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All Journal Jurnal Teknologi Informasi dan Ilmu Komputer El-Mujtama: Jurnal Pengabdian Masyarakat
Nana Ramadijanti, Nana
Teknologi Informasi, Politeknik Elektronika Negeri Surabaya (PENS) – ITS Jl. Raya ITS, Keputih-Sukolilo, Surabaya, 60111. Telp. +62-31-5947280
Religion Computer Science & IT Economics, Econometrics & Finance Education Engineering Languange, Linguistic, Communication & Media Social Sciences

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Strategi Penanganan Imbalance Class Pada Model Klasifikasi Penerima Kartu Indonesia Pintar Kuliah Berbasis Neural Network Menggunakan Kombinasi SMOTE dan ENN Darojah, Zaqiatud; Susetyoko, Ronny; Ramadijanti, Nana
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 10 No 2: April 2023
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.20236480

Abstract

Keterbatasan kuota penerima program Kartu Indonesia Pintar Kuliah (KIP Kuliah) dari pemerintah mengharuskan Perguruan Tinggi (PT) menyeleksi dengan cermat calon mahasiswa yang berhak menerima program tersebut. Pembentukan model klasifikasi penerima program KIP Kuliah merupakan salah satu cara yang dapat membantu PT dalam menyeleksi calon mahasiswa agar tepat sasaran berdasarkan data lampau. Penelitian ini bertujuan untuk membentuk model klasifikasi penerima KIP Kuliah menggunakan Neural Network (NN).  Strategi data processing level digunakan untuk mengatasi ketidakseimbangan data atau imbalance class yang terjadi antara kelas penerima KIP Kuliah sebagai kelas minoritas dan kelas bukan penerima KIP Kuliah sebagai kelas mayoritas. Teknik yang digunakan pada penelitian ini adalah mengkombinaskan metode oversampling Syntetic Minority Oversampling Technique (SMOTE), metode undersampling Edited Nearest Neighbor Rule (ENN),  dan metode undersampling dengan penghapusan langsung pada sampel terpilih. Skema penggabungan dilakukan dengan cara mengelompokkan terlebih dahulu kelas mayoritas menjadi beberapa sub kelas (cluster) menggunakan algoritma k-means. Metode SMOTE dan ENN diterapkan secara bersamaan menggunakan rasio sampling tertentu pada dataset yang berasal dari kelas minoritas dan sub kelas mayoritas yang merupakan tetangga terdekat kelas minoritas tersebut. Metode penghapusan sampel diterapkan pada sub kelas mayoritas yang memiliki jarak yang sangat signifikan dari kelas minoritas. Tujuan dari skema yang diajukan adalah untuk meminimalkan terjadinya pembangkitan false sample pada kelas minoritas dan penghapusan sampel informatif pada kelas mayoritas. Hasil simulasi menunjukkan bahwa kombinasi teknik undersampling dan oversampling dengan skema yang diusulkan mampu meningkatkan kinerja model klasifikasi NN secara signifikan. Model klasifikasi terbaik menghasilkan  nilai accuracy sebesar 93.45%,  TPR sebesar 90,00%, TNR sebesar 93.67%, G-Mean sebesar 91,51%, dan nMCC sebesar 81.25%.  Abstract  The limited quota for recipients of the Kartu Indonesia Pintar Kuliah (KIP Kuliah) program requires the university to select carefully the students who are entitled to receive the program. This study aims to build the classification model for KIP Kuliah recipients using Neural Network (NN) which can be utilized by universities in selecting prospective KIP Kuliah recipients students. To solve the imbalanced KIP Kuliah recipients data, we propose a hybrid sampling technique that combines the Synthetic Minority Over-Sampling Technique (SMOTE) and the Edited Nearest Neighbor (ENN) and also samples selected deletion method with a new scheme. Firstly, the majority class is clustered into several sub-classes using the k-means algorithm.  The SMOTE and ENN methods are applied simultaneously on a dataset derived from a minority class and a majority sub-class that is the nearest neighbor of the minority class with a certain sampling ratio. Furthermore, the sample-selected deletion method is applied to the majority sub-classes that have a very significant distance from the minority class. Lastly, The resampling results of the proposed scheme are combined into one training dataset in ANN. The objective of the proposed scheme is to minimize the generation of ‘false samples’ in the minority class and the elimination of informative samples in the majority class. The results show that the proposed scheme can significantly improve the performance of the NN classification model. The best classification model produces an accuracy value of 93.45%, TPR of 90.00%, TNR of 93.67%, G-Mean of 91.51%, and MCC of 81.25%.
Penerapan Aplikasi Klasifikasi Hukum Tajwid Menggunakan Image Processing Kindarya, Fabyan; Kusumaningtyas, Entin Martiana; Barakbah, Aliridho; Permatasari, Desy Intan; Al Rasyid, M. Udin Harun; Ramadijanti, Nana; Fariza, Arna; Syarif, Iwan; Sa'adah, Umi; Saputra, Ferry Astika; Ahsan, Ahmad Syauqi; Sumarsono, Irwan; Yunanto, Andhik Ampuh; Edelani, Renovita; Primajaya, Grezio Arifiyan; Kusuma, Selvia Ferdiana
El-Mujtama: Jurnal Pengabdian Masyarakat  Vol. 4 No. 2 (2024): El-Mujtama: Jurnal Pengabdian Masyarakat
Publisher : Intitut Agama Islam Nasional Laa Roiba Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47467/elmujtama.v4i2.1930

Abstract

Tajwid is an important science that regulates the way of reading the verses of the Al-Qur’an properly. Learning Tajwid means knowing the meaning that corresponds to the correct recitation. Learning to read the Al-Qur’an tends to be done traditionally in a place of learning or by calling a teacher to the house. Learning in this way has some drawbacks, such as the limited availability of trained and competent teachers because not all areas have sufficient access to these teachers. Dependence on schedules and locations can be a constraint for students with limited mobility or busy schedules. The role of the teacher is still important in learning tajwid, especially in providing effective explanations, guidance, and feedback. However, to overcome these shortcomings, integration with independent and technology-based learning methods can help improve the accessibility, flexibility, and quality of tajwid learning. The classification of tajwid laws using image processing allows users to see the results of inputting images of verses of the Al-Qur’an into the type of detected nun sukun tajwid and how to recite it. The initial stage of this system in detecting tajwid laws from uploaded images is the input of images by users, which can be done in two ways, namely by directly taking pictures using a smartphone camera or uploading images from the gallery. This is followed by the OCR process to detect the Arabic text contained in the image and provide diacritics for that Arabic text. Finally, letter classification is carried out after nun sukun and classification of tajwid laws contained in accordance with the detected letters after nun sukun. This system has an accuracy rate of 92.18% from the classification results that have been carried out.
Implementasi Sistem Antrian Online dan On-site di Kelurahan Gebang Putih Surabaya untuk Meningkatkan Efisiensi Layanan Publik Aziz, Adam Shidqul; Mubtadai, Nur Rosyid; Permatasari, Desy Intan; Saputra, Ferry Astika; Syarif, Iwan; Fariza, Arna; Al Rasyid, M. Udin Harun; Kusuma, Selvia Ferdiana; Sumarsono, Irwan; Ahsan, Ahmad Syauqi; Sa'adah, Umi; Yunanto, Andhik Ampuh; Primajaya, Grezio Arifiyan; Edelani, Renovita; Ramadijanti, Nana; Khoirunnisa, Asy Syaffa; Alfaqih, Wildan Maulana Akbar; Al Falah, Adam Ghazy
El-Mujtama: Jurnal Pengabdian Masyarakat  Vol. 5 No. 2 (2025): El-Mujtama: Jurnal Pengabdian Masyarakat
Publisher : Intitut Agama Islam Nasional Laa Roiba Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47467/elmujtama.v5i2.6239

Abstract

Digitalization is an important step in improving the efficiency of public services, particularly in managing queues in government institutions such as sub-district offices. Kelurahan Gebang Putih Surabaya faces significant challenges in managing its manual queue system, which often results in discomfort for the public due to long waiting times, exceeding 5 minutes. This reduces public satisfaction and causes inefficiencies in the queue process. To address this issue, this study aims to develop and implement a digital queue system that can be accessed both online and on-site, using the User-Centered Design (UCD) approach. This approach ensures that every aspect of the system's design and development focuses on user needs through an iterative process, where the design is adjusted based on direct feedback from users. The proposed solution in this study includes the creation of a mobile and website-based queue system, allowing the public to easily take a queue number online and also enabling quick on-site queueing with a wait time of less than 10 seconds. Another advantage of this system is its automated reporting feature, which facilitates documentation and queue reports, thereby accelerating administration and monitoring to the city government. The results show that the implementation of this system significantly reduces the queue-taking time from over 5 minutes to less than 10 seconds, successfully transforming the manual system into a more efficient digital system, and streamlining the reporting process to the government, which in turn improves the quality and satisfaction of public services.
Co-Authors Ahsan, Ahmad Syauqi Al Falah, Adam Ghazy Alfaqih, Wildan Maulana Akbar Ali Ridho Barakbah Andhik Ampuh Yunanto Arna Fariza Aziz, Adam Shidqul Darojah, Zaqiatud Desy Intan Permatasari, Desy Intan Edelani, Renovita Entin Martiana Kusumaningtyas Ferry Astika Saputra iwan Syarif Khoirunnisa, Asy Syaffa Kindarya, Fabyan Kusuma, Selvia Ferdiana M Udin Harun Al Rasyid, M Udin Harun Nur Rosyid Mubtadai, Nur Rosyid Primajaya, Grezio Arifiyan Sa'adah, Umi Sumarsono, Irwan Susetyoko, Ronny