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All Journal REKAYASA Jurnal Informatika dan Teknik Elektro Terapan Jurnal Sisfokom (Sistem Informasi dan Komputer) SENTIA 2016 Explore IT : Jurnal Keilmuan dan Aplikasi Teknik Informatika Jurnal Kreativitas PKM Jurnal Informatika Kaputama (JIK) Scientific Journal of Informatics Journal of Computer System and Informatics (JoSYC) Dinamika Informatika: Jurnal Ilmiah Teknologi Informasi SKANIKA: Sistem Komputer dan Teknik Informatika Journal of Electrical Engineering and Computer (JEECOM) International Journal of Computer and Information System (IJCIS) Indexia Kontribusi: Jurnal Penelitian dan Pengabdian Kepada Masyarakat Academic Journal of Computer Science Research (AJCSR) TRILOGI: Jurnal Ilmu Teknologi, Kesehatan, dan Humaniora Jurnal: International Journal of Engineering and Computer Science Applications (IJECSA) Insand Comtech : Information Science and Computer Technology Journal JUSTIFY : Jurnal Sistem Informasi Ibrahimy COREAI: Jurnal Kecerdasan Buatan, Komputasi dan Teknologi Informasi Nusantara Journal of Computers and its Applications Transaction on Informatics and Data Science JOKI: Journal of Computing and Informatics SINAR: Sinergi Pengabdian dan Inovasi untuk Masyarakat JuTISI (Jurnal Teknik Informatika dan Sistem Informasi)
Abu Tholib
Universitas Nurul Jadid
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Mechanical Engineering Medicine & Pharmacology Nursing Physics Public Health Transportation Other

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Implementasi GridSearch dalam Meningkatkan Kinerja Model Support Vector Regresion (SVR) utuk Prediksi Penjualan Produk (Studi kasus : Meubel Rohman Jaya) Ahmad Baidowi Eko Fitra Firmanda; Ahmad Hudawi AS; Abu Tholib; Juvinal Ximenes Guterres

Publisher : Program Studi Teknik Informatika, Fakultas Teknik, Universitas Yudharta Pasuruan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35891/explorit.v16i1.5042

Abstract

In the era of digitalization, product sales forecasting plays a crucial role for companies in estimating future demand. Meubel Rohman Jaya, a furniture business established since 2010, requires accurate predictions to optimize stock availability with the variety of products they produce. This research aims to forecast furniture product sales using the Support Vector Regression (SVR) algorithm with GridSearch optimization. Sales data of 11 furniture products over 30 months (January 2021 - June 2023) were processed through data collection and preprocessing. Modeling was performed using SVR without optimization and SVR with GridSearch optimization to obtain the best parameters. Predictions were generated and then evaluated using the Mean Absolute Percentage Error (MAPE) metric. The results showed that SVR without optimization achieved a MAPE of 40.39%, while SVR with GridSearch achieved a MAPE of 0.45%, indicating a significant increase in accuracy. GridSearch optimization has proven effective in improving prediction performance and is highly recommended for implementation in forecasting product sales at Meubel Rohman Jaya.
Pendampingan Program Start-Up Bisnis Menuju Sekolah Pencetak Wirausaha di Kabupaten Probolinggo Tholib, Abu; Pawening, Ratri Enggar; Junaedi, Deddy
Kontribusi: Jurnal Penelitian dan Pengabdian Kepada Masyarakat Vol. 5 No. 1 (2024): November 2024
Publisher : Cipta Media Harmoni

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53624/kontribusi.v5i1.496

Abstract

Latar Belakang: Program pendampingan ini dilaksanakan untuk mengatasi keterbatasan pemahaman kewirausahaan digital di kalangan SMK di Kabupaten Probolinggo. Tujuan: Kegiatan ini bertujuan membangun ekosistem kewirausahaan melalui pengembangan keterampilan manajerial dan teknis kepala sekolah, guru, dan siswa SMK. Metode: Dalam kolaborasi dengan MKKS SMK Kabupaten Probolinggo, metode yang digunakan mencakup sosialisasi, pelatihan kewirausahaan, penerapan teknologi melalui aplikasi SPW berbasis web, dan pendampingan berkelanjutan. Hasil: Hasilnya menunjukkan peningkatan signifikan pada keterampilan manajerial dan teknis di 47 sekolah mitra, yang kini lebih siap membimbing siswa dalam mengembangkan bisnis. Kesimpulan: Aplikasi SPW juga terbukti memudahkan sekolah dalam pemantauan dan evaluasi kewirausahaan, meningkatkan efisiensi manajemen bisnis di tingkat sekolah.
Thesis Topic Modeling Study: Latent Dirichlet Allocation (LDA) and Machine Learning Approach Hairani, Hairani; Janhasmadja, Mengas; Tholib, Abu; Ximenes Guterres, Juvinal; Ariyanto, Yuri
International Journal of Engineering and Computer Science Applications (IJECSA) Vol 3 No 2 (2024): September 2024
Publisher : Universitas Bumigora Mataram-Lombok

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/ijecsa.v3i2.4375

Abstract

The thesis reports housed in the campus repository have yet to be analyzed to reveal valuable knowledge patterns. Analyzing trends in thesis research topics can facilitate the selection of research topics, aid in mapping research areas, and identify underexplored topics.Therefore, this research aims to model and classify thesis topics using Latent Dirichlet Allocation (LDA) and the Naïve Bayes and Support Vector Machine (SVM) methods. This study employs the LDA method for thesis topic modeling, while SVM and Naïve Bayes are used for classifying these topics. The research results show that LDA successfully modeled five of the most popular thesis topics, namely two related to computer networks, two on software engineering, and one on multimedia. For thesis topic classification, the SVM method demonstrated higher accuracy than Naïve Bayes, reaching 92.80% after the data was balanced using Synthetic Minority Oversampling Technique (SMOTE). The implication of this study is that the topic modeling approach using LDA is able to identify dominant thesis topics. In addition, the SVM classification results obtained better accuracy than Naïve Bayes in the thesis topic classification task.
Pengembangan Sistem Informasi MA Zainul Anwar Kraksaan Berbasis Web dengan Sistem Multi User Manejemen Tholib, Abu; Marzuki, Muhammad Ismail; Tsabbit Albannani, Nur Wahyu; Ihsan, Gilang Hafidzul; Salman, Moh
TRILOGI: Jurnal Ilmu Teknologi, Kesehatan, dan Humaniora Vol 5, No 4 (2024)
Publisher : Universitas Nurul Jadid

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33650/trilogi.v5i4.9721

Abstract

The lack of effective information dissemination methods at MA Zainul Anwar Kraksaan has hindered the community and parents' understanding of school programs. This research aims to develop a web-based information system featuring multi-user management to address these challenges. Using the Research and Development (R&D) approach with the Waterfall model, the study involved stages of need analysis, system design, implementation, testing, and maintenance. Data were collected through observations and interviews, and the findings were used to design a user-friendly system tailored to the school’s needs. The results demonstrate that the developed system significantly improves communication efficiency and transparency, streamlines administrative processes, and provides a robust information portal. The study recommends adopting similar systems in other schools facing comparable challenges to enhance communication and operational efficiency.
Application of the Attention-Based LSTM Method for Rainfall Prediction in East Java Arifin, Zainal; Tholib, Abu; Hidayat, Rian
International Journal of Computer and Information System (IJCIS) Vol 5, No 4 (2024): IJCIS : Vol 5 - Issue 4 - 2024
Publisher : Institut Teknologi Bisnis AAS Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29040/ijcis.v5i4.224

Abstract

This research aims to measure the performance of the Attention-Based Long Short-Term Memory (LSTM) predictive model in rainfall prediction analysis in East Java, with a focus on including the application of the model in predicting complex time-series data. The main objective of this study is to create an efficient and accurate model and to emit the performance of the Attention-Based LSTM algorithm compared to conventional methods. The methodology used includes rainfall data collection, data preprocessing, Attention-Based LSTM model design, training models, and testing to assess accuracy. The results of the study indicate that the Attention-Based LSTM model is able to improve rainfall prediction compared to conventional methods, with the Root Mean Squared Error (RMSE) evaluation metrics with a value of 0.00807 and Mean Squared Error (MSE) with a value of 0.08987 which shows better results, so this model can be relied on for real-world applications.
Penerapan Machine Learning untuk Penentuan Mata kuliah Pilihan pada Program Studi Informatika Fathorazi Nur Fajri; Abu Tholib; Wiwin Yuliana
Jurnal Teknik Informatika dan Sistem Informasi Vol 8 No 3 (2022): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v8i3.3990

Abstract

Informatics study program at Nurul Jadid University does not have a general concentration of knowledge, so that sometimes the selection of elective courses by students is not quite right. This study aims to classify the concentration of knowledge with a data mining approach which can then be used as a recommendation for selecting elective courses by students. In this study, we implement a machine learning algorithm to provide recommendations to students regarding what interests are more suitable to be taken based on the values ​​of prerequisite courses in previous semesters. Student data was obtained from the Head of the Center for Data and Information Systems (PDSI) at Nurul Jadid University with 70 student data from Nurul Jadid University batch 2018. The machine learning algorithm used is Neural Network with Python programming language, the tools used are Google Collab. At the beginning of data collection, then pre-processing is carried out to prepare the dataset in order to get good results, and model training is carried out. After training on the model, then further testing is carried out on the model to determine the performance of the model. The result of the accuracy value in the training model process is 0.83 or 83% and the accuracy of the test data is 0.79 or 79%.
OPTIMASI CHATBOT DALAM SISTEM PENGADUAN PELAYANAN PUBLIK BERBASIS ANDROID Tholib, Abu; Andi, Moh syaiful; Sukron, Moh; Shudiq, Wali Ja'far; Hairani, Hairani; Guterres, Juvinal Ximenes
Insand Comtech : Information Science and Computer Technology Journal Vol 10, No 1 (2025): Insand Comtech
Publisher : Universitas Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53712/jic.v10i1.2637

Abstract

This study presents the development of an Android-based public service complaint application integrated with chatbot technology to improve service responsiveness. The system aims to facilitate community members in submitting complaints and receiving immediate responses through an interactive interface. A user-friendly mobile application was developed using the Kotlin programming language, and chatbot functionality was implemented via API integration to respond to frequently asked questions. The implementation followed the Waterfall model, encompassing stages of analysis, design, implementation, testing, and maintenance. Results show that the application effectively streamlines the complaint process, increases efficiency in complaint management, and enhances communication between the public and local government. The chatbot proved to be reliable in delivering relevant and timely responses, significantly reducing the time needed for initial interactions. This integration demonstrates the potential of artificial intelligence to support e-government services in rural setting
OPTIMASI MODEL RESNET50 UNTUK KLASIFIKASI SAMPAH Sihabillah, Ahmad; Tholib, Abu; Basit, Illiyah Ibnul
Indexia Vol. 6 No. 2 (2024): INDEXIA : Informatics and Computational Intelligent Journal Volume 6 Nomor 2 No
Publisher : Universitas Muhammadiyah Gresik

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30587/indexia.v6i2.9342

Abstract

Penelitian ini mengkaji pemanfaatan arsitektur ResNet50 dalam klasifikasi sampah organik dan anorganik untuk meningkatkan efisiensi pemilahan sampah secara otomatis. Dataset yang digunakan terdiri dari 12.565 gambar sampah organik dan 9.999 gambar sampah anorganik, mencakup berbagai variasi kondisi lingkungan, seperti pencahayaan, ukuran, dan bentuk. Tahapan penelitian meliputi preprocessing data, yang mencakup augmentasi gambar untuk menambah variasi, pembagian dataset menjadi data pelatihan dan validasi, serta penyesuaian bobot kelas untuk menangani ketidakseimbangan dataset. Model dilatih selama lima epoch dengan akurasi validasi tertinggi sebesar 80,15% pada epoch terakhir. Hasil evaluasi menggunakan metrik precision, recall, dan f1-score menunjukkan performa yang baik, dengan kategori sampah organik mencapai recall 91% dan f1-score 84%. Namun, kategori sampah anorganik memiliki precision sebesar 85% dengan recall yang lebih rendah, yaitu 67%. Analisis Confusion matrixmengungkapkan bahwa model mampu mengklasifikasikan sebagian besar sampel dengan benar, meskipun masih terdapat beberapa kesalahan pada kategori anorganik. Secara keseluruhan, penelitian ini membuktikan efektivitas ResNet50 dalam meningkatkan akurasi klasifikasi sampah, mendukung pengelolaan sampah yang berkelanjutan. Dengan optimisasi lebih lanjut, seperti penyesuaian hyperparameter atau augmentasi tambahan, model ini memiliki potensi untuk mencapai performa yang lebih tinggi dalam aplikasi praktis.
Peningkatan Usaha Kelompok Nelayan di UMKM Rusamin dengan IMS (Integrated Management System) Berbasis Web Codeigniter Tholib, Abu; Furqon, Ainul; Rahman, Taufiqur
TRILOGI: Jurnal Ilmu Teknologi, Kesehatan, dan Humaniora Vol 3, No 3 (2022)
Publisher : Universitas Nurul Jadid

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33650/trilogi.v3i3.5115

Abstract

UMKM konvensional masih terkendala dalam hal promosi dan pemasaran produk, sehingga banyak pembeli yang berada diluar kota masih kurang mengetahui produk apa saja yang diproduksi sehingga omset penjualan tidak meningkat selain itu juga sering terjadi kekeliruan dan kesalahan dalam mencatat transaksi penjualan yang dilakukan yang dapat menyita waktu dalam pembuatan laporannya. Pengelolaan data penjualan juga belum optimal karena belum adanya distribusi data ke masing-masing bagian sehingga sering terjadi ketidakcocokan data antara bagian gudang. metode penelitian yang dilakukan menggunakan data penelitian kualitatif, yaitu penelitian yang dilakukan melalui Observasi dan wawancara di UMKM Rusamin. Hasil  penelitian ini menunjukkan bahwa penggunaan aplikasi  Framework Codeigniter dengan berbasis web di UMKM Rusamin dapat memudahkan pihak manajemen dalam monitoring penjualannya.
MANAJEMEN KLUSTERISASI PASAR: Penerapan Segmentasi Pelanggan Berbasis Metode Self-Organizing Map (SOM) di CV Karunia Probolinggo Tholib, Abu
TRILOGI: Jurnal Ilmu Teknologi, Kesehatan, dan Humaniora Vol 1, No 2 (2020): Manajemen Data Berbasis Teknologi Informasi
Publisher : Universitas Nurul Jadid

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (550.076 KB) | DOI: 10.33650/trilogi.v1i2.1897

Abstract

As one of the distributors engaged in the sale and distribution of cosmetics, CV Karunia is in charge of serving customers who have placed an order, so that each order delivery must be recorded properly. By grouping customers according to regions and orders, it will be easier for distributors to know which regions and whose customers have the largest number of orders. Therefore, CV Karunia must have a customer mapping strategy, for example by using the SOM (Self Organizing Maps) method which aims to facilitate marketing efforts and customer grouping according to customer desires and habits, in order to obtain maximum results. Through this SOM method, customer decision making and optimization of the customer service process can be done well.
Co-Authors Agusmawati, Nanda Kurnia Ahmad Baidowi Eko Fitra Firmanda Ahmad Baidowi Eko Fitra Firmanda Ahmad Halimi Ahmad Hudawi As Ahmad Hudawi AS ahmad taufiqul imam Alfan Maulan Andi, Moh syaiful Basit, Illiyah Ibnul Cahyuni Novia Deddy Junaedi Deniyanto Muchlizin Wahidillah Devita Alif Barmansyah Eka Wahyu Ramadhan Eko Fitra Firmandani, Ahmad Muzakki Eliyanto, Andik Elfandiyono Erna Daniati Fadli Hidayat, M Noer Fadli Hidayat, M. Noer Fathorazi Nur Fajri Fauziah, Gustin Fitwatul Khoiriyah Furqon, Ainul Gulpi Qorik O tagalu .P Guterres, Juvinal Ximenes Hairani Hairani Halimi, Ahmad Hidayat, M. Noer Hudawi AS, Ahmad Ihsan, Gilang Hafidzul Inayatul Maula Itqan, Moh Syadidul Janhasmadja, Mengas Juvinal Ximenes Guterres Juvinal Ximenes Guterres Khoiriyah, Fitwatul Linda Uswatun Hasanah Marzuki, Muhammad Ismail Maula, Inayatul Maulidiansyah, Maulidiansyah Misbahul Munir Moh Ali Ishaq Moh Lailul Ilham Moh Syadidul Itqan Muafi Muafi Muafi Muh Nurul Imam Musfiroh Musfiroh, Musfiroh Nanda Kurnia Agusmawati Qurrotu Aini, Qurrotu Rahman, M Fadhilur Ratri Enggar Pawening Resty Wulanningrum Rian Hidayat Rianto, M. Erfan Rizal Sulton Salman, Moh Setiyo Adi Nugroho Sholeha, Selfia Hafidatus Sholehah, Baitus Shudiq, Wali Ja'far Sihabillah, Ahmad Soleh, Paisal Sukron, Moh Supri yono Supri Yono, Supri Supriadi, Ahmad Syafiih, M Syaroni, Wahab Syaroni, Wahab Taufiqur Rahman, Taufiqur Tsabbit Albannani, Nur Wahyu Virda Virdausih Putri Wahab Syaroni Wahab Syaroni Wali Ja’far Shudiq Warda, Faridatul Wiwin Yuliana Ximenes Guterres, Juvinal Yaqin, Moh. Ainol Yaqin, Moh. Ainol Yaqin Yayat Hidayat Yoga Yuniadi Yuliana, Wiwin Yuri Ariyanto Zain, Ahmad Naufal Waliyus Zainal Arifin Zainal Arifin