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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
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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 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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PENERAPAN ALGORITMA K-MEANS PADA SMA PROVINSI DKI JAKARTA UNTUK MENENTUKAN SEKOLAH TERBAIK BERDASARKAN NILAI UN Muhammad Hasan; Zaehol Fatah
Jurnal Ilmiah Multidisiplin Ilmu Vol. 2 No. 1 (2025): Februari : Jurnal Ilmiah Multidisiplin Ilmu (JIMI)
Publisher : CV. Denasya Smart Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69714/bncwkr16

Abstract

Education is an important aspect in human resource development in Indonesia. One indicator to measure the quality of education is the National Examination (UN) score. However, parents or students often have difficulty choosing the best school in DKI Jakarta Province because of the many choices available. This research aims to apply the K-Means algorithm to group high school schools in DKI Jakarta Province based on National Examination scores. By using the clustering method, it is hoped that groups of schools with the best achievements can be found, making it easier to select schools based on these criteria. In this research, the data used are high school National Examination scores in DKI Jakarta obtained from the Ministry of Education and Culture. The results of this research show that the K-Means algorithm can be effectively used to group schools based on National Examination scores, thereby providing a clearer picture for the public in determining quality schools.
IMPLEMENTASI DATA MINING UNTUK MENENTUKAN POLA PENJUALAN DI RAHAYU MART MENGGUNAKAN ALGORITMA APRIORI Bina Cahya Pamungkas, ihya16092002; Zaehol Fatah
Jurnal Ilmiah Multidisiplin Ilmu Vol. 2 No. 1 (2025): Februari : Jurnal Ilmiah Multidisiplin Ilmu (JIMI)
Publisher : CV. Denasya Smart Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69714/vbsxqq63

Abstract

The Apriori algorithm is a method used to discover patterns among a set of items. By analyzing all recorded sales transactions, it helps in determining and developing more accurate and targeted promotions. Rahayu Mart faces a challenge in understanding what customers want and need, as well as how they shop. Identifying frequently purchased items by customers can assist in making appropriate business decisions and serve as a consideration for sales strategies. By applying the Apriori algorithm, consumer purchasing patterns and the influence between items can be uncovered, enabling more effective business insights.
PENINGKATAN EFISIENSI PEMANTAUAN KEHADIRAN SISWA MENGGUNAKAN CLASTERING K-MEANS PADA MADRASAH I'DADIYAH SALAFIYAH SYAFI'IYAH Mohamad Faezal Fauzan Nanda; Zaehol Fatah
Jurnal Ilmiah Multidisiplin Ilmu Vol. 2 No. 1 (2025): Februari : Jurnal Ilmiah Multidisiplin Ilmu (JIMI)
Publisher : CV. Denasya Smart Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69714/87vcvz50

Abstract

This research aims to increase efficiency in monitoring student attendance at Madrasah I'dadiyah Salafiyah Syafi'iyah by utilizing the K-Means Clustering analysis method. Monitoring student attendance is still carried out conventionally, so it often takes time and is less effective in identifying overall student attendance patterns. For this reason, in this research, student attendance data collected from the madrasa attendance system was analyzed using K-Means Clustering, a machine learning technique that can group students based on their attendance patterns. This process produces several groups which make it easier for the madrasah to identify students who frequently attend, rarely attend, or frequently do not attend. In this way, madrasas can take more appropriate steps in dealing with attendance problems, such as paying special attention to students who are often absent. The results of this research indicate that the application of K-Means Clustering can increase the efficiency of attendance monitoring and provide a stronger basis for decision making to improve the attendance system at the I'dadiyah Salafiyah Syafi'iyah madrasah.
Klasifikasi Algoritma Decision Tree Untuk Tingkat Kemiskinan Di Indonesia Mifta Wilda Al -Aluf; Zaehol Fatah
Journal of Computer Science and Technology (JOCSTEC) Vol 3 No 1 (2025): JOCSTEC - Januari
Publisher : PT. Padang Tekno Corp

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59435/jocstec.v3i1.440

Abstract

Kemiskinan merupakan salah satu masalah sosial yang terus menjadi tantangan bagi pemerintah di berbagai negara, termasuk Indonesia. Dalam upaya mengidentifikasi faktor-faktor yang memengaruhi tingkat kemiskinan, analisis data yang tepat diperlukan untuk mendukung pengambilan kebijakan yang efektif. Penelitian ini bertujuan untuk mengklasifikasikan tingkat kemiskinan di Indonesia dengan menggunakan algoritma Decision Tree, salah satu metode pembelajaran mesin yang populer. Data yang digunakan dalam penelitian ini mencakup indikator ekonomi, demografi, dan sosial yang relevan dengan kemiskinan di Indonesia. Dengan menggunakan algoritma Decision Tree, kami dapat mengidentifikasi variabel-variabel kunci yang berperan dalam klasifikasi tingkat kemiskinan serta membangun model prediksi yang dapat membantu dalam pengambilan keputusan. Hasil penelitian menunjukkan bahwa algoritma Decision Tree memiliki kinerja yang baik dalam mengklasifikasikan data kemiskinan dan memberikan wawasan mendalam tentang faktor-faktor yang memengaruhi kemiskinan di Indonesia. Temuan ini diharapkan dapat berkontribusi dalam upaya penanggulangan kemiskinan melalui pendekatan berbasis data.
Penerapan Data Mining Untuk Prediksi Diagnosis Demam Berdarah Dengan Algoritma Decision Tree C4.5 Supandi; Zaehol Fatah
Journal of Computer Science and Technology (JOCSTEC) Vol 3 No 2 (2025): JOCSTEC - Mei
Publisher : PT. Padang Tekno Corp

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59435/jocstec.v3i2.437

Abstract

Prediksi dengan model sistem pendukung keputusan merupakan cara yang tepat sasaran untuk digunakan dalam memecahkan masalah. Demam Berdarah Dengue (DBD) adalah penyakit endemik di Indonesia yang memerlukan penanganan cepat untuk mencegah komplikasi lebih lanjut. Prediksi diagnosis DBD dengan menggunakan algoritma Decision Tree C4.5 memiliki tingkat akurasi 100% dan meyakinkan. Dataset yang digunakan mencakup data medis pasien, seperti gejala klinis yaitu demam, nyeri sendi, mual, hasil laboratorium berupa trombosit, hematokrit, uji NS1, serta riwayat komorbiditas dan durasi gejala. Proses pre-processing dilakukan untuk memastikan data siap digunakan, dengan menangani data yang hilang dan menyesuaikan format data agar konsisten. Model Decision Tree C4.5 dipilih karena kemampuannya mengolah data dengan berbagai format dan hasilnya dapat dengan mudah dipahami. Model C4.5 dievaluasi menggunakan metrik akurasi, presisi, sensitivitas, dan spesifisitas. Dengan performa yang baik, model ini memiliki potensi untuk digunakan dalam sistem pendukung keputusan medis. Implementasinya di lapangan dapat membantu tenaga medis dalam mempercepat diagnosis dan memberikan penanganan yang lebih tepat waktu, yang sangat penting dalam menangani pasien DBD.
PENERAPAN DATA MINING UNTUK PENILAIAN TES HADRAH DI PESANTREN SALAFIYAH SYAFI'IYAH MENGGUNAKAN METODE RANDOM FOREST Citra Nursihah; Zaehol Fatah; Rizki Hidayaturrochman
Jurnal Riset Teknik Komputer Vol. 2 No. 1 (2025): Maret : Jurnal Riset Teknik Komputer (JURTIKOM)
Publisher : CV. Denasya Smart Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69714/jfe1c445

Abstract

The application of data mining in the evaluation of Hadrah tests at Pesantren Salafiyah Syafi'iyah is explored using the Random Forest algorithm. Hadrah, a form of Islamic artistic performance involving vocal and percussion elements, is integral to the cultural and spiritual life in Islamic boarding schools. The objective of this research is to enhance the accuracy and objectivity of performance assessments in Hadrah, particularly in the context of competition or educational evaluation at Pesantren Salafiyah Syafi'iyah. By utilizing the Random Forest method, which is a robust machine learning technique, the study aims to minimize the subjectivity and inconsistency inherent in traditional evaluation methods. The study leverages secondary data from previous Hadrah tests, applying preprocessing steps to ensure the data is suitable for analysis. The results show that Random Forest provides a high level of precision in classifying participants based on key assessment features such as tempo, consistency, and overall performance. This method contributes significantly to improving the reliability and fairness of the evaluation process, ensuring a more standardized approach to assessing artistic skills in the context of Islamic traditions. The findings suggest that data-driven approaches can play a pivotal role in preserving and promoting Islamic arts while enhancing the educational process.
PENERAPAN DATA MINING UNTUK REKOMENDASI PAKET FOTO PRIWED MENGGUNAKAN ALGORITMA APRIORI Ifan Farimulyadi; Zaehol Fatah
Jurnal Riset Teknik Komputer Vol. 2 No. 1 (2025): Maret : Jurnal Riset Teknik Komputer (JURTIKOM)
Publisher : CV. Denasya Smart Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69714/wjn1zp06

Abstract

SM Wedding Decoration is a place that provides services to take care of everything related to weddings. For example, wedding decorations, wedding organizers, and wedding planners. SM Wedding Decoration has several wedding packages that can be offered to customers.  The large number of packages available makes prospective brides or customers confused about which wedding package is suitable for their wedding. The a priori algorithm method is used in this research to find recommendations for wedding packages based on existing transaction data and to improve company strategies and sales of other wedding packages. The Apriori algorithm is used to help computers learn patterns of association rules. This algorithm looks for a group of things that match the given criteria or order and have a certain frequency value. From this research, customers tend to order Photographer & Documentation and MUA → Deluxe packages more often, and these orders account for 44% of all package order transaction data. Transaction data for ordering the MUA→Deluxe Package was 41.3%. Photographer & Documentation package transaction data → Deluxe Package is 41.2%. And transaction data for ordering the MUA package → Premium Deluxe Package is 41.3%.
MENGUKIR KOMPETENSI DIGITAL : STUDI KASUS PELATIHAN MICROSOFT EXCEL DALAM MENINGKATKAN KETERAMPILAN PENGOLAHAN DATA SISWA Afrizal Rizqy Pratama; Zaehol Fatah
Jurnal Riset Teknik Komputer Vol. 2 No. 2 (2025): Juni : Jurnal Riset Teknik Komputer (JURTIKOM)
Publisher : CV. Denasya Smart Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69714/sgtsdx53

Abstract

This study aims to assess the extent to which Microsoft Excel training is expected to improve the information processing skills of students in Madrasah aliyah (MA) Sunan Ampel, Sumberkima, Buleleng, Bali. Through a case study approach, we examine how this training successfully sculpts advanced-level students’ competencies, transforming them from passive users into individuals fluent in processing information. A curriculum focused on practical applications Exceeding expectations , ranging from basic functions to simple information visualization, is proven to significantly improve students’ ability to sort, analyze, and present information. The method applied in this study was a practice-based training, followed by an assessment of the skills of the participants after the training. The research findings indicated that microsoft training exceeded expectations was able to significantly improve students’ information retrieval skills, accelerating the process of information recapitulation and analysis. However, it was found that a proportion of participants still required individual assistance to achieve full mastery on the more advanced features. Overall, this training had a positive influence on improving information processing skills in Madrasah Aliyah (MA) Sunan Ampel Sumberkima, Buleleng, Bali. as well as can be an initial step to optimize the utilization of technology in educational information processing.  
Pelatihan Dasar Desain Grafis Menggunakan Aplikasi CorelDRAW Di SMK 1 Ibrahimy Sukorejo Rudi Ananta Al Hidayah; M. Andrik Muqorrobin Pratama; Zaehol Fatah
JURNAL ILMIAH RESEARCH STUDENT Vol. 2 No. 2 (2025): September
Publisher : CV. KAMPUS AKADEMIK PUBLISING

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61722/jirs.v2i2.5756

Abstract

Graphic design skills are important in this digital era, butinitial observations show that students still have limitations inmastering design software. Therefore, the CorelDRAW training programaims to equip students with theoretical and practical knowledge inthe use of this application. The training was conducted intensively, coveringintroduction to the interface, basic to advanced features of CorelDRAW, as well ashands-on practice in making various graphic design products such as logos,posters, and pamphlets. Thus, this training not only improvestechnical competence, but also fosters students' interest and potential in the field of graphicdesign. It is hoped that the results of this study can be a reference for otherschools in developing graphic design skills improvement programs that arerelevant to industry needs.
Analisis Epoch dan Learning Rate untuk Meningkatkan Akurasi Pemrosesan Data Jilbab Instan dan Non-Instan di Teachable Machine: Analisis Epoch dan Learning Rate untuk Meningkatkan Akurasi Pemrosesan Data Jilbab Instan dan Non-Instan di Teachable Machine Dila Puspita Dewi; Zaehol Fatah
Jurnal Mahasiswa Teknik Informatika Vol. 4 No. 1 (2025): Jurnal Jamastika, Volume 4 Nomor 1 April 2025
Publisher : Universitas Ngudi Waluyo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35473/jamastika.v4i1.3501

Abstract

Penelitian ini mengkaji cara menggunakan Teachable Machine untuk mengoptimalkan pemrosesan data penggunaan hijab non-instan dan instan dengan menganalisis nilai learning rate dan epoch. Tujuan dari penelitian ini adalah menerapkan teknik pembelajaran transfer pada Teachable Machine untuk meningkatkan akurasi pengenalan penggunaan hijab. Dataset penggunaan hijab instan dan non instan Detection merupakan data gambar yang digunakan dalam penelitian ini.Data yang digunakan pada gambar dataset penelitian ini adalah dataset hijab instan dan non- instan yang diperoleh dari sumber internet dengan menggunakan metode web scraping pada platform internet di google image dan pinterest. Dalam pengumpulan data, dilakukan Scraping untuk mengunduh hasil pencarian pada platform. proses pelatihan model di Teachable Machine, agar model dapat mengenali dan mengklafikasikan hijab dengan akurasi yang tinggi sehingga dengan cara ini, dapat dengan mudah menemukan hijab yang sesuai dengan preferensi mereka. Kata Kunci: Hijab Instan dan Non-Instan, Teachable Machine, Machine Learning   Teachable machine is a platform that makes it easy for anyone to design machine learning models. The aim of this research is to apply transfer learning techniques on Teachable Machine to increase the accuracy of recognizing the use of the hijab. The dataset of instant and non-instant hijab use Detection is the image data used in this research. The data used in the image dataset of this research is the instant and non-instant hijab dataset obtained from internet sources using the web scraping method on the internet platform at Google Image and pinterest. In data collection, scraping is carried out to download search results on the platform and the model training process on Teachable Machine. Through effective parameter configuration, namely 50 epochs, batch size 64, and learning rate 0.001, the model managed to achieve 100% accuracy on training and testing data. The results show that the model not only learns quickly, as evidenced by the loss graph which experiences a sharp decline at the beginning of training and stabilizes after several epochs. Consistent performance in testing data shows that the model has been able to generalize well. Further analysis through cross-validation and testing with different datasets is recommended to ensure generalizability and identify potential overfitting. These findings indicate that the approach used is effective in producing high-performing and stable models.   Keyword: Instant hijab, Non instant hijab, Teachable Machine, Machine Learning
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