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All Journal PROSIDING SEMINAR NASIONAL Jurnal Statistika Universitas Muhammadiyah Semarang Value Added : Majalah Ekonomi dan Bisnis Jurnal Edukasi dan Penelitian Informatika (JEPIN) Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) BAREKENG: Jurnal Ilmu Matematika dan Terapan JTAM (Jurnal Teori dan Aplikasi Matematika) Variance : Journal of Statistics and Its Applications Abdimas UNWAHAS : Jurnal Pengabdian Masyarakat UNWAHAS Community Development Journal: Jurnal Pengabdian Masyarakat Jurnal Litbang Edusaintech Parameter: Journal of Statistics Prosiding Seminar Nasional Official Statistics Journal of Data Insights Prosiding Seminar Nasional Unimus Parameter: Jurnal Matematika, Statistika dan Terapannya Jurnal Meteorologi dan Geofisika LogicLink: Journal of Artificial Intelligence and Multimedia in Informatics Emerging Statistics and Data Science Journal JUSTINDO (Jurnal Sistem dan Teknologi Informasi Indonesia)
Fauzi, Fatkhurokhman
Program Studi Statistika, Universitas Muhammadiyah Semarang
Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Energy Engineering Health Professions Industrial & Manufacturing Engineering Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Physics Public Health Social Sciences Transportation

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Journal : Journal of Data Insights

 1 
Perbandingan Hasil Klasifikasi Data Iris menggunakan Algoritma K-Nearest Neighbor dan Random Forest : Comparison of Iris Data Classification Results using the K-Nearest Neighbor and Random Forest Algorithms Rahman , Budiono; Fauzi, Fatkhurokhman; Amri, Saeful
Journal of Data Insights Vol 1 No 1 (2023): Journal of Data Insights
Publisher : Department of Sains Data UNIMUS Universitas Muhammadiyah Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jodi.v1i1.135

Abstract

Data mining merupakan suatau metode yang baik untuk menangani data skala besar. Performasi menjadi penting dalam metode data mining. Dua metode yang memiliki performasi terbaik diantaranya K-Nearest Neighbor (KNN) dan Random Forest (RF). Artikel ini membahas terkait perbandingan performasi K-NN dan RF. Data yang digunakan pada penelitian ini adalah Iris. Data dibagi menjadi 80% data training dan 20% data testing. Validasi performasi menggunakan nilai akurasi dan F1-Score. Berdasarkan nilai. Berdasarkan hasil yang didapat metode RF lebih baik dibandingkan dengan metode K-NN. Nilai akurasi yang didapat oleh metode RF adalah 1.00 atau 100% dan nilai F1-Score sebesar 1.00.
Clustering Untuk Menentukan Indeks Kesejahteraan Rakyat di Provinsi Jawa Tengah 2022 Menggunakan Metode Fuzzy C-Means: Clustering to Determine the People's Welfare Index in Central Java Province 2022 Using the Fuzzy C-Means Method Indra Firmansyah; Salmaa Fauziah; Hanif Nur Ibrahim; Fatkhurokhman Fauzi; Tiani Wahyu Utami
Journal of Data Insights Vol 1 No 2 (2023): Journal of Data Insights
Publisher : Department of Sains Data UNIMUS Universitas Muhammadiyah Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jodi.v1i2.149

Abstract

Kesejahtraan rakyat merupakan salah satu tujuan negara yang tercantum pada Undang-undang Dasar 1945. Dalam meningkatakan kesejahtraan rakyat, tentunya perlu adanya pembangunan yang merata. Untuk menjalankan program pembangunan yang merata, harus dilakukan identifikasi berdsarkan karaktaeristik tingkat kesejahtraan rakyat berdasarkan variabel-variabel yang telah ditentukan agar dalam membuat strategi dan mengambil kebijakan untuk meningkatkan kesejahtraan rakyat dapat tepat sasaran dan optimal. Tujuan dari penelitian ini adalah untuk mengetahui pengelompokkan 35 Kabupatan/Kota di Provinsi Jawa Tengah dan k arakteristik dari setiap kelompok berdasarkan indeks kesejahtraan rakyat. Berdasarkan hasil analisis yang dilakukan, bahwa terdapat 35 Kabupaten/Kota di Provinsi Jawa Tengah dapat membentuk 4 kelompok (cluster), dimana pada cluster 0 beranggotakan 8 Kabupaten/Kota dengan karakteristik Jumlah peduduk miskin tinggi, Daya beli cenderung rendah, rata-rata lama sekolah rendah, angka harapan hidup sangat rendah. Pada cluster 1 terdapat 12 Kabupaten/Kota dengan karakteristik Nilai PDRB sangat tinggi, angka pengangguran relatif rendah, angka lama sekolah relatif tinggi. Pada cluster 2 terdapat 5 Kabupaten/Kota dengan karakteristik Nilai PDRB sangat rendah, jumlah penduduk miskin sangat rendah, daya beli sangat tinggi, kepemilikan rumah rendah, kepadatan penduduk tinggi, daya beli tinggi, angka melek huruf tinggi, rata-rata lama sekolah tinggi, dan yang terakhir cluster 3 terdapat 10 Kabupaten/Kota dengan karakteristik PDRB rendah, kepadatan penduduk sangat rendah, kepemilikan rumah sangat tinggi, daya beli cenderung rendah.
Decision Tree Classification Prediction of Covid-19 Cases in Indonesia: Prediksi Kasus Covid-19 di Indonesia Menggunakan Metode Klasifikasi Decision Tree Arafat, Amaliah Sholeha; Anawai Basman, Aprilla; Fauzi, Fatkhurokhman; Amri, Saeful
Journal of Data Insights Vol 2 No 2 (2024): Journal of Data Insights
Publisher : Department of Sains Data UNIMUS Universitas Muhammadiyah Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jodi.v2i2.213

Abstract

Forecasting is the prediction of an event in the present and future using past event data. The purpose of forecasting is to minimize errors in predictions (forecast errors) to provide a higher level of confidence. In the context of the COVID-19 pandemic, forecasting the number of cases can help anticipate surges, allowing for better-preparedness to minimize its impact. Forecasting methods can be categorized into three common classifications: qualitative methods, time series, and causal methods. Time series methods are further divided into statistical methods and machine learning. Machine learning methods are more effective in forecasting as they can accommodate non-linear and complex relationships between inputs and outputs. One of the machine learning methods used is the Decision Tree, which is a predictive model structured in a tree or hierarchical format. The Decision tree is a data processing method for predicting the future by constructing classification and regression models in a tree structure. The decision tree is also the most popular and easily understood classification method. In this study, a classification decision tree is used to forecast positive COVID-19 cases in Indonesia using the Python programming language.
K-Nearest Neighbor (KNN) Method for Weather Data Prediction: Penerapan Metode K-Nearest Neighbour (KNN) Untuk Prediksi Data Cuaca Putri, Agata Dwi Putri; M. Al Haris; Fauzi, Fatkhurokhman; Amri, Saeful
Journal of Data Insights Vol 3 No 1 (2025): Journal of Data Insights
Publisher : Department of Sains Data UNIMUS Universitas Muhammadiyah Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jodi.v3i1.214

Abstract

The weather tends to change frequently every day, so weather forecasts are made to be used as an early warning if sudden weather changes occur. By forecasting the weather, losses can be minimized and people are alert to carry out outdoor activities. From this problem, the K-Nearest Neighbor (KNN) method was applied. This method is expected to provide accurate and efficient information to obtain weather predictions for existing conditions. The data used is secondary data. After conducting research on training data (old data) amounting to 80% and test data (new data) amounting to 20%. The accuracy results from the testing data predictions are 75% with a value of k = 8.
Co-Authors - Tarsan Achmad Fauzan Achmad Fauzan, Achmad Agung Subakti Nuzulullail Ahmad Amrullah B Alfidha Rahmah Alifia Puspita Sari Alwan Fadlurohman Amri, Saeful Amrullah, Setiawan Ana, Nisfatun Nurul Anang Kurnia Anawai Basman, Aprilla Angelina, Lea Anggun Erya Santika Anisa Ma'u Luthfi Anita Retno Indriani Arafat, Amaliah Sholeha Ardelita Ika Fadhlillah Ardiansyah, Muhammad Rifqy Aulia, Syifa Azizah, Apipah Nur Bagus Sartono Barlian, Seftia Amelia Rizki Burhanuddin Izzul Salam Chumairoh, Kamilah Citra Dannu Purwanto Dewi Ratnasari Wijaya Dwi Agustina Eko Yuliyanto, Eko Eny Winaryati Erika Siva Aulia Erlinda, Relly Fabiola, Gwenda Fadillah, Muhammad Reza Fatikha Adha Fahreza Fauziah Rahma Gabriella Hilary Wenur Hanif Nur Ibrahim Haris, M Al Haris, M. Al Hasbi Assidiqi Iis Widya Harmoko Iis Widya Harmoko Iis Widya Harmoko, Iis Widya Indah Manfaati Nur Indah Manfaati Nur Indra Firmansyah Iqbal Kharisudin Izzah, Nasyiatul Junaidi, Muhammad Rifki Khikman, Muhammad Alvaro Laila Khoirun Nisa Lestari, Febi Anggun Lia Aryanti Sholekhah Litasya Shofwatillah M. Al Haris Moh Yamin Darsyah Moh. Yamin Darsyah Multiyaningrum, Riska Nida Faoziatun Khusna Ninu, Maria Febronia Nugrahanto, Rifqi Nur, Rachmat Kahfiwan Oktavia Sri Banowati Pandiriyan, Muhammad Tegar Permatasari, Shella Heidy Prizka Rismawati Arum Putra, Septian Malik Putri Ayu Firnanda Putri, Agata Dwi Putri Putri, Dinda Meyda Putri, Melfia Verahma Qonita Syalsabilla Handayani Rahma Nurmalita Rahmah, Alfidha Rahman , Budiono Rahman, Budiono Rahmawati, Gita Ramadhan, Abimanyu Arya Rhendy K P Widiyanto Rizma Novinda Puteri Rochdi Wasono RR. Ella Evrita Hestiandari Safril Ahmadi Sanmas Salmaa Fauziah Sam'an, Muhammad Sanmas, Safril Ahmadi Sarah, Albertus Dion Septi Winda Utami Setiayani, Wiwik Shinta Amaria Soffi Amalia Nur Kholifah Syafira, Elsa Izza Syaharani, Nabbila Dyah Syahrani, Nabbila Dyah Syaifullah, Ahmad Reyhan Syifa Aulia Tari Fitri Ningsih Tiani Wahu Utami Tiani Wahyu Utami Watur, Annisa Cahyaningrum Widiyanti, Karin Dita Widiyanto, Rhendy K. P. Wiwit Putri Nur Izzaturrohmah Wulan Sari, Wulan Yan Nazala Bisoumi Yuliardi, Fahrul Raditiar Yuni Nurkuntari