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All Journal Jurnal Nalar Pendidikan CommIT (Communication & Information Technology) Explore: Jurnal Sistem Informasi dan Telematika (Telekomunikasi, Multimedia dan Informatika) Scientific Journal of Informatics Register: Jurnal Ilmiah Teknologi Sistem Informasi KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) Informatika Mulawarman: Jurnal Ilmiah Ilmu Komputer Knowledge Engineering and Data Science JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) JPPM (Jurnal Pengabdian dan Pemberdayaan Masyarakat) Jurnal Mantik Progresif: Jurnal Ilmiah Komputer Infotekmesin Jurnal Informatika dan Rekayasa Elektronik JATI (Jurnal Mahasiswa Teknik Informatika) Madani : Indonesian Journal of Civil Society Infokes : Jurnal Ilmiah Rekam Medis dan Informasi Kesehatan Tadris : Jurnal Penelitian dan Pemikiran Pendidikan Islam Journal of Dinda : Data Science, Information Technology, and Data Analytics Prosiding Seminar Nasional Pengabdian Kepada Masyarakat IJCOSIN : Indonesian Journal of Community Service and Innovation Proceeding of International Conference Health, Science And Technology (ICOHETECH) eProceedings of Engineering Jurnal Informatika: Jurnal Pengembangan IT Jurnal MediaTIK Journal of Mechatronics and Artificial Intelligence Transaction on Informatics and Data Science
Ummi Athiyah
Institut Teknologi Telkom Purwokerto
Religion Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mechanical Engineering Medicine & Pharmacology Nursing Public Health Social Sciences Veterinary Other

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PENGEMBANGAN MEDIA PEMBELAJARAN BIOLOGI SEMESTER II KELAS X SMA BERBASIS LECTORA INSPIRE Ummi, Athiyah
JURNAL NALAR PENDIDIKAN Vol 6, No 1 (2018): JURNAL NALAR PENDIDIKAN
Publisher : LPM Penalaran UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (503.774 KB) | DOI: 10.26858/jnp.v6i1.6041

Abstract

menggunakan Lectora Inspire yang dapat memudahkan siswa SMA Negeri 10 Gowa agar dapat menyerap materi yang diajarkan dengan baik. Jenis penelitian yang digunakan yaitu Research and Development (R&D). Menggunakan model pengembangan Hannafin dan Peck yang terdiri dari tahapan: analisis kebutuhan (need assessment), fase perancangan (design phase) dan fase pengembangan dan implementasi (development and implementation phase). Hasil pengembangan ini adalah media pembelajaran offline berbasis audio visual menggunakan Lectora Inspire agar siswa dapat belajar kapan pun dan di mana pun. Pengujian media dilakukan dengan cara validasi oleh ahli media dan ahli materi. Hasil validasi yang diperoleh adalah media ini sangat layak untuk diimplementasikan. Semua fungsi pada media berjalan dengan baik dan layak digunakan. Serta tanggapan siswa terhadap media ini sangat baik. Kata Kunci: Biologi, Media pembelajaran, Lectora Inspire
Perbandingan Metode Logika Fuzzy Untuk Diagnosa Penyakit Diabetes Hasan Nizar; Alifta Salma Shafira; Juvandio Aufaresa; Muhammad Alvi Awliya; Ummi Athiyah
Explore: Jurnal Sistem Informasi dan Telematika (Telekomunikasi, Multimedia dan Informatika) Vol 12, No 1 (2021): Juni
Publisher : Universitas Bandar Lampung (UBL)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36448/jsit.v12i1.1763

Abstract

Salah satu faktor yang utama dalam kehidupan manusia yaitu kesehatan. Jika tubuh kita sehat, maka aktivitas harian yang kita lakukan akan berjalan lebih lancar. Namun, tidak dapat dipungkiri tidak sedikit penyakit yang menyebabkan kematian pada manusia. Salah satunya adalah penyakit diabetes. Diabetes merupakan jenis penyakit gangguan metabolik menahun akibat pankreas tidak memproduksi insulin yang cukup atau tubuh tidak dapat menggunakan insulin yang telah diproduksi secara efektif. Penyakit ini masuk ke dalam masalah utama kesehatan masyarakat di Indonesia dan sayangnya tidak dapat disembuhkan, tetapi apabila sudah dideteksi secara dini, segera diterapi, minum obat secara teratur, dan selalu rajin kontrol ke dokter, maka penderita dapat memperbesar tingkat kesembuhannya. Beberapa metode dalam Fuzzy Logic mampu digunakan oleh pakar untuk memprediksi gejala pada diabetes mellitus. Dalam penelitian ini  membandingkan tiga metode  fuzzy logic dalam mendeteksi dini Diabetes yaitu Meode Fuzzy Mamdani, Metode Fuzzy Sugeno dan Metode Fuzzy Tsukamoto.  Metode fuzzy yang digunakan kali ini diharapkan dapat digunakan untuk menentukan tingkat keakurasian untuk mendeteksi penyakit Diabetes. Dari hasil perbandingan diketahui bahwa metode sugeno lebih baik dengan menghasilkan 97,33% tingkat keakuratan dan  nilai eror atau kesalahan yang kecil yaitu kurang dari 3%. 
Human Intestinal Condition Identification based-on Blended Spatial and Morphological Feature using Artificial Neural Network Classifier Ummi Athiyah; Arif Wirawan Muhammad; Ahmad Azhari
Knowledge Engineering and Data Science Vol 3, No 1 (2020)
Publisher : Universitas Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17977/um018v3i12020p19-27

Abstract

Colon cancer is a type of disease that attacks the intestinal walls cell of humans. Colorectal endoscopic screening technique is a common step carried out by the health expert/gynecologist to determine the condition of the human intestine. Manual interpretation requires quite a long time to reach a result. Along with the development of increasingly advanced digital computing techniques, then some of the weaknesses of the manually endoscopic image interpretation analysis model can be corrected by automating the detection process of the presence or absence of cancerous cells in the gut. Identification of human intestinal conditions using an artificial neural network method with the blended input feature produces a higher accuracy value compared to the artificial neural network with the non-blended input feature. The difference in classifier performance produced between the two is quite significant, that is equal to 0.065 (6.5%) for accuracy; 0.074 (7.4%) for recall; 0.05 (5.0%) for precision; and 0.063 (6.3%) for f-measure.
DESAIN BASIS DATA TERHADAP KEBUTUHAN PETANI BAWANG MERAH Faiz Rizky Fahlevi; Ahmad Muslih Syafi'i; Adytia Abi Restianto; Ummi Athiyah
KLIK- KUMPULAN JURNAL ILMU KOMPUTER Vol 8, No 3 (2021)
Publisher : Lambung Mangkurat University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/klik.v8i3.394

Abstract

Shallot itself is one of the spices that can be easily found in various places. This herb is an important spice in all dishes. Green onions are one of those spices that can be easily found in many places. This herb is an important spice in all dishes. With the creation of these databases, it can help onion farmers or people who are starting to grow onions to find out how the process and items needed in each planting in a field that will be planted with shallots are made. The problems experienced by the lack of shallot farmers basically calculate roughly, with this database a new breakthrough to build more modern farmers in farming, especially shallots. The research method used in this study uses the MySQL application and in this method we use the MySQL application. Query Optimize and Triggers. The discussion explains how the function of the database works to calculate and display the results of the farmers' needs. The use of Query Optimize and Trigger will help farmers with problems when they want to plant, with these Databases it can help onion farmers in the future.Keywords : databases, Shallots, DML , trigger, viewBawang merah sendiri ialah salah satu bumbu yang dapat dengan mudah ditemukan di berbagai tempat. Tanaman ini adalah bumbu penting di semua masakan. Bawang hijau adalah salah satu bumbu yang dapat dengan mudah ditemukan di berbagai tempat. Tanaman ini adalah bumbu penting di semua masakan. Dengan adanya pembuatan databases ini dapat membantu para petani bawang atau orang yang ini memulai menanam bawang untuk mengetahui bagaimana proses dan barang- barang yang dibutuhkan dalam setiap penanaman disuatu lahan yang akan ditanami bawang merah. Problematika yang dialami kurangnya petani bawang merah pada dasarnya menghitung secara kasar, dengan adanya Database ini  merupakan trobosan baru untuk membangun petani yang lebih modern dalam bercocok tanam khususnya bawang merah  .Metode Penelitian yang digunakan pada penelitian kali ini menggunakan aplikasi MySQL dan pada metode ini kami menggunakan Query Optimize dan Trigger. Pembahasan menjelaskan tentang bagaimana fungsi dari basis data berjalan untuk menghitung serta menampilkan hasil dari kebutuhan para petani. Penggunaan Query Optimize dan Trigger akan membantu para petani dalam permasalahan saat ingin menanam, dengan adanya Databases ini bisa membantu kedepannya kepada para petani bawang merah.Kata Kunci : basis data, bawang merah, DML , trigger, view
Diagnosa Resiko Penyakit Jantung Menggunakan Logika Fuzzy Metode Tsukamoto Ummi Athiyah; Felia Citra Dwiyani Putri Rosyadi; Reno Agil Saputra; Hafidz Daffa Hekmatyar; Tufail Akhmad Satrio; Adam Ikbal Perdana
Jurnal Infokes Vol 11 No 1 (2021): Jurnal Ilmiah Rekam Medis dan Informatika Kesehatan
Publisher : Universitas Duta Bangsa Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The heart is one of the most vital organs in the body and its a very important role for humans. Therefore, it is very important to pay attention to the risk of heart disease from an early age. This disease can be detected early with routine examinations. Based on WHO data (2011), heart disease is the number one cause of death in the world and at least 17.5 million or the equivalent of 30% of deaths worldwide are caused by heart disease. From these problems, the researchers created an expert system using the Fuzzy Tsukamoto method to diagnose the risk of heart disease. The benefit of this research is that it can help make it easier for the general public to check the level of risk for heart disease. The input from the system is blood sugar, cholesterol, blood pressure, and body mass index (BMI), while the output is a risk rating for heart disease with 3 categories, namely small, medium, and large. The stages of the fuzzy method Tsukamoto include fuzzification, formation of IF-THEN rules, inference engine, and finally defuzzification. From the application of the fuzzy Tsukamoto produces an expert system that can diagnose heart disease with three risk categories and based on 30 test data, an accuracy value of 83 percent is generated based on a comparison of the system results with expert results.
Implementasi Algoritma Fuzzy Tsukamoto Untuk Diagnosis Penyakit Anemia (Studi Data: Rekam Medis Pasien Ibu RSIA Bunda Arif Purwokerto) Rheni Aprilia Ningrum; Agus Priyanto; Ummi Athiyah
Jurnal Infokes Vol 11 No 2 (2021): Jurnal Ilmiah Rekam Medis dan Informatika Kesehatan
Publisher : Universitas Duta Bangsa Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47701/infokes.v11i2.1303

Abstract

Anemia is caused by a low hemoglobin condition in the human body. Low hemoglobin conditions can cause various symptoms, including fatigue, weakness, dizziness and others. The impact on anemia can reduce concentration, physical endurance and get sick easily. So it is necessary to detect early to diagnose anemia based on the symptoms experienced with maximum accuracy. Users only need to enter the value of symptoms experienced, namely the value of hb, bleeding and weakness, the system will calculate the symptom values using the Tsukamoto fuzzy algorithm. In calculations using the Tsukamoto fuzzy algorithm using the Python programming language, there are 4 stages, namely fuzzification, rule formation, inference engine and defuzzification. At the fuzzification stage, the input symptom value becomes a fuzzy value (0-1), then at the rule formation stage there are 18 rules of 3 symptoms and 3 diagnosis results. After obtaining a rule, it is followed by an inference engine that looks for the α-predicate value in each rule using the min function. After getting the α-predicate value, defuzzification is carried out to get the crisp value or the output value. With the multiple confusion matrix method, the accuracy of the resulting data from the Tsukamoto fuzzy algorithm and prediction data is 85%. This can be used by the community to easily detect anemia early through the website.
Sistem Inferensi Fuzzy: Pengertian, Penerapan, dan Manfaatnya Ummi Athiyah; Adela Putri Handayani; Muhammad Yusril Aldean; Novantri Prasetya Putra; Rafian Ramadhani
Indonesian Journal of Data Science, IoT, Machine Learning and Informatics Vol 1 No 2 (2021): August
Publisher : Research Group of Data Engineering, Faculty of Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (141.454 KB) | DOI: 10.20895/dinda.v1i2.201

Abstract

Logika fuzzy salah satu komponen pembentuk soft computing yang digunakan sebagai cara untuk memetakan masalah dari input ke output yang diharapkan. logika fuzzy memiliki beberapa kelebihan seperti mudah dimengerti karena memiliki konsep matematis yang sederhana, fleksibel untuk digunakan, terdapat toleransi pada data-data yang tidak tepat, mampu memodelkan fungsi-fungsi non-linear yang sangat kompleks, dapat menerapkan pengalaman pakar secara langsung tanpa proses pelatihan, dapat bekerja sama dengan teknik-teknik kendali secara konvensional, dan didasarkan pada bahasa alami. Logika fuzzy memiliki banyak peran di industri seperti bidang Kesehatan, Ilmu Ekonomi, Psikolog, dan Teknologi yang dapat membantu manusia dalam memecahkan suatu masalah dalam kehidupan. Dalam penerapan logika fuzzy terdapat beberapa proses, salah satunya yaitu sistem inferensi. Sistem inferensi merupakan kerangka komputasi yang didasarkan pada teori himpunan fuzzy, aturan fuzzy berbentuk IF-THEN, dan penalaran fuzzy. Manfaat dari inferensi fuzzy yaitu sebagai alat untuk mewakili pengetahuan yang berbeda tentang suatu masalah, serta untuk memodelkan interaksi. Dengan menggunakan metode penelitian studi literatur dari beberapa sumber, ditemukan banyak produk yang dikembangkan dari logika fuzzy seperti pengambilan keputusan, penentuan atau penilaian hasil, perangkat kendali jarak jauh, alat ukur, dan sistem pakar.
Sistem Pendukung Keputusan Prediksi Harga Rumah Kost untuk Mahasiswa IT Telkom Purwokerto Menggunakan Metode Fuzzy Tsukamoto Berbasis Web Ummi Athiyah; Arnelka Hananta; Taufik Maulidi; Vico Meylana Eka Putra; Theo Felix Harianto Purba; Elisabeth Angeline Wilhelmina Bakowatun
Indonesian Journal of Data Science, IoT, Machine Learning and Informatics Vol 1 No 2 (2021): August
Publisher : Research Group of Data Engineering, Faculty of Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (283.78 KB) | DOI: 10.20895/dinda.v1i2.202

Abstract

Purwokerto City is a developing city located in the southwestern part of Central Java Province. Purwokerto is known as thecity of students in Central Java. It is not wrong if many newcomers choose to continue their studies at the favoriteuniversities in this city. One of the universities in this city is the Telkom Purwokerto Institute of Technology. With so manynewcomers who want to continue their studies in this city. Of course, you need a place to live like a boarding house. Eachboarding house has different facilities and also has varying prices, making it difficult for newcomers to choose the boardinghouse. So a decision support system is needed to help students of the Telkom Purwokerto Institute of Technology to make theright decision in predicting the price of a boarding house when choosing a boarding house according to the existing criteriaand funds using the Fuzzy Tsukamoto method.
Penentuan Jurusan Siswa Sekolah Menengah Atas menggunakan Metode Fuzzy Tsukamoto Hikmah Quddustiani; Ummi Athiyah; Made Riza Kartika; Rayhan Hidayat; Luthfi Rakan Nabila
Indonesian Journal of Data Science, IoT, Machine Learning and Informatics Vol 1 No 2 (2021): August
Publisher : Research Group of Data Engineering, Faculty of Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (269.788 KB) | DOI: 10.20895/dinda.v1i2.205

Abstract

According to the Regulation of the Minister of National Education (Permendiknas) Number 22 of 2006, the determination of majors is carried out at the end of the second semester of class X and the implementation of Teaching and Learning Activities (KBM) according to the program majors starts in the first semester of class XI. In fact, there are still many high school students who are confused about choosing a major in a tertiary institution and this phenomenon can be seen in high school students. There are several majors in high school programs such as Natural Sciences (IPA), Social Sciences (IPS), and Language. This research is expected to be able to determine the majors according to the abilities of the new students for the process of selecting majors and provide recommendations that help students in determining the majors in SMA using the Fuzzy Tsukamoto method. The Tsukamoto method is an extension of monotonous reasoning. In the Tsukamoto method, each consequence of the IF-THEN rules must be represented by a fuzzy set with monotonous membership functions assisted by system design using the programming language PHP, HTML, Javascript, and MySQL database, resulting in a decision making system using the fuzzy method. tsukamoto which is a useful website for determining student majors so that it can lighten the work of the school in order to help speed up and make it easier for schools to make decisions in choosing majors.
Pengembangan Perangkat Lunak Untuk Deteksi DDoS Berbasis Neural Network Arif Wirawan Muhammad; Muhammad Nur Faiz; Ummi Athiyah
Infotekmesin Vol 13 No 2 (2022): Infotekmesin: Juli, 2022
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v13i2.1544

Abstract

System security issues are a vital factor that needs to be considered in the operation of systems and networks, which will later be used for disaster mitigation and preventing attacks on the network. Distributed Denial of Services (DDoS) is a form of attack carried out by individuals or groups to damage data through servers or malware in the form of flooding packets, therefore it can paralyze the network system used. Network security is a factor that must be maintained and considered in an information system. DDoS can take the form of Ping of Death, flood, Remote control attack, User Data Protocol (UDP) flood, and Smurf Attack. This study aims to develop software to detect DDoS attacks based on network traffic logs. The software has been tested and run according to the neural network algorithm. This software was developed with an interface that makes it easier for users to detect the source IP whether the IP is carrying out a DDoS attack or normal.
Co-Authors Adam Ikbal Perdana Adela Putri Handayani Aditya Dwi Putro Aditya Dwi Putro Wicaksono Adytia Abi Restianto Agus Priyanto Agustyawan, Arif Ahmad Muslih Syafi'i Ajeng Ayu Suryani Alam Patria Utama Alameka, Faza Alifta Salma Shafira Alika, Shintia Dwi Andreas Rony Wijaya Arif Wirawan Muhammad Arif Wirawan Muhammad Arnelka Hananta Atika Ratna Dewi Azhari, Ahmad Dwi Setiawan, Brandon Elisabeth Angeline Wilhelmina Bakowatun Erlina Marfianti, Erlina Faisal Dharma Adhinata Faiz Rizky Fahlevi Felia Citra Dwiyani Putri Rosyadi Firda Millennianita Firda Millennianita Hafidz Daffa Hekmatyar Hasan Nizar Hasna Shafa Amalia Hikmah Quddustiani Hulqi, Filfimo Yulfiz Ahsanul Irmayatul Hikmah Ismail , Moh Izzati Muhimmah Jannah , Uzlifatul Juvandio Aufaresa Kholidiyah Masykuroh Luthfi Rakan Nabila Made Riza Kartika Maya Nurachmawati Adiningtias Moh. Aminullah Al Fachri Muhammad Alvi Awliya Muhammad Nur Faiz Muhammad Quthb Habiburrahman Muhammad Yusril Aldean Naden, Yoga Nikmatul Khayati Novanda Alim Setya Nugraha Novantri Prasetya Putra Novian Adi Prasetyo Oktavia Jazilatus Sa’adah Pangestu, Happy Gery Puguh Ika Listyorini Rafian Ramadhani Rara Nur Salsabila Rayhan Hidayat Regina Putri Wanda Zahirah Reno Agil Saputra Rheni Aprilia Ningrum Ridha Berlianny Sulistiaputri Saputro, Satria Nur Sausan Sinaga, Rifaldo Yohannes Siti Khomsah, Siti Sudianto Taufik Maulidi Theo Felix Harianto Purba Tri Ginanjar Laksana Tufail Akhmad Satrio Ulya, Fadilla Zundina Vico Meylana Eka Putra Warto Yehezekiel Ramasyah Putra Haloho Yohani Setiya Rafika Nur Yunita Wisda Tumarta Arif