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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Robotics and Automation (IJRA) IAES International Journal of Artificial Intelligence (IJ-AI) Bulletin of Electrical Engineering and Informatics Jurnal Informatika Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Journal of ICT Research and Applications JUITA : Jurnal Informatika International Journal of Advances in Intelligent Informatics MUSTEK ANIM HA Scientific Journal of Informatics JOIV : International Journal on Informatics Visualization Informatika Mulawarman: Jurnal Ilmiah Ilmu Komputer Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) SISFOTENIKA Wikrama Parahita : Jurnal Pengabdian Masyarakat IT JOURNAL RESEARCH AND DEVELOPMENT JURNAL REKAYASA TEKNOLOGI INFORMASI SINTECH (Science and Information Technology) Journal JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI METHODIKA: Jurnal Teknik Informatika dan Sistem Informasi MIND (Multimedia Artificial Intelligent Networking Database) Journal KOMPUTIKA - Jurnal Sistem Komputer TELKA - Telekomunikasi, Elektronika, Komputasi dan Kontrol Building of Informatics, Technology and Science JISKa (Jurnal Informatika Sunan Kalijaga) Jurnal Informatika dan Rekayasa Elektronik Scientific Journal of Informatics Journal of Innovation Information Technology and Application (JINITA) Indonesian Journal of Data and Science Infotek : Jurnal Informatika dan Teknologi Jurnal Teknologi Informatika dan Komputer SKANIKA: Sistem Komputer dan Teknik Informatika Innovation in Research of Informatics (INNOVATICS) Jurnal Teknik Informatika (JUTIF) Jurnal PTI (Jurnal Pendidikan Teknologi Informasi) Jurnal SAINTIKOM (Jurnal Sains Manajemen Informatika dan Komputer) Jurnal Sains Teknologi dan Sistem Informasi JUSTIN (Jurnal Sistem dan Teknologi Informasi) Transformasi Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi) PROSISKO : Jurnal Pengembangan Riset dan observasi Rekayasa Sistem Komputer JOMPA ABDI: Jurnal Pengabdian Masyarakat Jurnal Pengabdian Masyarakat Intimas (Jurnal INTIMAS): Inovasi Teknologi Informasi Dan Komputer Untuk Masyarakat Data Sciences Indonesia (DSI) Jurnal Masyarakat Madani Indonesia Journal Of Artificial Intelligence And Software Engineering Jurnal INFOTEL Journal of Computer Science Contributions (Jucosco) Journal of Computer Science and Information Technology Inovasi Teknologi Masyarakat Jurnal Pengabdian Siliwangi International Journal of Applied Mathematics and Computing.
Anindita Septiarini, Anindita
Mulawarman University
Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Physics Public Health Social Sciences Other

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Enhancing crude palm oil quality detection using machine learning techniques Puspitasari, Novianti; Hairah, Ummul; Kamila, Vina Zahrotun; Hamdani, Hamdani; Septiarini, Anindita; Masa, Amin Padmo Azam
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 14, No 4: August 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v14.i4.pp2955-2963

Abstract

Indonesia, a leading nation in the palm oil industry, experienced a significant increase of 15.62% in crude palm oil (CPO) exports in 2020, effectively meeting the global need for vegetable oil and fat. Therefore, the subjective assessment of CPO quality, influenced by differences in human evaluations, may lead to inconsistencies, necessitating the adoption of machine learning methods. There are several categories of CPO, such as bad and excellent. Machine learning can determine the quality of CPO itself. This study utilizes two distinct categories to measure the quality of CPO. CPO quality data is collected and processed into pre-processing data, in classifying using several methods such as artificial neural network (ANN), k-nearest neighbor (KNN), support vector machine (SVM), decision tree (DT), naïve Bayes (NB), and C.45 using the cross-validation evaluation parameter. The best results are obtained by C.45 and DT with an accuracy of 99.98%.
IMPLEMENTASI LOGIKA FUZZY MAMDANI DALAM SISTEM PENILAIAN KESEHATAN MAKANAN KEMASAN BERDASARKAN LABEL NUTRITION FACTS Ahmad Nur Fauzan; Muhammad Abdillah; Reviansa Fakhruddin Aththar; Anindita Septiarini; Masna Wati
METHODIKA: Jurnal Teknik Informatika dan Sistem Informasi Vol. 11 No. 2 (2025): Volume 11 Nomor 2 Tahun 2025
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/mtk.v11i2.4334

Abstract

The growth of the packaged food industry has increased the need for an easy-to-understand health assessment system for consumers, especially those with limited nutrition literacy. This study develops a Mamdani fuzzy logic-based decision support system to evaluate the healthiness of packaged foods using Nutrition Facts labels. The system processes nutritional parameters such as fat, sugar, salt, fiber, protein, fruit/vegetable/nut content, and calorie content, converting them into linguistic categories like "low," "moderate," and "high" for easier interpretation by lay users. It effectively handles uncertainties and ambiguities in nutrition data, providing classifications like "Unhealthy," "Healthy," or "Very Healthy." Implemented through a web platform using Python and Flask, the system was tested with five food samples, achieving an 80% agreement with the official NutriScore classification. This indicates the potential of the system as a reliable, practical tool to help consumers make quicker and more accurate dietary decisions and improve nutrition awareness.
Implementasi XGBoost dalam Klasifikasi Gagal Ginjal Kronis Menggunakan Dataset Chronic Kidney Disease Abdillah, Muhammad; Sarira, Brayen Tisra; Hidayat, Ahmad Nur; Fauzan, Ahmad Nur; Nurhidayat, Rifki; Septiarini, Anindita; Puspitasari, Novianti
JATISI Vol 12 No 3 (2025): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v12i3.11546

Abstract

Chronic Kidney Disease (CKD) is a serious health issue that can lead to death if not detected early. To support early detection, this study applies the eXtreme Gradient Boosting (XGBoost) algorithm to classify patients at risk of CKD. The dataset used is the Chronic Kidney Disease Dataset from Kaggle, consisting of 400 patient records and 26 clinical attributes. Preprocessing involved imputing missing values and converting categorical features into numerical form. The model was evaluated using accuracy, precision, recall, and F1-score metrics. The results show that XGBoost achieved 99% accuracy, with 98% precision and 100% recall, indicating excellent performance in binary classification tasks. This study demonstrates that XGBoost is a reliable algorithm for automatic prediction of chronic kidney disease. Keywords: XGBoost, chronic kidney disease, classification, machine learning
Enhanced Semarang batik classification using deep learning: a comparative study of CNN architectures Winarno, Edy; Solichan, Achmad; Putra Ramdani, Aditya; Hadikurniawati, Wiwien; Septiarini, Anindita; Hamdani, Hamdani
Bulletin of Electrical Engineering and Informatics Vol 14, No 5: October 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i5.9347

Abstract

Batik is an important part of Indonesia’s cultural heritage, with each region producing unique designs. In Central Java, Semarang is known for its distinctive batik patterns that reflect rich local traditions. However, many people are still unfamiliar with these designs, which threatens their preservation. This study develops an automated system to classify Semarang batik patterns, showing how technology can help safeguard cultural heritage. A convolutional neural network (CNN) approach was used to recognize ten batik types, including Asem Arang, Asem Sinom, Asem Warak, Blekok, Blekok Warak, Gambang Semarangan, and Kembang Sepatu. Pre-processing steps—such as image resizing, cropping, flipping, and rotation—improved model performance and reduced complexity. Five CNN architectures (MobileNetV2, ResNet-50, DenseNet-121, VGG-16, and EfficientNetB4) were tested using 224×224 input size, Adam optimizer, ReLU activation, and categorical cross-entropy loss. Results show VGG-16, ResNet-50, and DenseNet-121 achieved perfect accuracy (1.0) on a dataset of 3,000 locally collected images. These findings highlight CNN models’ strong potential for batik pattern recognition, supporting digital preservation of Indonesian culture.
Penerapan Metode K-Means Clustering Status Gizi Balita Di UPT Puskesmas Barong Tongkok Vicky Pranandika Wijaksana; Hairah, Ummul; Wati, Masna; Puspitasari, Novianti; Septiarini, Anindita
Data Sciences Indonesia (DSI) Vol. 5 No. 1 (2025): Article Research Volume 5 Issue 1, June 2025
Publisher : Yayasan Cita Cendikiawan Al Kharizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/dsi.v5i1.6517

Abstract

Gizi pada anak balita merupakan masalah yang sangat penting untuk diperhatikan terutama bagi orang tua dan tenaga kesehatan. Status gizi balita dapat diketahui berdasarkan indeks Berat Badan menurut Umur dan Tinggi Badan menurut Umur. Penelitian ini bertujuan untuk mengidentifikasi pola-pola yang mungkin ada dalam status gizi balita dan mengidentifikasi kelompok balita yang berisiko tinggi atau berada dalam kondisi gizi yang buruk pada balita di kecamatan Barong Tongkok dengan penerapan K-Means. Data yang digunakan sebanyak 300 data yang akan dicluster menjadi 3 yaitu Underweight, Gizi Baik dan Gizi Lebih menggunakan metode perhitungan jarak Ecludean Distance, Manhattan Distance dan Minkowski Distance. Hasil pengujian Sum Squared Error (SSE) menunjukkan metode Minkowski Distance lebih unggul karena mendapatkan nilai error terkecil sebesar 815,4409. Sebanyak 133 Balita dalam kategori Gizi Baik (C1), 83 Balita dalam kategori Gizi Lebih (C2), dan 84 Balita dalam kategori Underweight (C3).
Implementasi Logika Fuzzy Mamdani Dalam Klasifikasi Kategori Berat Badan Berbasis IMT Ambon, Matelda Yunanta; Lili, Juniver Veronika; Bandhaso, Victor; Wati, Masna; Septiarini, Anindita
Infotek: Jurnal Informatika dan Teknologi Vol. 8 No. 2 (2025): Infotek : Jurnal Informatika dan Teknologi
Publisher : Fakultas Teknik Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jit.v8i2.30637

Abstract

Body Mass Index (BMI) is a common method used to classify body weight based on the ratio of weight to height. However, its accuracy is often questioned because it does not account for age and gender, which also influence body composition. This study implements the Mamdani fuzzy logic approach to classify body weight based on BMI while considering age and gender. The system utilizes fuzzy membership functions to dynamically determine categories such as Underweight, Normal, Overweight, and Obese, and is developed using the Python programming language with interactive visualizations. Testing results show that the system can provide more adaptive and personalized classifications. Defuzzification values, such as 59.48 for a BMI of 24.22, indicate a classification consistent with WHO standards—namely, the Normal category. The system also demonstrates that classification results may vary for the same BMI when age or gender differs, as illustrated in multi-demographic visualizations. The centroid defuzzification method produces stable and representative outputs. Evaluation results show high accuracy, consistency in rule base, and an ability to handle data uncertainty. Thus, this system serves as a more flexible alternative to conventional methods in body weight classification.
KLASIFIKASI INTENSITAS HUJAN DI SAMARINDA MENGGUNAKAN LOGIKA FUZZY MAMDANI Putri, Septi Aulia; Asmita, Rizka; Nggotu, Antonieta Aryuka Paskalia; Hutapea, Vedra Dian Sierrafina; Septiarini, Anindita; Wati, Masna
TRANSFORMASI Vol 21, No 1 (2025): TRANSFORMASI
Publisher : STMIK BINA PATRIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56357/jt.v21i1.422

Abstract

This study aims to classify rainfall intensity in the Samarinda area into three categories: light rain, moderate rain, and heavy rain based on three meteorological variables: temperature (in °C), air pressure (in hPa), and rainfall (in mm) to provide a more adaptive and accurate classification of rainfall intensity based on local weather conditions in Samarinda, which is prone to disasters due to high rainfall intensity. The data used in this study was obtained from the Meteorology, Climatology, and Geophysics Agency (BMKG) Samarinda for the period of October to December 2024. This study implements the Mamdani Fuzzy Logic method, which consists of the stages of fuzzification, rule base application, inference, and defuzzification. Fuzzy logic was chosen due to its ability to handle data that is ambiguous and uncertain, which is common in weather phenomena. Testing results on 50 random weather condition data samples indicate that the developed Mamdani fuzzy model achieved an accuracy of 100% on the test data, demonstrating consistency between the resulting rainfall intensity classification and actual data. Based on these findings, this model can be utilized as a support tool for decision-making, both by individuals and local government agencies, in efforts to monitor and mitigate extreme weather conditions in Samarinda, East Kalimantan.Keywords : Fuzzy Logic, Mamdani Method, Rainfall Intensity, Classification
Comparison of Noise Using Reduction Method for Repairing Digital Image Masa, Amin Padmo Azam; Fajri, Muhamad Mushfa Hikmatal; Septiarini, Anindita; Winarno, Edy
JOIV : International Journal on Informatics Visualization Vol 8, No 4 (2024)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.8.4.2032

Abstract

Digital images are used to become a visual bridge of information. The information data must be precise so that the information can be adequately conveyed, but in the process, digital images sometimes experience a change in quality. One of the causes of this change is noise, where the image affected by noise is of poor quality, so misinformation can occur. This problem can be solved using filtering methods, but there are so many filtering methods. In this study, five filtering methods were used, including the Gaussian filter, mean filter, median filter, wiener filter, and conservative filter, to be compared with two types of noise, such as salt and pepper and speckle, so that the best method for noise reduction in digital images is known based on the criteria that have been set determined. The research results were determined based on the value of the measurement parameters Mean Square Error (MSE) and Peak Signal-to-Noise Ratio (PSNR). The results show that the conservative method is the best based on the parameter values of MSE 3.21 and PSNR = 37.99. However, when viewed visually, the median method is superior for reducing noise in digital images that have been carried out. The results of the research can be used as information to develop future research, especially in the field of digital image processing.
KLASIFIKASI PENYAKIT TANAMAN DAUN PADI MENGGUNAKAN METODE DEEP LEARNING DENGAN TEKNIK TRANSFER LEARNING MOBILENET Tulili, Hadie Pratama; Septiarini, Anindita; Hamdani
Jurnal Informatika dan Rekayasa Elektronik Vol. 8 No. 2 (2025): JIRE November 2025
Publisher : LPPM STMIK Lombok

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36595/jire.v8i2.1737

Abstract

Pertanian padi memiliki peran penting dalam ketahanan pangan, namun produksi sering terganggu akibat penyakit daun seperti Blast, Brown spot, dan Hispa. Klasifikasi manual kurang efektif karena membutuhkan waktu dan keahlian khusus. Penelitian ini mengusulkan klasifikasi otomatis menggunakan transfer learning dengan arsitektur MobileNetV1 dan MobileNetV2. Kontribusi orisinal dari penelitian ini berupa validasi performa dan optimasi spesifik pada arsitektur MobileNet untuk kasus penyakit daun padi, termasuk analisis komparatif pada konfigurasi Dense layer dan rasio data training. Dataset terdiri dari 2000 citra empat kelas yang dibagi menjadi data train, test, dan validation untuk mencegah overfitting. Model dilatih menggunakan konfigurasi Dense layer 32, 64, dan 256 dengan rasio data 7:2:1 dan 8:1:1. Model terbaik diperoleh dari MobileNetV2 dengan 64 neuron dan rasio 8:1:1, menghasilkan akurasi 93,50%. Hasil ini menunjukkan bahwa MobileNetV2 dapat menjadi metode yang efisien dan akurat untuk klasifikasi penyakit daun padi serta mendukung pengambilan keputusan petani secara lebih cepat.
Sosialisasi Gemar Menabung Kepada Anak SD Negeri 038 di Desa Bendang Raya Sakti, Dwi Nika; Septiarini, Anindita; Hamdani, Hamdani
Inovasi Teknologi Masyarakat (INTEKMAS) Vol. 1 No. 2 (2023): December 2023
Publisher : Wadah Inovasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53622/intekmas.v1i2.231

Abstract

Sosialisasi adalah salah satu sarana yang mempengaruhi kepribadian seseorang. Sosialisasi biasa di sebut sebagai teori mengenai peranan (role theory). Karena dalam proses sosialisasi diajarkan peran-peran yang harus dijalankan oleh individu. Menabung saat ini merupakan hal yang penting. Menabung sudah mulai ditanamkan sejak dini oleh beberapa orang tua kepada anaknya, mengajari anak menabung sejak dini juga bisa membentuk kepribadian positif, menabung bermakna mengajari anak bagaimana melatih kesabaran, dan menabung berguna untuk simpanan masa depan Karena tabungan memiliki peranan penting di masa depan. Menabung berarti menyisihkan sebagian uang kita miliki untuk disimpan. Menabung merupakan salah satu cara untuk mengelola uang. Menabung yang paling mudah bagi anak-anak adalah menabung di celengan. Memiliki kebiasaan menabung sudah jelas sangat berguna untuk masa depan. Menabung adalah menyimpan sejumlah uang agar dapat digunakan di kemudian hari jika diperlukan. Semakin banyak duit yang ditabung maka semakin baik. Kegiatan sosialisasi ini dilaksanakan di SD Negeri 038 Tenggarong.
Co-Authors Abdul Razak Aliudin Achmad Solichan Adi Muhammad Syifai Adnan, Fahrizal Afifah, Dinda Nur Agus Qomaruddin Munir AHMAD ANSYORI Ahmad Nur Fauzan Ajay, Muhammad Akhmad Masyudi Akhmad Syaifudin, Encik Alameka, Faza Aldi Daffa Arisyi Alif Rifa’i Alvito Gabbriel Saputra Alyani Noor Septalia Amalia, Syaffira Rizky Ambari, Nasser Ambon, Matelda Yunanta Andi Tejawati Andri Syafrianto Anita Ahmad Kasim Annisa Putri Novalianti Anton Prafanto Antonieta Aryuka Paskalia Nggotu Ardi Setyiawan Arif Hidayat Arindra Nurshadrina Ramadini Arini Wijayanti Asmita, Rizka Aulia Rahman Awang Harsa Kridalaksana Awang Zheri Rhesvianur Az Zahrah, Rezha Nur Bandhaso, Victor Bima Prihasto Briyan Efflin Syahputra Budi Rahmani Budiman, Edy Cakra Dewandaru Chairunnisa Ardiansyah Lamasitudju Christy Maulidiah Daffa Putra Mahardika Didit Suprihanto, Didit Dwi Prasetio Dyna Marisa Khairina Edy Winarno Enny Itje Sela Ery Burhandenny, Aji Ery Burhandeny, Aji Evi Wildana Fahrozi, Muhammad Naufal Fairil Anwar Fajri, Muhamad Mushfa Hikmatal Fandi Alief Al Akbar Farida Djumiati Sitania Fathia Nuq Qamarina Fauzan, Ahmad Nur Fayza Virdana Addiza Firyal, Tasya Nadina Fornia, Daviana Dwitasari Enka Fuad, Natalie Gempar Panggih Dwi Gideon Simalango, Yanuar Gunawan, Ayu Lestari Hairah, Ummul Hairah, Ummul Hakim, Muhammad Irvan Hamdani Hamdani . Hamdani Hamdani Hamdani Hamdani Hamdani Hamdani Hamdani Hamdani Hanif, Ahmad Luthfi Hariyanto Harry Tanni Pagiu Hatta, Heliza Rahmania Haviluddin Haviluddin Haviuddin, Haviluddin Heliza Hatta Heliza Rahmania Hatta, Heliza Rahmania Henderi . Heni Sulastri Herlawati Herlawati Heru Ismanto Hidayat, Ahmad Nur Hutagalung, Wilson Boyaron Hutapea, Vedra Dian Sierrafina Ibnu Amri Thaher Ifnu Umar Indah Fitri Astuti Indah Wulan Lestari Irfan, Aliya Irsyad, Akhmad Kalingga Dwindra Putraka Kamila, Vina Zahrotun Kiki Purwanti Laraswati, Sherina Lempas, Gidion Lili, Juniver Veronika Lukman Nadjamuddin M. Rizky Nilzamyahya Maharani, Agustina Dwi Mahendra, Dicky Alvian Masa, Amin Padmo Azam Masna Wati Maya Agustina Mewengkang, Alfrina Muhamad Azhari Muhammad Abdillah Muhammad Abdillah Muhammad Aidil Saputra Muhammad Andas Lesmana Muhammad Bakri Muhammad Dzacky Muhammad Ifandi Muhammad Nur Ramadhan Muhammad Rafif Hanif Muhammad Sofian Sauri Mu’nisah Assisi Najwa Felira Zetti Nanda Arianto Nathaniela Aptanta Parama Nggotu, Antonieta Aryuka Paskalia Novi Puspitasari Novianti Puspitasari Nupa, Joy Disanto Nur Madia Nurcahyono, Damar Nurhidayat, Rifki Nurmadewi, Dita Olivia Octavia Padmo Azam Masa, Amin Patricia Chandra Pebianoor, Pebianoor Prafanto, Anton Pramudya, Pranata Eka Pratiwi, Sinthya Ayu Puguh Budi Prakoso Puspitasari, Novianti Puspitasari, Novitanti Putra Ramdani, Aditya Putri, Septi Aulia Rafi Ichsanul Iqbal Rahmadya Trias Handayanto Rahmat Kamara Raihanfitri Adi Kalipaksi Rajiansyah, Rajiansyah Rakhmat Purnomo Ramadhaniaty, Dinda Raudhya Azzahra Reski Harisma Dewi Barkah Reviansa Fakhruddin Aththar Ricky Anggari Risky Kurniawan Riswandi Syam Rita Diana Riyayatsyah, Riyayatsyah Rizqi Saputra Rohman, Reisa Maulidya Rondongalo Rismawati Rosmasari, Rosmasari Sadewa, Bintang Putra Saipul, Saipul Sakti, Dwi Nika Salsabila, Nur Maya Saragih, Muhammad Nabil Sarira, Brayen Tisra Satria Bagus Eka Chandra Saucha Diwandari Setiawan, Maulana Agus Sihombing, Yobel Fernanda Siti Retno Wulandari Sophy Awaliah Sugandi Sugandi Sumaini Sumaini Supriyono Supriyono Supriyono Supriyono Surya Eka Priyatna Syaffira Rizky Amalia Syifani, Sarah Taruk, Medi Tejawati, Andi Theresia Amelia Pawitra Tulili, Hadie Pratama Ummul Hairah Ummul Hairah Vicky Pranandika Wijaksana Viny Christanti M Wahyudi, Moh Ikhwan Wati, Masna Wibisono, Bramantyo Ardi Harimurti Widians, Joan Angelina Wintin, Chintia Liu Wiwien Hadikurniawati Yanuar Satria Gotama Yasmin, Annisa Yudi Sukmono Yuyun Nabilawati Rumbia zahra salsabila Zainal Arifin Zulfariansyah, Muhammad