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All Journal Jurnal Simantec Jurnal Riset Informatika Seminar Nasional Teknologi Informasi Komunikasi dan Administrasi [SEMINASTIKA] GANDRUNG: Jurnal Pengabdian Kepada Masyarakat Jurnal Mahasiswa Sistem Informasi (JMSI) Jurnal Aplikasi Teknologi Informasi dan Manajemen (JATIM) Jurnal Penelitian Rumpun Ilmu Teknik JUSTIFY : Jurnal Sistem Informasi Ibrahimy Jurnal Pengabdian Kolaborasi dan Inovasi IPTEKS Journal Of Computer Science And Technology JURNAL ILMIAH SAINS TEKNOLOGI DAN INFORMASI "JAMASTIKA" Jurnal Mahasiswa Teknik Informatika Jurnal Ilmiah Multidisiplin Nusantara Gudang Jurnal Multidisiplin Ilmu Jurnal Ilmiah Research Student Jurnal Sains Student Research JURNAL ILMIAH PENELITIAN MAHASISWA Jurnal Imiah Pengabdian Pada Masyarakat (JIPM) Jurnal Ilmiah Multidisiplin Ilmu Jurnal Riset Teknik Komputer Jurnal Pengabdian Masyarakat Jurnal Riset Sistem Informasi Jurnal Padamu Negeri Jurnal Pendidikan Sains dan Teknologi Terapan Jurnal Sistem Informasi Karya Anak Bangsa Jurnal Teras Pengabdian Masyarakat Jurnal Pengabdian Indonesia Abhakte
Zaehol Fatah
Unknown Affiliation
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Medicine & Pharmacology Physics Public Health Social Sciences Other

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Analisis Produksi Cabai Rawit Indonesia Menggunakan Algoritma K-Means Clustering Syaiful Hasan Abdullah; Zaehol Fatah
JURNAL ILMIAH SAINS TEKNOLOGI DAN INFORMASI Vol. 3 No. 1 (2025): Januari
Publisher : CV. ALIM'SPUBLISHING

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59024/jiti.v3i1.1024

Abstract

Indonesia, dengan tanahnya yang subur, memiliki potensi besar dalam pertanian, terutama berkat letak geografisnya di wilayah tropis yang ditandai dengan curah hujan tinggi. Kondisi ini mendukung pertumbuhan berbagai jenis tanaman secara optimal, menjadikan Indonesia dikenal sebagai negara agraris. Sebagian besar penduduknya menggantungkan hidup pada sektor pertanian. Salah satu komoditas penting adalah cabai rawit, yang memiliki rasa pedas khas dan sering digunakan sebagai bahan masakan. Selain memberikan rasa pedas yang kuat, cabai rawit juga mempercantik tampilan hidangan dan mampu meningkatkan nafsu makan. Karakteristik ini menjadikan cabai rawit sebagai elemen penting dalam kuliner Indonesia. Cabai rawit adalah salah satu komoditas utama di Indonesia. Oleh karena itu, penting untuk melakukan kajian mendalam terkait tingkat produksinya, termasuk upaya mengoptimalkan hasil produksi melalui analisis berbagai faktor yang memengaruhinya. Metode data mining memungkinkan penggalian pola-pola tersembunyi yang menarik dalam kumpulan data. Selain itu, metode ini dapat digunakan untuk mengurangi kesalahan pengguna dalam proses pengolahan data. Salah satu pendekatan data mining yang efektif untuk memetakan atau mengelompokkan data serupa adalah klastering. Klastering memiliki kelebihan unik dibandingkan metode lain karena mampu mengklasifikasikan data tanpa memerlukan pengetahuan awal. Teknik ini membagi data menjadi kelompok-kelompok berdasarkan kemiripan karakteristik. Ada berbagai algoritma yang digunakan dalam klastering, dan salah satu yang paling populer adalah algoritma K-Means
PREDIKSI PRODUK PENJUALAN DI SUPERMARKET DENGAN METODE ALGORITMA K-NEAREST NEIGHBORS (KNN) Ahmad Muflih Wafir; Zaehol Fatah
JURNAL ILMIAH SAINS TEKNOLOGI DAN INFORMASI Vol. 3 No. 1 (2025): Januari
Publisher : CV. ALIM'SPUBLISHING

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59024/jiti.v3i1.1056

Abstract

In today's era, there are already many companies that have been established, from urban to rural areas, various companies have been established, especially companies that provide daily necessities such as supermarkets. And each company competes with each other in selling its products with the expected results. In this study, researchers use data to support this study. Because sales of goods or product stock can be calculated in sales results, the higher the sales, the higher the risk that will be faced. This study aims to apply data mining in analyzing sales results that occur in supermarkets. And to find out its impact on sales. This researcher uses the KNN method, by looking for test results with this method which will be implemented using the Rapid Miner application which will later produce the results of its analysis.
IMPLEMENTASI METODE K-NEAREST NEIGHBOR UNTUK KLASIFIKASI PENYAKIT PARU-PARU PADA ANAK Risma Alfiatul Karima; Zaehol Fatah
Jurnal Ilmiah Multidisiplin Ilmu Vol. 1 No. 6 (2024): Desember : Jurnal Ilmiah Multidisiplin Ilmu (JIMI)
Publisher : CV. Denasya Smart Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69714/yx4smf68

Abstract

Lung disease, especially in children, is a significant health problem and can have serious consequences if not diagnosed and treated quickly. Implementation of the K-Nearest Neighbor method as a classification of lung disease in children. This algorithm allows medical data analysis to identify patterns related to lung disease symptoms to achieve a high level of accuracy in predicting lung disease risk. The results of the test show that K-Nearest Neighbor can produce an effective and accurate prediction model, with CAP data accuracy of 83.33%, and provides useful insights for early diagnosis and decision-making in children's health care.
PENERAPAN METODE NEURAL NETWORK UNTUK PREDIKSI HARGA CABAI PASAR JOHAN DI KABUPATEN SEMARANG Sulistia Wardani; Zaehol Fatah
Jurnal Ilmiah Multidisiplin Ilmu Vol. 1 No. 6 (2024): Desember : Jurnal Ilmiah Multidisiplin Ilmu (JIMI)
Publisher : CV. Denasya Smart Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69714/hnqc1f46

Abstract

Chili consumption in Indonesia continues to increase along with population growth, however chili prices often experience fluctuations which are influenced by various factors, such as rainfall, market demand and production costs. These unpredictable price fluctuations can make it difficult for farmers and market players to plan chili production and distribution. This research aims to predict chili prices using the neural network method, by utilizing historical data on chili prices and other supporting factors such as weather conditions, market demand and production costs. The neural network model is expected to be able to produce chili price predictions that are more accurate and reliable compared to conventional methods. With accurate price predictions, it is hoped that it can provide a stronger basis for farmers and market players in making decisions regarding the production, distribution and marketing strategies of chilies, as well as creating price stability in the market.
KLASIFIKASI SPESIES BUNGA IRIS MENGGUNAKAN ALGORITMA KLASIFIKASI KNN DI RAPIDMINER Zainur Rahman; Zaehol Fatah; Jarot Dwi Prasetyo
Jurnal Ilmiah Multidisiplin Ilmu Vol. 1 No. 6 (2024): Desember : Jurnal Ilmiah Multidisiplin Ilmu (JIMI)
Publisher : CV. Denasya Smart Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69714/0syd5n74

Abstract

The classification of Iris flower species based on morphological features is a crucial challenge in biological research and data science. This study aims to address this issue using the K-Nearest Neighbor (KNN) algorithm, implemented via RapidMiner, to automate and enhance the accuracy of the classification process. Fisher's Iris Dataset, consisting of 150 samples across three species (Iris setosa, Iris versicolor, and Iris virginica), was utilized. The research followed the Knowledge Discovery in Database (KDD) methodology, involving data preprocessing, model training, and evaluation. The results showed that the KNN algorithm achieved 100% accuracy in classifying the dataset, validating the effectiveness of both the algorithm and the RapidMiner platform for data mining. These findings underline the potential of KNN as a reliable tool for similar classification tasks.
SISTEM INFORMASI INVENTARIS BARANG BERBASIS WEB PADA DINAS KOMUNIKASI DAN INFORMASI BONDOWOSO Lutfiana , Nurisma; Zaehol Fatah
Jurnal Ilmiah Multidisiplin Ilmu Vol. 1 No. 6 (2024): Desember : Jurnal Ilmiah Multidisiplin Ilmu (JIMI)
Publisher : CV. Denasya Smart Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69714/p074a746

Abstract

The Web-Based Inventory Information System at the Bondowoso Communication and Information Service aims to improve efficiency and accuracy in asset management. In the context of government, effective inventory management is essential to ensure transparency and accountability in resource use. This study began with a needs analysis through interviews and surveys of users, which was then followed by system design using flowcharts and Data Flow Diagrams (DFD). The developed system integrates the process of inputting, maintaining, and reporting inventory, and provides a user-friendly interface. The software development methodology used is waterfall, which allows adjustments based on user feedback during the testing phase. The implementation results show that the system is able to reduce data errors, accelerate the decision-making process, and improve collaboration between departments within the service. Thus, this Web-Based Inventory Information System not only meets administrative needs but also contributes to better asset management at the Bondowoso Communication and Information Service. This study is expected to be a reference for other government agencies in implementing similar systems to improve the efficiency and transparency of inventory management.
IMPLEMENTASI RAPIDMINER PADA KLASTERISASI GEMPA BUMI DI INDONESIA BERDASARKAN KEDALAMAN MENGGUNAKAN K-MEANS Maruf Ubaidillah; Zaehol Fatah
Jurnal Ilmiah Multidisiplin Ilmu Vol. 1 No. 6 (2024): Desember : Jurnal Ilmiah Multidisiplin Ilmu (JIMI)
Publisher : CV. Denasya Smart Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69714/w0m9zv32

Abstract

Indonesia is a meeting place for four major tectonic plates, namely the Carolina Plate, the Philippine Sea Plate, the Indo-Australian Plate, and the Eurasian Plate. Every year thousands of earthquakes strike, causing material losses, infrastructure damage, and even loss of life. Therefore, understanding the characteristics of earthquakes in Indonesia is a crucial step to mitigate disaster risks and improve community preparedness. The dataset used comes from the Kaggle.com website, the dataset is taken from the Earthquake Repository managed by BMKG. The K-Means algorithm is used as a clustering process method in this study. Clustering using K-Means aims to identify the dominant types of earthquakes that occur in regions of Indonesia. The application of this method to earthquakes that occurred in Indonesia based on the identified depth in cluster_0 shows the least earthquakes with the deepest earthquake type. Cluster_1 shows a shallow earthquake type. While cluster_2 is the earthquake with the most occurrences and shows an earthquake with a moderate depth.
PENERAPAN K-MEANS CLUSTERING UNTUK PENGELOMPOKAN WILAYAH BERDASARKAN TINGKAT KEMISKINAN DI INDONESIA Sagita Maesarah; Zaehol Fatah
Jurnal Ilmiah Multidisiplin Ilmu Vol. 1 No. 6 (2024): Desember : Jurnal Ilmiah Multidisiplin Ilmu (JIMI)
Publisher : CV. Denasya Smart Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69714/3d5mkb02

Abstract

Poverty is one of the problems that hinder national and regional growth. Poverty is the inability to meet the minimum standards of basic needs including food and non-food needs. Poor people are people who are below a limit or called the poverty line. The resources used are sourced from www.kaggle.com. In the process of data processing with the k-means Clustering method. The K-means Clustering method is a method of grouping existing data into several groups where the data in one group has the same characteristics as each other and has different characteristics from the data in the group. The results of the study show that regions in Indonesia can be grouped into several clusters with different poverty level characteristics. These clusters reveal specific patterns, such as the concentration of areas with high poverty in certain areas and the factors that contribute to these conditions. With this approach, the government and policy makers can identify priority areas and design more effective programs to reduce poverty levels..
IMPLEMENTASI KELULUSAN MAHASISWA BERDASARKAN DATA NILAI AKADEMIK MENGGUNAKAN ALGORITMA DECISION TREE Wildatul Hasanah; Zaehol Fatah
Jurnal Ilmiah Multidisiplin Ilmu Vol. 1 No. 6 (2024): Desember : Jurnal Ilmiah Multidisiplin Ilmu (JIMI)
Publisher : CV. Denasya Smart Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69714/9hx6fa37

Abstract

Predicting student graduation is one of the important things in managing education in higher education. By using academic score data such as course grades and Grade Point Average (GPA),Can predict student graduation more efficiently. This article implements the Decision Tree algorithm to predict student graduation based on their academic score data. The Decision Tree algorithm has proven to be effective in making predictions based on existing attributes. The research results show that this model has good accuracy in predicting student graduation status.
PENERAPAN DATA MINING DENGAN ALGORITMA NAÏVE BAYES UNTUK ANALISIS KEBUTUHAN STOK OBAT DI KLINIK IDAMAN AS'ADIYAH SUKOREJO Muchammad Atfal Nur Afil; Zaehol Fatah
Jurnal Ilmiah Multidisiplin Ilmu Vol. 1 No. 5 (2024): Oktober : Jurnal Ilmiah Multidisiplin Ilmu (JIMI)
Publisher : CV. Denasya Smart Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69714/fsgkh354

Abstract

Medicine stocks that are not well managed can cause shortages or excess stocks which have an impact on health services in clinics. This research aims to apply the Naïve Bayes algorithm to analyze drug stock needs at the Idaman As'adiyah Sukorejo Clinic. By using historical data on drug sales and monthly demand for one year, the Naïve Bayes algorithm is used to predict the type of drug that will be needed in the following month. The research results show that this algorithm is able to predict drug stock needs with an accuracy of up to 85%, which can help clinic managers plan the purchase and distribution of drugs more efficiently.
Co-Authors Abdul Hadi Abdur Rohman Nurut Toyyibin Abrori, Syariful Ach. Zubairi Achmad Fathoni Verdian Afcharina Diniyil Muhlisin Afrizal Rizqy Pratama Ahmad Homaidi Ahmad Muflih Wafir Ahmad Syahril Lail Ahmad Wahyu Fernando Ahmed Arifi Hilman Rahman Ahsin Ilallah Ainul Fadil Aisyah Putri Sabrina Akhlis Munazilin Alfan Jamil Alfi Fahira Salsabila Alfi Khairunnisa Alfina Damayanti Alfiyah Aurella Alifan Ibrohim Alifia Rosa Firdausiah Alviatur Rizqiyah Amelia Ismatul Hawa Ammar Farisi Anang Maulana Zulfa Angeli Dwiyanti Nur’azizah Anisa Anisa Anwar Anas Anzori Arif Ferdiansyah audiatul jinan Auliya Apriliana Aviatus Sholiha Bagas Wira Yuda Basmalia Bina Cahya Pamungkas, ihya16092002 Citra Nursihah Danil Bahroni Della Natasya Diana Uzlifatul Khairu Ummah Dila Puspita Dewi Diva Maulana Dwi Alya Putri Arifany Dzakwan Rohmatul Hanif Elvi Nazulia Rahma Elvina Eldiavani Epariani Erinia Dzikrotul Kharimah Fahrillah Fahrillah Faqih Nur Rahman Fatimah Isa Auliya Fatma Nur Afifah Faza Qori Aina Fikri Rostina Firda Wati Husaini Kulsum Fitri Elvi Karisma Fitria Ayu Ulandari Hafidz, M. Fajar Hasna Ruhmaniatin Herlinatus Safira Muasolli Hermanto , Hijrah Hijriah Holida Izzatilla Holil Asy’ari Huday, Ahmad Ifan Farimulyadi Ifan Prasetyariansyah Ifqy Ahmad Fahrizal iin, Nur Inayah Ika Indah Khasanah ila, Sufatun Aila Ilham Rafi Jawara Ilham Rafiqi Imam Nawawi Imelda Valentina Octavia Indah Novita Sari Iqbal Ainul Yaqin Irfansyah, Khairullah Irham, Muhammad Nazril Irma Yunita Islamiyatul Addewiyah Ismawati Ismawati Ismawati Ivana Dwikartika Sari j-sika Jarot Dwi Jarot Dwi Prasetyo Jefri Jefri Jesika Maya Nur Islami Kayyisah Fakhirah Kevin Riyas Robbani Khairul Anam Khozaimah Dian Islami Komarul Imam Laila Devi Sari LAILATUL FITRIYAH Lailatul Risqia Lailatus Syarifah Lailatussyarifah Lina Sosiana Lisa Novia Ramdani Lubebetun Nafisa Lukman Fakih Lukman Fakih Lidimilah Luluk Nuril Mukarromah Lutfiana , Nurisma Lutfiyatul F Anas Lu’luul Maulidya Nova M. Andrik Muqorrobin P M. Andrik Muqorrobin Pratama M. Fazlur Rahman Assauqi Maharani Rahmatul Hanani Mahmudi Mahmudi Mamluatur Rizkiyatun Nafiah Manda Nuria Suhailatin Najwa Maruf Ubaidillah Maryana Mashuri, Ahmad Meliana Khamisah Mifta Wilda Al -Aluf Miftahul Arif Aldi Milka Afifah Rahmatillah Mochammad Rofi Mochammad Syukron Ramadani Moh. Agus Efendi Moh. Baha’Uddin Moh. Syahrul Iskandar Moh. Zaini Romly Mohamad Faezal Fauzan Nanda Mohammad Alfian Husni Mubarok Mohammad Farhan Fatah Muchammad Atfal Nur Afil Muflihatul Hasanah Muftiyah Zakiyah Muhamad Auliya Muhamad Ilhan mansiz Muhammad Al Madany Muhammad Faidhurrahman Wahid Muhammad Hanif Zaky Ubaidillah Muhammad Hasan Muhammad Robitul Umam Muhammad Trisnawadi Ismardani Mutmainnah Ilmiatul Faidah Muyessiroh Muzayyana, Muzayyana Mu’tashim Billah Rahman Nabila Khansa Nabila Sofia Az-zahra Nadia Selvi Ramadhani Nafisatul Insiyah Naqibuzzahidin Naufal Arif Maulana Nur Aida NUR AINI Nur Azise Nur Dina Kamelia Nur Laili Mukarromah Nur Rizatul Mufidah Nur Sahila Chapsah Nur Saputra, Zuhrian Nurin Naimah Nurisma Lutfiana Prastika Buya Hakim Putri Anindya Damayanti Qittratul Ameliatus Qurratul Aini Rafi Jawara, Ilham Raihan Asriel Afandi Ratu Maulidia Anggraini Regina Izza Aofkarina Riatul Jannah Rifki Dwi Saputra Risma Alfiatul Karima Risqiatus Syarifah Risqiyati Amilia Ningsih Rita Irawati rizka, Rizka Aprilia Ningsih Rizki Hidayaturrochman Rosita Natania Maulani Rudi Ananta Al Hidayah Ruqoyyatul Widad Ruwaida Khollatil Widat Safitri Nurul Qomariyah Sagita Maesarah Septi Camelia Ulfa Sidra Al Zahro Sinta Bella Sinta Dewi Anggraeni Siti Aysatin Rodia Siti Imroatul Jannah Siti Kholifah Siti Maghfiroh Siti Nabilatul Hoiroh Siti Nur Azizah Siti Romlah Siti Sulaiha Sitti Ainur Rofiqotul Anisa Sofi Naila Nuriyazih Sofyan, Moh Sofyan Alfandi SU'AYDI, AHMAD SU'AYDI Suci Mulianingsih Sukiman Eki Putra Sulistia Wardani Supri Arrohman Syaiful Hasan Abdullah Syirva Nada Fidya Tadzkirotul Latifah Taufik Saleh Ubeitul Maltuf Ulvi Munawaroh Ummi Fadlilatuz Zakiyah Ummil Mahfudoh Ummul Khoirun Fitriyah Uny Khafifah USWATUN HASANAH Wafi Riga Ramadhani Wafi, Wafi Wardatul Gufronia Wildatul Hasanah Winda Yanti Umami Wiwik Handayani Wulan Shelfiana Kamil Yeni nur hasanah Yua Isman Islam Yulina Sari Zahrafil Jannah Zainur Rahman Zakiyatus Solehah