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All Journal Jurnal Simantec 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 "JAMASTIKA" Jurnal Mahasiswa Teknik Informatika Gudang Jurnal Multidisiplin Ilmu Jurnal Ilmiah Research Student Jurnal Sains Student Research Jurnal Riset Sistem dan Teknologi Informasi 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
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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 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 PENGELOMPOKAN DATA NILAI SISWA UNTUKMENENTUKAN SISWA BERPRESTASI MENGGUNAKAN METODE CLUSTERING K- MEANS Mochammad Syukron Ramadani; Zaehol Fatah
Jurnal Riset Sistem Informasi Vol. 1 No. 4 (2024): Oktober : Jurnal Riset Sistem Informasi
Publisher : CV. Denasya Smart Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69714/hq2bsy84

Abstract

Identifying high-achieving students is a critical step in evaluating learning outcomes to enhance the quality of education. This study aims to analyze the clustering of student grade data using the K-Means Clustering method to identify groups of high-achieving students. The K-Means method is utilized due to its effectiveness in grouping data based on value similarity. The data used in this study consist of students' academic scores across various subjects. The research stages include data collection, preprocessing, applying the K-Means algorithm, and validating the clustering results. The results show that the K-Means method successfully grouped students into several categories, such as high-achieving, moderate-achieving, and low-achieving students. The clustering analysis indicates that high-achieving students exhibit consistent performance across all subjects, whereas low-achieving students tend to show significant variations in their scores. This method also provides data visualization that helps schools make informed decisions to improve student performance. Thus, the implementation of the K-Means method in clustering student grade data can serve as an effective and efficient approach to support evaluation processes and data-driven decision-making.
IMPLEMENTASI DATA MINING UNTUK MENGANALISA POLA PENJUALAN MENGGUNAKAN METODE K-MEANS PADA CV. HAVAS P2S2 Alfan Jamil; Zaehol Fatah
Jurnal Riset Sistem Informasi Vol. 1 No. 4 (2024): Oktober : Jurnal Riset Sistem Informasi
Publisher : CV. Denasya Smart Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69714/rxnjxb68

Abstract

Sales are an important aspect in the continuity of company operations, including CV. Hafas P2S2 which is engaged in the distribution of bottled drinking water products. In order to increase the effectiveness of marketing strategies and stock management, it is important to analyze sales patterns that occur. This research aims to implement data mining techniques using the K-means method to analyze sales patterns at CV. Memorize P2S2. The K-means method was chosen because of its ability to find associative relationships between items that are often purchased together in transactions. The data used in this research involves sales information recorded in the company system. The results of applying the K-means algorithm show that there are certain combinations of items that are often sold together, which provides valuable insights for companies in terms of stock management and marketing strategies. It is hoped that these findings can help CV. Hafas P2S2 in improving operational efficiency and maximizing profit potential by better understanding customer demand patterns. Thus, the implementation of data mining through the K-means method makes a significant contribution to data-based decision making in the company's sales sector.
PENGELOMPOKAN DATA NILAI SISWA MADRASAH TA’HILIYAH MENGGUNAKAN METODE K-MEANS CLUSTERING Fahrillah Fahrillah; Zaehol Fatah
Jurnal Riset Sistem Informasi Vol. 2 No. 1 (2025): Januari : Jurnal Riset Sistem Informasi
Publisher : CV. Denasya Smart Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69714/0v1pkz05

Abstract

Data mining, or data mining is the process of collecting and processing data to extract important information. The stages in the data mining process are useful for finding a particular pattern from a large amount of assessment data. This goal is to find out and form student data clusters based on grades so that they become a cluster, so that the results of student clusters can be a reference in improving student grades in the next learning process. The results of the evaluation and assessment of students are carried out by teaching staff or teachers in conducting assessments during the learning process. In the learning process there are 2 assessment categories, namely UTS and UAS student grades. The results of grouping student grade data using the K-Means clustering method show that based on the results of student data clusters in one semester, cluster 0 is obtained with 7 students, cluster 1 is 3. The results of testing using rapid miner show that there are 7 students who have grades with a good average and there are 3 students with a poor average grade.
PREDIKSI NILAI INDEKS EKSPOR SUSU SEGAR DI INDONESIA MENGGUNAKAN ALGORITMA BACKPROPAGATION Holil Asy’ari; Zaehol Fatah
Jurnal Riset Sistem Informasi Vol. 2 No. 1 (2025): Januari : Jurnal Riset Sistem Informasi
Publisher : CV. Denasya Smart Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69714/46fpc085

Abstract

The results of research on the value of exports in Indonesia can be concluded that the architectural model can make predictions with 100% accuracy with a short training time. In addition, by looking at the results of testing on architecture, it can be seen that both the speed and the prediction results, it can be concluded that the value of exports in Indonesia is increasingly declining. For future research, research should use a different algorithm or the Backpropagation algorithm can be optimized with other algorithms, such as conjugate gradient and so on, that is, the research was first carried out using the backpropagation algorithm, then after knowing the results, calculations were carried out with the algorithm. other. After that, a comparison is made between the results of backpropagation with the results of other algorithms. Images or graphs of each algorithm used, or a graphic image of the comparison of the previous data with the data that has been generated using the algorithm.
ANALISIS POLA KEHADIRAN MAHASISWA MENGGUNAKANALGORITMA DECISION TREE Mu’tashim Billah Rahman; Zaehol Fatah
Jurnal Riset Sistem Informasi Vol. 2 No. 1 (2025): Januari : Jurnal Riset Sistem Informasi
Publisher : CV. Denasya Smart Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69714/6z8kc143

Abstract

Student attendance in lectures plays a crucial role in academic achievement and the quality of learning. The Decision Tree algorithm is used to analyze student attendance patterns with a dataset containing 6,607 entries from Kaggle, comprising 20 related attributes. Using RapidMiner, the analysis process includes data splitting, model building, and performance evaluation. The model achieved 49.96% accuracy, with the best performance in the "Medium" class (50.40% precision, 98.12% recall) but showed weaknesses in the "High" and "Low" classes. These results highlight the importance of data-driven approaches to designing effective strategies, such as rescheduling or improving teaching methods, to enhance student participation.
ALGORITMA K-MEANS CLUSTERING UNTUK MENENTUKAN SISWA UNGGULAN BERDASARKAN HASIL UJIAN DI SEKOLAH Ainul Fadil; Zaehol Fatah
Jurnal Riset Sistem Informasi Vol. 2 No. 1 (2025): Januari : Jurnal Riset Sistem Informasi
Publisher : CV. Denasya Smart Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69714/p26gcf27

Abstract

Determining classes for outstanding students based on exam results is a crucial step in promoting the improvement of learning quality. This study applied a data mining method using the K-Means Clustering algorithm to group students based on their exam results. The process includes collecting exam score data, preprocessing the data, and applying the K-Means algorithm to form several student groups based on their achievement levels. Through this algorithm, students are clustered into groups with similar characteristics, such as excellent, average, and those requiring more attention. The study's results indicate that the K-Means Clustering approach can provide an accurate representation of the distribution of student abilities, serving as a basis for designing more effective and equitable learning strategies. This implementation is expected to help schools identify students' potential more objectively and enhance overall educational quality.
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.
Co-Authors Abdul Hadi Abdur Rohman Nurut Toyyibin Abrori, Syariful Ach. Zubairi Achmad Fathoni Verdian Afcharina Diniyil Muhlisin Afrizal Rizqy Pratama Ahmad Homaidi Ahmad Syahril Lail 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 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 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 Pratama Maharani Rahmatul Hanani 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 Oka dewata Syaputra Prastika Buya Hakim Putri Anindya Damayanti Qittratul Ameliatus Qurratul Aini 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 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