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All Journal Teknika Jupiter Biota: Jurnal Ilmiah Ilmu-Ilmu Hayati Pendidikan Bahasa Inggris Jurnal Informatika Jurnal Informatika Proceeding International Conference on Information Technology and Business JOURNAL OF HEALTHCARE TECHNOLOGY AND MEDICINE Sistemasi: Jurnal Sistem Informasi Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal TAM (Technology Acceptance Model) Jurnal Informasi dan Komputer Aptisi Transactions on Technopreneurship (ATT) Jurnal Inovasi Pendidikan Building of Informatics, Technology and Science SERAMBI: Jurnal Ekonomi Manajemen dan Bisnis Islam Sainstek : Jurnal Sains dan Teknologi Jurnal Tecnoscienza Educate: Jurnal Ilmu Pendidikan dan Pengajaran Aurelia: Jurnal Penelitian dan Pengabdian Masyarakat Indonesia Jurnal Ilmiah Mahasiswa Pendidikan Agama Islam Jurnal Informatika: Jurnal Pengembangan IT Jurnal Ilmu Siber dan Teknologi Digital INOVTEK Polbeng - Seri Informatika Jurnal TAM (Technology Acceptance Model) Jurnal Esensi Infokom : Jurnal Esensi Sistem Komputer dan Informasi
Chairani Chairani
Institut Informatika Dan Bisnis Darmajaya
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Analisis Performa Model BiLSTM dan CNN-LSTM Dalam Prediksi Sea Water Level Pada Pelabuhan Berdasarkan Data Historis Kristyanto, Andi; Chairani, Chairani; Sriyanto, Sriyanto
Building of Informatics, Technology and Science (BITS) Vol 7 No 1 (2025): June (2025)
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v7i1.7364

Abstract

Indonesia is a country dominated by waters, so data on sea level rise, one of maritime weather is important. The Meteorology, Climatology, and Geophysics Agency one of its duties, namely conducting observations in meteorology. The Merak-Bakauheni Port serves the busiest crossing route in Indonesia and connects the islands of Java and Sumatra. If there is a disruption due to meteorological factors, shipping and sea transportation activities will be hampered and disrupted. The purpose of this study is to compare the performance of the BiLSTM and CNN-LSTM models in estimating sea water levels at Merak Port based on the results of the parameter analysis used. The steps begin with collecting, processing data, training the model, and analyzing the model. The data used is daily sea water level data over a period of six years from 2019 to 2024. Evaluation of MSE, MAE and RMSE values ​​is used to see the performance of the two models. From this study, the BiLSTM model produced values ​​of 0.0026 (MSE), 0.0224 (MAE), and 0.0512 (RMSE), the CNN-LSTM model values ​​of 0.0044 (MSE), 0.0319 (MAE), and 0.0664 (RMSE), it can be seen that BiLSTM method has more optimal in predicting sea water levels of Merak Port.
Hubungan Pola Asuh Ibu dengan Karies Gigi Anak Balita di TK Perkebunan Nusantara I Kota Langsa Tahun 2019 Chairani, Chairani; Harahap, Juliandi; Zein, Umar
JOURNAL OF HEALTHCARE TECHNOLOGY AND MEDICINE Vol 9, No 1 (2023): April 2023
Publisher : Universitas Ubudiyah Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33143/jhtm.v9i1.2834

Abstract

Masalah karies merupakan penyakit yang sangat luas penyebarannya, dan penderita terbanyak adalah kelompok umur anak-anak. Provinsi Aceh merupakan Provinsi urutan ke-7 dari keseluruhan Provinsi yang ada di Indonesia dengan penduduk yang bermasalah terhadap gigi dan mulut yaitu 30,5%. Sedangkan di lihat dari kelompok usia 1-4 tahun mencapai 10,4%6. Data dari Dinas Kesehatan Kota Langsa pada tahun 2017 angka prevalensi karies gigi pada balita 2-5 tahun adalah sebanyak 306 kasus. Tujuan penelitian ini untuk mengetahui hubungan pola asuh ibu dengan karies gigi anak balita di TK Perkebunan Nusantara I Kota Langsa Tahun 2019. Jenis Penelitian menggunakan survey analitik dengan desain cross sectional. Populasi penelitian ini adalah seluruh anak yang mengalami karies gigi di TK Perkebunan Nusantara I Kota Langsa. Sampel penelitian diambil dari populasi sebanyak 89 orang dengan masing-masing strata (proportional startifed sampling) dan sampel sebanyak 73 responden. Teknik analisa data menggunakan analisa univariat, bivariat dan multivariat dengan menggunakan uji regresi logistik. Hasil penelitian menunjukkan pengaruh yang signifikan hubungan pola asuh ibu berdasarkan dimensi kontrol (p-value 0,001), dimensi kehangatan (p- value 0,000), dan jenis pola asuh ibu (p-value 0,002) terhadap karies gigi pada anak. Kesimpulan pada penelitian ini menunjukkan bahwa sub variabel dimensi kehangatan menjadi penyebab utama karies gigi dengan nilai OR sebesar 13,349 dan IK 3,386-52,632. Saran penelitian ini diberikan kepada orang tua agar memperhatikan pola asuh terhadap anak untuk pencegahan terjadinya karies sejak dini, terutama memberikan motivasi dan perhatian serta contoh perilaku kepada anak untuk selalu menjaga kebersihan gigi. Serta diadakan program penyuluhan dari institusi kesehatan agar informasi tentang perawatan gigi anak dapat diketahui orang tua untuk mengatasi kasus karies.Kata kunci : Karies Gigi, Dimensi Kontrol, Dimensi Kehangatan, Jenis Pola Asuh.The problem of caries is a very widespread disease, and most sufferers are children in the age group. Aceh Province is the 7th province of all provinces in Indonesia with a population with oral and dental problems, namely 30.5%. Whereas seen from the age group 1-4 years it reaches 10.4% 6. Data from the Langsa City Health Office in 2017, the prevalence rate of dental caries in children 2-5 years old was 306 cases. The purpose of this study was to determine the relationship between maternal parenting and dental caries in children under five at Kindergarten Perkebunan Nusantara I Langsa City in 2019. This type of research used analytical survey with cross sectional design. The population of this study were all children who had dental caries in TK Perkebunan Nusantara I Langsa City. The research sample was taken from a population of 89 people with each strata (proportional started sampling) and a sample of 73 respondents. Data analysis techniques used univariate, bivariate and multivariate analysis using logistic regression tests. The results showed a significant influence on the relationship between maternal parenting based on the control dimension (p-value 0.001), warmth dimension (p-value 0.000), and the type of parenting style (p-value 0.002) on dental caries in children. The conclusion of this study shows that the sub-variable of the warmth dimension is the main cause of dental caries with an OR value of 13.349 and CI 3.386-52.632. Suggestions for this study are given to parents to pay attention to child care patterns to prevent caries from an early age, especially to provide motivation and attention as well as examples of behavior for children to always maintain dental hygiene. As well as an extension program from health institutions so that information about children's dental care can be known by parents to deal with caries cases.Keywords: Dental Caries, Control Dimension, Warm Dimension, Type of                       Parenting.
Sistem Pendukung Keputusan Penerimaan Bantuan PKH di Kelurahan Tanjung Sari I Komang Swandika; Achmadi Hudadin Albarqi; Chairani Fauzi; Sri Lestari
Jurnal Esensi Infokom : Jurnal Esensi Sistem Informasi dan Sistem Komputer Vol 8 No 1 (2024)
Publisher : Institut Bisnis Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55886/infokom.v8i1.832

Abstract

Berdasarkan temuan berbagai penelitian, terdapat banyak kesalahan dalam distribusi statistik Program Keluarga Harapan (PKH) yang tidak akurat. Hal serupa juga ditunjukkan oleh hasil survei yang dilakukan di Kelurahan Tanjung Sari , Buay Pemaca, Kab. Ogan Komering Ulu Selatan . Hal ini menunjukkan bahwa masih banyak masyarakat yang masih mempunyai klaim atas uang tersebut namun tidak menerimanya. Terutama jika sejumlah calon peserta berada dalam kondisi miskin atau kurang beruntung dan tingkat kelayakan mereka hampir sama.Penelitian Penerimaan Program Keluarga Harapan (PKH) dengan Memanfaatkan Metodologi Simple Additive Weighting (SAW) dan Weighted Product (WP) pada Sistem Pendukung Keputusan (SPK) PKH di Kelurahan Tanjung Sari, Buay Pemaca .Hasil pada penelitian disini menunjukkan bahwa meskipun terdapat perbedaan di antara masing-masing pendekatan, seperti yang ditunjukkan oleh perbandingan hasil pemeringkatan pada Tabel 9, terdapat kesamaan antara hasil dari Peringkat 1–12 dan perbedaan antara hasil dari Peringkat 13–27.Penelitian menyimpulkan bahwa di Kelurahan Tanjung Sari , Buay Pemaca, , metode Weight Product (WP) dapat direkomendasikan sebagai metode sistem pendukung keputusan penerimaan bantuan PKH. Hasil yang ditampilkan dalam penelitian ini mempunyai rentang nilai yang sangat sempit, menandakan bahwa keakuratan data telah teruji.
CNN-Based Skin Cancer Classification with Combined Max and Global Average Pooling Chairani Fauzi; Fitra Salam S. Nagalay
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 9 No 6 (2025): December 2025
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v9i6.6617

Abstract

Skin cancer is one of the most threatening diseases to human health, with an increase in new cases each year. Early detection plays a crucial role in improving recovery rates, however, conventional diagnostic methods such as biopsy are often invasive, time-consuming, and costly. To address this issue, artificial intelligence-based diagnostic systems, particularly Convolutional Neural Networks (CNNs), offer a promising solution for enhancing diagnostic accuracy and efficiency. This study aims to evaluate the performance of a CNN model that combines Max Pooling and Global Average Pooling (GAP) in detecting skin cancer from digital dermoscopic images. The ISIC (International Skin Imaging Collaboration) dataset was used, focusing on two classes: malignant and benign. The combination of Max Pooling and GAP is intended to increase model precision while reducing the risk of overfitting. The experimental results show that the proposed model achieved a precision of 96.35%, indicating strong performance in minimizing false positives. However, the recall was relatively low at 85.99%, suggesting reduced sensitivity in detecting malignant cases. The overall accuracy of the combined model was 91.68%, slightly lower than the Max Pooling-only model (91.79%). Although the combination does not significantly improve accuracy, it effectively enhances precision to 96.35%. This is a critical advantage in a clinical setting, as it directly translates to minimizing false positive diagnoses and preventing patients from undergoing unnecessary invasive procedures like biopsies.
Sistem Prioritas Proses Pengajuan Pensiun BKPSDM Lampung Tengah Menggunakan Metode Fuzzy Simple Additive Weighting (F-SAW) I Putu Rio Kurniawan; Hariyanto Wibowo; Fitria; Chairani Fauzi
JURNAL TECNOSCIENZA Vol. 10 No. 2 (2026): JURNAL TECNOSCIENZA
Publisher : JURNAL TECNOSCIENZA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51158/esespz53

Abstract

The retirement application process at BKPSDM Lampung Tengah currently faces challenges in determining service priority due to high document volume and diverse criteria. This study aims to develop a decision support system to objectively determine retirement application priorities using the Fuzzy Simple Additive Weighting (F-SAW) method. This method was selected for its ability to handle data uncertainty through fuzzy logic and rank alternatives based on predetermined criteria weights, including retirement type, time urgency, document completeness, and number of dependents. The system was developed using the Waterfall model and implemented as a web-based application. The results demonstrate that the system produces retirement priority rankings with high accuracy. Based on functional testing using Black Box Testing, the system operates according to the design. Furthermore, validation testing shows a consistency level of 99.96% compared to manual calculations. The implementation of this system is expected to accelerate decision-making processes and enhance the efficiency of personnel administration services at BKPSDM Lampung Tengah.
Comparative Analysis of Instance Segmentation Models for House-Level Visual Socioeconomic Classification using Satellite Imagery David Cahyapratama; Chairani Fauzi
SISTEMASI Vol 15, No 8 (2026): Sistemasi: Jurnal Sistem Informasi
Publisher : Universitas Islam Indragiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v15i8.6743

Abstract

House-level visual socioeconomic information can provide a more detailed spatial understanding of residential areas and can support applied urban and commercial analysis. However, official socioeconomic data are often available only at broader administrative levels and may not capture variation among small residential clusters or individual houses. This study compares five instance segmentation models for detecting, segmenting, and classifying individual houses into lower, middle, and upper visual socioeconomic classes using high-resolution satellite imagery. The evaluated models are Mask R-CNN, Cascade Mask R-CNN, YOLO11n-seg, SOLOv2, and Mask2Former. The dataset consists of 1,209 training images with 7,052 annotations and 213 validation images with 1,353 annotations from residential areas in Banten and DKI Jakarta. Annotation reliability was assessed using 100 annotation pairs, producing a quadratic-weighted Cohen’s kappa of 0.8077. Model performance was evaluated using COCO metrics for both segmentation masks and bounding boxes. The results show that Cascade Mask R-CNN achieved the highest observed overall validation performance among the tested configurations. Under the current experimental setting, it produced the strongest combination of object-localization and mask-segmentation metrics. These findings show that comparing multiple instance segmentation models can help identify a more suitable method for house-level visual socioeconomic classification. Unlike previous studies that generally perform area-level socioeconomic estimation or building extraction alone, this study compares multiple instance-segmentation approaches for expert-defined socioeconomic classification at the individual-house level. The resulting output can serve as a supplementary visual socioeconomic layer that complements demographic, accessibility, and commercial data in applied spatial and market-development analyses.
Co-Authors Abda Abda Abdullah, Syaukani Achmadi Hudadin Albarqi Adeng Slamet Aditya, Fiqri Akhmad Unggul Priantoro Ayu Zulfiani Azima, Muhammad Fauzan Belinda Analido David Cahyapratama Dedi Kundana Diki Andita Kusuma DWI SURYANTO Elpisah Fitra Salam S. Nagalay Fitria Fitria . Fitria . Fitria Fitria Harahap, Juliandi Hari Sabita Haris Luthfi, Muhammad Hariyanto Wibowo Herwanto, Riko I Komang Swandika I Putu Rio Kurniawan Kesuma, Martika Ketang Wiyono Kristyanto, Andi Lubis, Nita A. Luh Putu Ratna Sundari M Devid Alam Carnegie Mega Fatimah Rosana Novita, Eka Nur Listanto, Arif Nur ‘Azah pratama, febri Rachma Zannati Rian Sefriadi Rifki, Rifki Arif Rio Kurniawan Rusika, Deddy Setiawan, Gatot B Sherly Trisnawati Siti Mukodimah Siti Nurhaliza Sri Lestari Sri Suning Kusumawardani Sriyanto, Sriyanto Sulyono, Sulyono Triloka, Joko Tupari Tupari Umar Zein W, Muhammad Fahreza Widyawan Yuda Septiawan Yuni Arkhiansyah Yurnaliza, Yurnaliza