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Iqbal Maulana
Jurusan Teknik Sipil FT. UNDIP Jl. Prof. H. Soedarto SH., Tembalang, Semarang 50275
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Analisis Sentimen Masyarakat Pada Twitter Terhadap Debt Collector Menggunakan Metode Naive Bayes Classifier Pratama, Rizqy Arya; Maulana, Iqbal; Komarudin, Oman
Jurnal Ilmiah Wahana Pendidikan Vol 10 No 7 (2024): Jurnal Ilmiah Wahana Pendidikan
Publisher : Peneliti.net

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.11201354

Abstract

Currently, many people need cash loans. Sourced from the results of the Financial Services Authority (OJK) report, the amount of online loan distribution has reached IDR 18.73 trillion throughout 2022. Debt collectors are present to collect for people who are unable to pay off the loans that have been submitted. Even so, the performance of debt collectors has experienced a lot of criticism from the public, the performance of debt collectors is often discussed on social media twitter. Therefore, it is necessary to analyze the issue of debt collectors on twitter to see public opinion about the practice of debt collectors themselves. The data used in this study amounted to 600 data. Data labeling uses Indonesian linguists as validators to determine the sentiment class. In the preprocessing stage the data is cleaned to reduce attributes that have little effect on the classification process. The highest accuracy result obtained using Naive Bayes Classifier and TF-IDF is 78.3% with a data percentage of 90:10 (90% training data and 10% test data). For the highest precision value obtained from testing with the use of 90:10 data using Naive Bayes Classifier with the BoW method, which is 80%. While the highest recall value is obtained from testing with the use of 90:10 data using the BoW method which is 80%. The use of BoW succeeded in increasing the accuracy value in most of the data sharing scenarios in the test. The classification process produces the most frequently occurring words in each sentiment class visualized with word clouds and fishbone diagrams. The word "chase" is the most dominant word in negative tweet data, while the word "help" is the most dominant in positive tweet data against debt collectors on twitter. The depiction using the fishbone diagram provides a solution to the negative opinions and experiences of the public towards debt collectors, one of which is the use of harsh words which can be overcome by conducting training for all team members on communication ethics.
Pengkategorian Penilaian Uji Laik Fungsi Jalan Ditinjau Dari Aspek Keselamatan Sahri, Agus; Maulana, Iqbal
Jurnal Keselamatan Transportasi Jalan (Indonesian Journal of Road Safety) Vol. 5 No. 2 (2018): JURNAL KESELAMATAN TRANSPORTASI JALAN (INDONESIAN JOURNAL OF ROAD SAFETY)
Publisher : Pusat Penelitian dan Pengabdian Masyarakat (P3M)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46447/ktj.v5i2.52

Abstract

Salah satu tujuan penyelenggaraan uji laik fungsi jalan yaitu memberikan keselamatan bagipengguna jalan. Jalan sudah memenuhi standar teknis jalan masih belum dapatmemberikan keselamatan bagi para pengguna jalan. Hal inilah yang menjadi tolak ukurkeberhasilan uji laik fungsi jalan. Dengan dukungan data kecelakaan lalu lintas dapatdiidentifikasi lokasi rawan kecelakaan. Ruang lingkup dari penelitian ini adalah ruas jalandengan status fungsi jalan arteri sekunder di Kota Yogyakarta. Pada penelitian ini bertujuanmengkategorikan hasil uji laik fungsi jalan ditinjau dari aspek keselamatan. Dari hasilpenelitian dapat disimpulkan bahwa suatu jalan dilakukan uji korelasi antara uji laik fungsijalan dan lokasi rawan kecelakaan memiliki nilai sig2 tailed 0,727 dapat disimpulkan bahwaantara dua variabel memiliki hubungan yang semakin kuat. Dengan cara pemberianstarrating dan menentukan tingkat resiko/Risk Level dari penurunan kinerja jalan dapatmembantu untuk prioritas penanganan/rekomendasi.
Klasterisasi Gaya Belajar Mahasiswa Berbasis VARK dengan Algoritma DBSCAN untuk Personalisasi E-Learning Maulana, Iqbal; Witanti, Wina; Melina
Jurnal Algoritma Vol 22 No 2 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-2.2980

Abstract

The incompatibility between e-learning systems and students' learning styles remains a major challenge in improving the effectiveness of learning in Indonesian universities. This study aims to classify the learning styles of students at Jenderal Achmad Yani University using the VARK (Visual, Auditory, Read/Write, Kinesthetic) model, enriched with the Kano method. Data were collected from 1,000 students through the VARK-Kano questionnaire and analyzed using the DBSCAN (Density-Based Spatial Clustering of Applications with Noise) algorithm. The clustering process was carried out by determining the optimal parameters using the k-distance plot, and the validity of the clusters was assessed using the Silhouette Score. The results showed that DBSCAN could form representative clusters of student learning styles and effectively detect data noise. This study contributed to the development of a cluster-based adaptive e-learning framework that could be implemented in Indonesian universities. These findings could serve as a basis for designing adaptive learning strategies that are more suited to student characteristics, thereby increasing the effectiveness of e-learning and learning motivation.
Co-Authors Abhinaya, Reswara Faza ade, Nofri Affandi, Felix Rafiansyah Afrilian, Mochammad Agim, Agim Agustin, Heny Ainun Safitri Airin Liemanto Akbar, Muhibudin Aldair, Muhammad Diva Alfian, Iqbal Amaliyah, Cinta Ayu Aminuddin Irfani, Aminuddin Ammellia Putri, Zahra Amrih, Dewi Andi Rosa Andni, Riyan Anggellica, Silviana Apriade Voutama Ariana Salsabila, Nazwa Aries Suharso Arif Prambudiarto, Benny Arifin Pahlawan, Ilham Astuti, Elsi Athariq, Fajar Aulia, Nazi Ratul Ayu E., Chinta Kartika Ayunaning, Kholidia Bahary, Achmad Rizal Basri, Ahmad Hasanul Betha Nurina Sari Briliyanti, Rahma Dita Budi Arif Dermawan Budiarti, Puspita Daud, Azzam Hasan Dewi Nurhanifah, Dewi Dikriyah Dwi Agustiar, Fajar Dwi Ely Kurniawan E Haodudin Nurkifli Edi Sofyan, Edi Elfrida Ratnawati Enri, Ultach Erwin Erwin FADLI, MOH Fajar Alamsyah, Indra Farah Putri Wenang Lusianingrum Fauzan . Fauzan, Miftahul Febrianti, Amanda Fifa Latifah, Umi Finisica Dwijayati Patrikha Fiqri Faturrian, Muhammad Firdausiah, Salsabila Firmansyah, Faiz Agil Fitri Kurniawati Fitriana Fitriana Gantara, Gerald Dewa garno, Garno Ghiffari, Ahmad Tsaqief Ghufron, Khairul Hanifah, Ayu Nur’aliyah Herlinda Herlinda, Herlinda Herlindah, Herlindah Hidayat Intan Purnamasari Iqron Muhammad, Seno Irwani Irwani Ismawati, Iis Ismiasih, Ismiasih Iwan Permadi Izzati, Nuril Khoirunisa Jaman, Jajam Haerul Jannah, Erana Misbahul Jauharoh, Arini Julaiha, Juli Karimuddin, Karimuddin Kholilur Rahman, Moh. Nur Khowwas, Aliyul Komarudin, Oman Kurnia Abdullah, Kunaifi Kurniawan, Syukri Lejap, Theodorus Yoseph Tatabuang Lestari, Arfena Deah Lubis, Zulfahmi Luthfi, Amar Marlinda, Gusta Marpaung, Willi Rahim Maulana, Asyifa Mayasari, Rini Medianti, Vebyola Dwi Meirany, Jasisca Mela Sandra Melina Miftahussalamah, Dwi Moh. Jufriyanto Mohammad Al Farabi, Mohammad Mufid, Tsaqif Mu'tashim Muhammad Indrawan Jatmika Muhammad Jafar, Muhammad Muhammad Manaqib, Muhammad Muhammad Syawal Karo-Karo Mukhlidin Mukholad Fauzi, Wildan Mumtaz Muizza, Muhammad Ahmad Muslikhun, Alfin Norkhaliza, Fitria Novalia, Elfina Nugraha, Ihsan Satya Adi Nugroho, Trio Nur Qomariyah Nur, Asrul Ibrahim Nurina Sari, Betha Onny Medaline Padilah, Tesa Nur Pamungkas, Mochammad Fitra perkasa, surya rimba Permata Ningtyas, Alviani Hesthi Permatasari, Ismi Aprilianti Pradipta, Aditya Arya Pramudya, Aditya Pratama, Elvin Alan Pratama, Rizqy Arya Prawira Buana, Andika Primaya, Aji Purwantoro Putri, Windy Anissa Amilia Rahman, Sufirman Rahmanto, Ludi Rahmayani, Fenny Ramadhan, Bintang Zulfikar Riliandhita, Riliandhita Riza Ibnu Adam, Riza Ibnu Rizal, Adhi Rohman, Ahmad Maulana Rowiyani Rozi, Achmad Safitri, Tiara Sahri, Agus Salminawati Sentot Purboseno Setiabudi, David Wahyu Shah, Akmal Sholeh, Khoerul Shonaliya, Indra Putra Siti Halimah Siti Halimah Sri Redjeki Sulistiyowati, Anjar Sundari, Ariefah Supriyadi Supriyadi Susanto, Santo Susilo Yuda Irawan, Agung Syafiih, M Syamsiar, Syamsiar Syarif Abdullah Syarifah, Atika Nur Syawal Karo-Karo, Muhammad Syukri Kurniawan Nasution Umaidah, Yuyun Vincent, Roland Wati, Helmalia Wina Witanti Wiyono, Slamet Wulandari, Adinda Yopi Hutomo Bhakti Yusuf Rismanda Gaja, Muhammad Yusup, Dadang ZAHWA, ST Zaini Dahlan Zidane, M Yazid