threshold kemiringan lereng > 10 %, koefisien Cohen’s kappa mencapai 0,92 (sangat kuat), serta dihasilkan peta WebGIS yang memetakan area seluas 247 ha berpotensi longsor, sehingga sistem ini siap mendukung pemerintah dan masyarakat dalam mitigasi bencana.
DETEKSI POHON PINUS PADA CITRA UDARA MENGGUNAKAN METODE LOCAL MAXIMA Risza Purnomo, Muhammad; Yanuarsyah, Iksal; Agustian Hudjimartsu, Sahid
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 9 No. 3 (2025): JATI Vol. 9 No. 3
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v9i3.14241

Abstract

Hutan pinus merupakan salah satu hutan produksi yang dikelola oleh Perum Perhutani. Sukabumi merupakan salah satu kawasan hutan pinus di Jawa Barat yang berada di bawah lingkup Perum Perhutani. Berdasarkan kesesuaian kawasan hutan Kesatuan Pemangkuan Hutan (KPH) yang bersumber dari Perhutani, wilayah Sukabumi memiliki luas hutan pinus sebesar 45.946,55 Ha. Untuk meningkatkan produktivitas hutan pinus perlu dilakukan penajaman sumber daya, salah satunya dengan melakukan perhitungan pohon pinus. Perhitungan pohon pinus akan membutuhkan waktu yang lama jika perhitungan jumlah pohon pinus dilakukan secara konvensional. Oleh karena itu, diperlukan suatu solusi untuk mempermudah dan mempersingkat proses perhitungan pohon pinus. Penelitian ini bertujuan untuk mengetahui hasil analisis otomatisasi perhitungan jumlah pohon dari citra udara dengan metode local maxima dengan menggunakan 2 parameter, yaitu tinggi dan ukuran jendela. Sampel yang dideteksi adalah citra udara pohon pinus dengan menggunakan teknologi penginderaan jauh yaitu drone. Hasil penelitian menunjukkan bahwa dengan menggunakan metode local maxima diperoleh nilai rata-rata comission error sebesar 0.07, nilai rata-rata omission error sebesar 0.14 dan akurasi secara keseluruhan sebesar 0.81
ANALISIS PERUBAHAN PENGGUNAAN LAHAN PERTANIAN PRESISI DENGAN METODE OBIA (Studi Kasus Di Kecamatan Dramaga, Kabupaten Bogor) Yanuarsyah, Iksal
Krea-TIF: Jurnal Teknik Informatika Vol 3 No 1 (2015)
Publisher : Fakultas Teknik dan Sains, Universitas Ibn Khaldun Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1184.97 KB) | DOI: 10.32832/kreatif.v3i1.97

Abstract

The current development of Bogor Regencyespecially in Dramaga Sub-district is very rapidly. Landusechange activities was occurred by converting forest or vegetationarea, farm field, bareland, particularly in agricultural landconverted into settlements, office cluster and industrial area.Beside of many methods due to analyze landuse change, remotesensing is one approach to do so more powerful. Remote sensingis not only relying on imagery with respected to the accuracy andquality of data, but also followed by extraction technique withwhich is an Object-Based Image Analysis (OBIA). OBIA is oneprecisely technique to extract information from imagery by usingmultiresolution segmentation based on certain parameters (suchas cale parameter, color, shape factor, compact, dan smooth, etc).The imagery extraction result by using OBIA provides objectbasedclassification parameters thus to calculate precisely thechange of agricultural land (such as farm fields and paddy field)are converted into developed land.
Usability Testing Design to Increase User Experience of a Mobile Landslide Application yanuarsyah, iksal; Ahmad, Syarbaini; Khalid, Nurkaliza
Krea-TIF: Jurnal Teknik Informatika Vol 11 No 2 (2023)
Publisher : Fakultas Teknik dan Sains, Universitas Ibn Khaldun Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32832/krea-tif.v11i2.15160

Abstract

The necessity of usability testing on mobile applications built for landslide disaster management is discussed in this article. The design of user usability tests is critical to ensuring that the program is effective and efficient in catastrophic conditions, and the application's success greatly depends on its usability level. This research seeks to address user needs by designing a disaster mobile application. The goal is to address comfort issues when using disaster applications and provide the necessary solutions to improve their design and functionality by establishing user usability testing. In addition to identifying and solving usability problems that may occur when using disaster mobile applications, this research intends to establish a usability testing methodology related to landslide mitigation. The method of this study starts with research design, research procedures, data collecting, and analysis within several questions that relate to respondents who live in landslide-prone areas. The aspect of the usability test was assessed, such as connectivity, awareness, familiarity, easiness, usability, functionality, accessibility, error handling, and satisfaction. Using user usability test design in disaster mobile application development can boost the app's adoption and efficacy. Users who can easily access and use the application will have better access to emergency information and support. This study concludes that designing user usability tests is a viable method for improving the usability of disaster mobile applications. The findings revealed that user performance differed by group, with rescue workers being more efficient
Artificial Intelligence Application Usage Training: ChatGPT, Gamma, and Bing Image Creator In SMK Taman Siswa Bogor Students Primasari, Dewi; Kamilah, Nurul; Hermawan, Erwin; Riana, Freza; Laxmi, Gibtha Fitri; Yanuarsyah, Iksal; Hadjimartsu, Sahid Agustian; Eosina, Puspa
Jurnal Pengabdian Masyarakat Inovatif Vol. 3 No. 1 (2025): JPMI (Jurnal Pengabdian Masyarakat Inovatif)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Pakuan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33751/jpmi.v3i1.157

Abstract

The development of artificial intelligence technology has opened up new opportunities in the world of education, especially for vocational high school students who need digital skills to compete in the era of the industrial revolution 4.0. However, the implementation of this technology still faces challenges such as low digital literacy and limited infrastructure. This study aims to provide training on artificial intelligence applications (ChatGPT, Gamma, and Bing Image Creator) in improving the digital competence of SMK Taman Siswa Bogor students. The training method uses a participatory approach with three main stages: preparation (needs analysis, material preparation), implementation (theoretical training, direct practice, and case studies), and evaluation (pre-test, post-test, and interview). Participants consisted of 18 students and 2 teachers. Data analysis was carried out quantitatively (statistical tests). The results showed a significant increase in understanding the concept of artificial intelligence (from 32.4% to 78.6%) and mastery of applications (82% for ChatGPT, 79% Gamma, 71% Bing Image Creator). In addition to technical aspects, 88% of participants reported increased motivation to learn and 41% showed interest in technology-based careers. Key challenges included limited infrastructure (23% network issues) and varying participant abilities, which were successfully addressed through differentiated learning approaches and the use of personal devices.
Artificial Intelligence Application Usage Training: ChatGPT, Gamma, and Bing Image Creator In SMK Taman Siswa Bogor Students Primasari, Dewi; Kamilah, Nurul; Hermawan, Erwin; Riana, Freza; Laxmi, Gibtha Fitri; Yanuarsyah, Iksal; Hadjimartsu, Sahid Agustian; Eosina, Puspa
Jurnal Pengabdian Masyarakat Inovatif Vol. 3 No. 1 (2025): JPMI (Jurnal Pengabdian Masyarakat Inovatif)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Pakuan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33751/jpmi.v3i1.157

Abstract

The development of artificial intelligence technology has opened up new opportunities in the world of education, especially for vocational high school students who need digital skills to compete in the era of the industrial revolution 4.0. However, the implementation of this technology still faces challenges such as low digital literacy and limited infrastructure. This study aims to provide training on artificial intelligence applications (ChatGPT, Gamma, and Bing Image Creator) in improving the digital competence of SMK Taman Siswa Bogor students. The training method uses a participatory approach with three main stages: preparation (needs analysis, material preparation), implementation (theoretical training, direct practice, and case studies), and evaluation (pre-test, post-test, and interview). Participants consisted of 18 students and 2 teachers. Data analysis was carried out quantitatively (statistical tests). The results showed a significant increase in understanding the concept of artificial intelligence (from 32.4% to 78.6%) and mastery of applications (82% for ChatGPT, 79% Gamma, 71% Bing Image Creator). In addition to technical aspects, 88% of participants reported increased motivation to learn and 41% showed interest in technology-based careers. Key challenges included limited infrastructure (23% network issues) and varying participant abilities, which were successfully addressed through differentiated learning approaches and the use of personal devices.
Environmental Carrying Capacity as a Solution to Overlapping Forest Area Permits in Bulungan District, North Kalimantan Hartono, Tjahjo Tri; Yanuarsyah, Iksal; Setiawan, Yudi; Sakti, Fikri; Stephanie, Endah Nadiya
Jurnal Rekayasa Lingkungan dan Biosistem Vol. 1 No. 1 (2023)
Publisher : Universitas Ibn Khaldun Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32832/relibi.v1i1.418

Abstract

Research on the carrying capacity of the environment for mining activities, as indicated by the dynamics of stored carbon stocks will be carried out in Bulungan Regency, North Kalimantan in early 2022. Data was collected both through literature studies and surveys calculating tree diameter at breast height in the field as a basis calculation of stored carbon stock. Land cover spatial data analysis is used as a reference for calculating stored carbon stocks at the study site. The results of a comparison of stored carbon stocks between forest and land clearing and reclamation based on planned mining activities show that the area that can be utilized is 1,578.3 Ha. There are efforts to restore carrying capacity and carrying capacity based on mining activities with broad impacts that can be used is 1,947.84 Ha. The usable area can be increased 1.2 times from the recommended area (2,337,415 Ha) to accommodate the required land as an overburden area. This addition is made possible through the application of various appropriate technologies. The carrying capacity of the environment in this study, although only limited to the dynamics of stored carbon stocks, shows that the results can be used as a solution for overlapping permits in forest areas in accordance with the laws and regulations in effect since the Ministry of Environment and Forestry has so far provided a maximum area of 10 percent of the area areas affected by overlapping cases.
DIJITALISASI E-COMMERCE WARUNG SAYUR IBU ECIH BERBASIS ANDROID Yanuarsyah, Iksal; Purnomo, Muhammad Risza; Kamilah, Nurul
SINKRON: Jurnal Pengabdian Masyarakat UIKA Jaya Vol. 2 No. 1 (2024): SEMUA ARTIKEL TERBIT SECARA ONLINE
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat UIKA Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32832/jpmuj.v2i1.1947

Abstract

Warung Sayur Ibu Ecih, situated in Kp. Kambing RT01/06, Karang Asem Barat, Citeureup, Bogor, is among the food stalls offering a diverse range of vegetables, meats, culinary spices, and more. Customer traffic at the Warung Sayur Ibu Ecih has dwindled due to growing vegetable stalls near Kp. Kambing and the impact of the government-imposed Community Activity Restrictions, which encourage residents to avoid congregating outside their homes. Therefore, a solution is imperative to rekindle buyer interest in the Warung Ibu Ecih and to devise strategies for mitigating shopping crowds. Given this context, the concept of developing an Android-based e-commerce application prototype for the Warung Sayur Ibu Ecih stall has surfaced to lure back customers and circumvent crowding while still adhering to the regulations associated with the government's Community Activity Restrictions. Envisioned as a remedy to attract patrons, this prototype holds the potential to enable convenient vegetable shopping that arises from crowded shopping environments.
Landslide Potential Detection Model Using rdNDVI and the GEE Platform in Leuwiliang District, Bogor Iqbal, Reyhan Hikmatul; Yanuarsyah, Iksal; Hermawan, Erwin
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 19 No. 2 (2025)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/inderaja.v19i2.8801

Abstract

Landslide is among the most frequent natural disasters in Indonesia, especially in regions characterized by steep slopes and high rainfall. This study analyzes the potential for landslides in Leuwiliang District, Bogor Regency, using the Relative Difference Normalized Difference Vegetation Index (rdNDVI) and the Google Earth Engine (GEE) platform. Sentinel-2A imagery with a 10-meter spatial resolution was used to calculate rdNDVI values from pre- and post-event periods (2020–2023). Slope data derived from Digital Elevation Models (DEM) were integrated to identify areas exceeding a 10% slope threshold, categorized as high-risk zones. The rdNDVI analysis revealed that Karehkel Village had the largest landslide-prone area (40.06 ha), while Leuwiliang Village had the smallest (20.88 ha). Validation using field survey data in 2025 showed an accuracy of 78% for a slope threshold of 10%. The resulting WebGIS system provides interactive visualization for disaster risk mapping and supports decision-making for local mitigation planning. The combination of rdNDVI and GEE demonstrates the potential of cloud-based remote sensing for rapid and scalable landslide detection. Future work should include additional parameters such as rainfall intensity and soil moisture to enhance prediction accuracy.
Co-Authors Ade Yansyah Andry Liu, Wahyu Dewi Primasari Disti Ayu Sadewa Erwin Hermawan Fety Fatimah Freza Riana Gibtha Fitri Laxmi Hadjimartsu, Sahid Agustian Iqbal, Reyhan Hikmatul Jie, Lie Jixiong, Cai Khalid, Nurkaliza Lulu Lutfi Latifah Minati Minati Nazar, Muarief Ahlun Nitin, Mahon Nurul Kamilah Purnomo, Muhammad Risza Puspa Eosina R, Muh Rafli Rahmatullah, Andhika Risza Purnomo, Muhammad Safaruddin Hidayat Al Ikhsan Sahid Agustian Hudjimartsu Sakti, Fikri Stephanie, Endah Nadiya Suwarno, Yatin Syawaludin Alisyahbana Harahap Tjahjo Tri Hartono Tuharea, Jumiati Yudi Setiawan