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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) JURNAL SISTEM INFORMASI BISNIS Jurnal Simetris TEKMAPRO Journal of Industrial Engineering and Management Prosiding SNATIF Jurnal Teknologi Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Transformatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Jurnal Mantik Penusa SISFO Ekonomi dan Bisnis Aisyah Journal of Informatics and Electrical Engineering bit-Tech JATI (Jurnal Mahasiswa Teknik Informatika) JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Jurnal Teknologi Informatika dan Komputer Indonesian Journal of Technology, Informatics and Science (IJTIS) Jurnal Dialektika Informatika (Detika) Journal La Multiapp Bulletin of Computer Science Research Jurnal Pengabdian Masyarakat - Teknologi Digital Indonesia Malcom: Indonesian Journal of Machine Learning and Computer Science Jurnal Bina Informatika dan Komputer (BINER)
Ahmad Abdul Chamid
Program Studi Teknik Informatika, Fakultas Teknik, Universitas Muria Kudus
Aerospace Engineering Automotive Engineering Chemical Engineering, Chemistry & Bioengineering 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 Industrial & Manufacturing Engineering Mechanical Engineering Social Sciences Other

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Development of a Web-Based Selling System Utilizing the RajaOngkir API at Toko Hijab ByAlya to Enhance Online Transaction Performance Safitri, Sabrina Alya; Wijayanti, Esti; Chamid, Ahmad Abdul
Journal La Multiapp Vol. 6 No. 3 (2025): Journal La Multiapp
Publisher : Newinera Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37899/journallamultiapp.v6i3.2266

Abstract

Toko Hijab By Alya, located in Kudus, is a newly established hijab retail store that faces challenges in reaching potential customers who do not use mobile-based e-commerce applications. To address this issue, a web-based selling system has been developed, integrated with the RajaOngkirAPI. This system allows customers to conveniently purchase hijab products online without the need to install additional applications, while simultaneously providing real-time and accurate shipping cost estimations. The integration of the RajaOngkir API enables the calculation of shipping fees from various courier services, enhancing transparency and improving customer satisfaction regarding delivery charges. The web-based platform not only simplifies the shopping experience but also provides clear and accessible delivery information, enabling the store to expand its market reach and increase online transaction volume. The implementation of this system is expected to significantly improve online sales performance and provide customers with a seamless shopping experience.
Comparative Analysis of Machine Learning Algorithms for Predicting Patient Admission in Emergency Departments Using EHR Data Chamid, Ahmad Abdul; Nindyasari, Ratih; Ghozali, Muhammad Imam
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 9 No 2 (2025): April 2025
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v9i2.6188

Abstract

Every patient who is rushed to the Emergency Department needs fast treatment to determine whether the patient should be inpatient or outpatient. However, the existing fact is that deciding whether an inpatient or outpatient must wait for the diagnosis made by the existing doctor, so if there are many patients, it generally takes quite a long time. So, to predict patient admissions to the emergency unit, a machine learning model that can be fast and accurate is needed. Therefore, this study developed a machine learning and neural network model to determine patient care in Emergency Departments. This study uses publicly available electronic health record (EHR) data, which is 3,309. The model development process uses machine learning methods (SVM, Decision Tree, KNN, AdaBoost, MLPClassifier) and neural networks. The model that has been obtained is then evaluated for its performance using a confusion matrix and several matrices such as accuracy, precision, recall, and F1-Score. The results of the model performance evaluation were compared, and the best model was obtained, namely the MLPClassifier model with an accuracy value = 0.736 and an F1-Score value = 0.635, and the Neural Network model obtained an accuracy value = 0.724 and an F1-Score value = 0.640. The best models obtained in this study, namely the MLPClassifier and Neural Network models, were proven to be able to outperform other models.
Pengunaan Barcode dalam Sistem Inventory Modern untuk Meningkatkan Akurasi dan Kecepatan Operasional: Utilization of Barcode Technology in Modern Inventory Systems to Enhance Accuracy and Operational Efficiency Maulana, Sahidin Achmad Noor; Wijayanti, Esti; Chamid, Ahmad Abdul
MALCOM: Indonesian Journal of Machine Learning and Computer Science Vol. 5 No. 3 (2025): MALCOM July 2025
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/malcom.v5i3.1943

Abstract

Pengelolaan stok di gudang sering menghadapi tantangan seperti kesalahan pencatatan, inefisiensi proses, dan kurangnya transparansi data. Untuk mengatasinya, penelitian ini bertujuan merancang dan mengimplementasikan aplikasi inventory berbasis barcode guna meningkatkan efisiensi dan akurasi operasional. Aplikasi dilengkapi dengan fitur seperti pendaftaran produk, pemindaian barcode untuk barang masuk dan keluar, serta pencatatan riwayat transaksi secara real-time dan terintegrasi. Teknologi barcode memungkinkan pencatatan otomatis yang dapat mengurangi kesalahan manusia dan mempercepat proses pengelolaan stok. Metode pengembangan sistem yang digunakan adalah metode Prototyping, yang memungkinkan pengembangan sistem dilakukan secara bertahap melalui pembuatan model awal dan penyempurnaan berkelanjutan berdasarkan umpan balik pengguna. Pendekatan ini sesuai diterapkan dalam kondisi di mana kebutuhan sistem belum sepenuhnya terdefinisi sejak awal. Studi kasus dilakukan pada sebuah gudang distribusi untuk menguji potensi aplikasi dalam meningkatkan keandalan data dan transparansi pelaporan. Penelitian ini diharapkan dapat memberikan kontribusi terhadap pengembangan sistem inventory yang lebih adaptif, akurat, dan efisien di sektor logistik dan distribusi.
PEMANFAATAN MODEL TOPSIS UNTUK PEMILIHAN PRODUK KERAJINAN DALAM MENINGKATKAN KEUNGGULAN DAN KEARIFAN LOKAL Fiati, Rina; Chamid, Ahmad Abdul; Murti, Alif Catur
Simetris: Jurnal Teknik Mesin, Elektro dan Ilmu Komputer Vol 10, No 1 (2019): JURNAL SIMETRIS VOLUME 10 NO 1 TAHUN 2019
Publisher : Fakultas Teknik Universitas Muria Kudus

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (162.883 KB) | DOI: 10.24176/simet.v10i1.2915

Abstract

Pemerintah daerah pelu melakukan persiapan dalam rangka menghadapi Pasar ASEAN, masih banyak peluang UMKM untuk meraih pangsa pasar dan peluang investasi. Guna memanfaatkan peluang tersebut, maka tantangan yang terbesar bagi UMKM di Indonesia menghadapi pasar Bebas ASEAN adalah bagaimana mampu menentukan strategi yang tepat guna memenangkan persaingan. Salah satu solusinya adalah memunculkan produk unggulan dari industri kerajinan tradisional tanah liat yang sampai sekarang masih berkembang dan merupakan warisan budaya bangsa turun-temurun. Kerajinan ini memiliki kearifan lokal yang perlu dijaga kelestariannya. Semula jumlah objek produk penelitian umkm terbagi menjadi 4 jenis yaitu produk tas, pisau, batik, dan tanah liat, tetapi peneliti menemukan beberapa fakta bahwa produk kerajinan dari industri kerajinan tanah liat memiliki banyak jenis produk dan belum pernah masuk dalam kategori produk unggulan daerah di kabupaten kudus, karena itu produk dari tanah liat dijadikan objek  penelitian. Hasil yang diperoleh untuk menentukan prioritas produk kerajinan tanah liat digunakan sistem pendukung keputusan dengan menerapkan metode Technique For Others Reference by Similarity to Ideal Solution (TOPSIS). Pemilihan   Dalam menentukan prioritas produk kerajinan digunakan lima (5) kriteria diantaranya : Jumlah Unit Usaha, Jumlah Tenaga Kerja, Nilai Produksi, Nilai Investasi, Nilai Kompetitif. Hasil dari penelitian ini dapat dijadikan bahan rujukan atau bahan pertimbangan oleh dinas terkait dalam menentukan produk unggulan daerah, khususnya industri tanah liat yang dalam sejarahnya belum pernah menghasilkan salah satu produknya menjadi produk unggulan kabupaten Kudus.
Analysis of Public Opinion on The Governor Candidate Debate Using LDA and IndoBERT Chamid, Ahmad Abdul; Nindyasari, Ratih; Azizah, Noor; Hariyadi, Ahmad
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 10, No. 3, August 2025
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v10i3.2221

Abstract

The gubernatorial candidate debate was broadcast live streaming through various YouTube channels, which attracted public attention. Many discussions and conversations appeared in the comments section of each YouTube channel that broadcasted the debate. Given the numerous public discussions, it is undoubtedly interesting to analyze the contents of the conversations, as well as the expectations and feedback from the public. However, analyzing conversations in the form of text data will be challenging using conventional methods. Therefore, in this study, public opinion will be analyzed using the topic identification and sentiment classification approaches. Topic identification is conducted to obtain accurate information about what the public is discussing, while sentiment classification is used to determine whether each comment contains positive or negative sentiments. This research is novel because it utilizes data collected from various major media YouTube channels and includes a qualitative analysis of the findings. This study uses public comment data taken from the KPU, NarasiTV, and KompasTV YouTube channels; the results obtained included 4,147 data points. Data preprocessing involves identifying topics using the LDA method, evaluating the LDA model, performing sentiment classification using IndoBERT, and visualizing the results of the public opinion analysis. The results revealed five topics with a perplexity value of -7.7909 and a coherence score of 0.5109. In addition, topic 4 is the most dominant compared to other topics, with 1,146 comments classified as positive sentiment and 504 classified as negative sentiment. Topic 4 reflects how religion, culture, and frequently mentioned figures are perceived and discussed by the public, especially in relation to the gubernatorial election (pilgub) or gubernatorial candidate debates.
Design of an Exam Cheating Detection System Application Based on Machine Learning with the Computer Vision Method Hendrawan, Andra Putra; Wijayanti, Esti; Chamid, Ahmad Abdul
Jurnal Teknologi Informatika dan Komputer Vol. 11 No. 2 (2025): Jurnal Teknologi Informatika dan Komputer
Publisher : Universitas Mohammad Husni Thamrin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37012/jtik.v11i2.2704

Abstract

Exam cheating is a persistent problem facing educational institutions worldwide. This cheating not only harms honest students but also undermines the integrity of the education system. In today's digital age, various forms of cheating are increasingly difficult to detect using manual proctoring methods. For example, test takers can use hidden technological devices or engage in non-verbal communication that is difficult for human proctors to detect. This suggests that traditional proctoring is less effective in addressing increasingly sophisticated cheating. Abstract Exam cheating is a serious problem that can compromise the integrity of the education system. Manual proctoring is often ineffective in identifying suspicious behavior that occurs during exams. This study aims to design and develop a machine learning-based exam cheating detection system with computer vision methods. This system uses facial recognition technology, motion tracking, and object detection to identify suspicious activities such as the use of prohibited devices or unusual movements automatically and in real-time. The method used involves a Convolutional Neural Network (CNN) algorithm for participant face verification, pose estimation for motion analysis, and You Only Look Once (YOLO) for object detection. The results of this system development show that the system can improve efficiency and accuracy in detecting cheating behavior, as well as reduce reliance on manual proctoring.
Image Brightness Improvement Analysis Using HE, AHE, and ESIHE Comparison Methods Riadi, Aditya Akbar; Chamid, Ahmad Abdul
Jurnal Transformatika Vol. 18 No. 1 (2020): July 2020
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v18i1.2370

Abstract

Image improvement is the process to improve visual quality, from the original image to get optimal image results. The first category, this technique operates on the transformation of frequency selection and the second technique operates directly at the pixel level of the image. in this study the Exposure Sub-Image Histogram Equalization (ESIHE) technique will be enhanced with a brightness level to get visual image results. Then ESIHE is compared with other additional techniques, such as Histogram Equalization (HE), Adaptive Histogram Equalization (AHE) from the side of the image. Furthermore, for the even distribution of histograms, we will use ESIHE entropy calculations to show an increase in the image results that are more optimal when compared with HE and AHE. The visual image quality of each technique shows the strength of the method and the superiority of the other methods for various types of images.
Pakcoy Plant Sprinklers Based Internet Of Things Riasti, Savira; Riadi, Aditya Akbar; Chamid, Ahmad Abdul
Jurnal Transformatika Vol. 18 No. 2 (2021): January, 2021
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v18i2.3034

Abstract

Agriculture is a pillar of the economy a nation, with the system and the implementation of good agricultural, so will go the nation economic.One of the causes of the lack of agricultural productivity in Indonesian that is some farmers in Indonesian still relied on climate change rain without blemish. Climate change has caused planting patterns the farmers, so that in the end agricultural products planted could not stable , any process planting .The instability caused the price of agricultural products to be very significant plant at a certain season.This is what causes the thing farmers have to produce more energy and the cost of extra do watering manually so that of the trees can grow fertile and can be harvest pakcoy especially in plants .To overcome the problems hence writers try to make sprinkler system plant with using microcontroller Wemos D1 R1 of experiment to the republic of Indonesian that in arable land plant with using soil moisture capacitive sensors that is going to be the moisture the ground in plants can be monitored over long distances through the android application named Blynk. The system will shut when discharging is out of danger at the boundary moisture expected means of sensors the humidity and turn off water pump.
Pengembangan Chatbot Pada Platform Telegram Sebagai Media Informasi Seputar Handphone Umam, Arfiyan khusnul; Wijayanti, Esti; Chamid, Ahmad Abdul
bit-Tech Vol. 8 No. 1 (2025): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i1.2150

Abstract

Di tengah kompleksitas pasar teknologi yang terus berkembang, generasi muda sering menghadapi tantangan dalam menemukan informasi yang relevan, terutama terkait perangkat seluler. Untuk mengatasi masalah ini, penelitian ini bertujuan mengembangkan Chatbot Tanya Phone, sebuah solusi interaktif yang dirancang untuk memberikan informasi spesifikasi, harga, dan ulasan produk kepada pengguna Telegram. Proses pengembangan chatbot ini mencakup analisis menyeluruh terhadap kebutuhan pengguna, perancangan alur percakapan yang intuitif, serta pengembangan berbasis API Telegram untuk memastikan integrasi yang efisien dan responsif.Implementasi sistem diharapkan dapat memberikan respons yang cepat dan akurat, membantu pengguna dalam memahami informasi penting terkait perkembangan teknologi di pasar handphone saat ini. Metode pengujian yang digunakan dalam penelitian ini adalah black box testing, yang bertujuan untuk memastikan bahwa semua fitur chatbot berfungsi sesuai dengan ekspektasi dan memenuhi kebutuhan pengguna. Selain itu, proses pengujian juga mengidentifikasi beberapa aspek yang memerlukan penyempurnaan guna meningkatkan kinerja chatbot secara keseluruhan. Hasil penelitian menunjukkan bahwa Chatbot Tanya Phone tidak hanya mampu memberikan umpan balik secara real-time, tetapi juga meningkatkan pemahaman pengguna terkait teknologi, memudahkan pencarian informasi, serta memberikan kontribusi positif bagi generasi muda dalam menghadapi perkembangan teknologi yang semakin dinamis di era digital saat ini, serta membantu mereka dalam membuat keputusan yang lebih baik dan memperkuat keterampilan literasi digital mereka untuk beradaptasi dengan perubahan teknologi yang cepat.
Demand Prediction and Apparel Production Management Using AI-Based Decision Tree Ariyanto, Iqbal Haqiqi; Chamid, Ahmad Abdul; Fiati, Rina
bit-Tech Vol. 8 No. 1 (2025): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i1.2325

Abstract

The apparel industry faces significant challenges in demand forecasting due to market volatility, rapid changes in fashion trends, and diverse consumer behavior, especially within e-commerce environments. Traditional forecasting methods such as linear regression and time series models often fall short in addressing the complex dynamics of the modern fashion market. This study presents a novel integration of demand forecasting and size recommendation into a unified AI-based system utilizing the Decision Tree algorithm. The system is designed to predict product demand while also providing personalized clothing size recommendations based on user attributes such as body measurements, style preferences, and seasonal trends. The system was developed using a structured data processing and predictive modeling approach, incorporating user profiles and trend sentiment derived from social media. The evaluation results show that the system achieved an accuracy rate of 87.5% in demand forecasting and 84% user satisfaction for size recommendations. It demonstrated better adaptability and performance compared to traditional methods such as ARIMA. A functional prototype was implemented, allowing users to interactively input data and receive real-time predictions. This study confirms the potential of Decision Tree-based AI models to enhance the shopping experience, reduce product return rates, and optimize inventory management. Future improvements may involve integrating real-time data and advanced technologies such as 3D body scanning to further increase prediction accuracy and personalization in digital fashion retail.
Co-Authors Aditya Akbar Riadi Ahdi Riyono Ahmad Hariyadi, Ahmad Ahmad Jazuli Akbar, Fadhil Akh Sokhibi Alif Catur Murti Alif Catur Murti, Alif Catur Aprilianto, Mohammad Andrean Jaya Ariyanto, Iqbal Haqiqi Bayu Surarso Dimas Satrio Oktavianto Endang Supriyati Endang Supriyati Esti Wijayanti Esti Wijayanti Esti Wijayanti, Esti Evita Noor Sofiana Dewi Hakim, Alvin Rainaldy Hendra Dwi Kurniawan, Hendra Dwi Hendrawan, Andra Putra Ida Nur Aeni Ida Nur Aeni, Ida Nur Ivan Bagus Prasetiyo Juwanda, Farikhin Mahendra, Bagus Rosa Maula Yudhananta, Naufal Maulana, Sahidin Achmad Noor Mohammad Kanzunnudin, Mohammad Muhammad Imam Ghozali Muhammad Rieza Maulana Muhammad Rizki Naila Rizki Salisa Noor Azizah Prayogo, Sandi Ratih Nindyasari Riasti, Savira Rijal, Syaifur Rina Fiati Safitri, Sabrina Alya Sentanu, Arga Seva Amartya Shafian Syah, Aliffaza Sholihul Ibad Sokhibi, Akh Sugiharto, Wibowo Harry Teguh, Aris Wicakosno Umam, Arfiyan Khusnul Wibowo, Yuniar Satrio Wicaksono, Abraham Wahyu