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Pungkas Subarkah
Universitas Amikom Purwokerto
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Analisis Sentimen Media Sosial X Terhadap Kenaikkan PPN di Indonesia Menggunakan Algoritme Naïve Bayes dan Support Vector Machine (SVM) Ikhsan, Ali Nur; Pungkas Subarkah; Alifah Dafa Iftinani; Alif Nur Fadilah
Infotekmesin Vol 16 No 1 (2025): Infotekmesin: Januari 2025
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v16i1.2518

Abstract

One of the ways to increase state revenue is by raising the Value-Added Tax (VAT). However, implementing a VAT hike policy often elicits both positive and negative responses from the public. With the presence of social media, people can voice their opinions about government policies, including through social media platform X. This study aims to analyze public sentiment on social media X using the Naïve Bayes and Support Vector Machine (SVM) algorithms. The research compares the highest accuracy results before and after the balancing process. The dataset comprises 2,852 rows in CSV format. The findings indicate that the SVM algorithm achieves an accuracy of 98% before balancing and 97% after balancing, while Naïve Bayes achieves an accuracy of 97% before balancing and 90% after balancing. Overall, both algorithms demonstrate good and balanced performance.
OPTIMIZATION OF CART ALGORITHM BASED ON ANT BE COLONY FEATURE SELECTION FOR STUNTING DIAGNOSIS Subarkah, Pungkas; Ikhsan, Ali Nur; Wahyudi, Rizki; Rofiqoh, Dayana
JURTEKSI (Jurnal Teknologi dan Sistem Informasi) Vol 11, No 2 (2025): Maret 2025
Publisher : Universitas Royal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurteksi.v11i2.3579

Abstract

Abstract: One of the main health problems in children is stunting which is one of the concerns in the Sustainable Development Goals (SDGs). Specifically in Indonesia, the prevalence of stunting in 2024 is 21.6%. This figure is still relatively high, because the target prevalence of stunting is 14%. This study aims to implement machine learning knowledge through the Classification And Regression Trees (CART) algorithm based on Ant Be Colony (ABC) feature selection which aims to determine the increase in accuracy in analyzing stunting datasets. The data used comes from Kaggle which consists of 16500 datasets. The dataset consists of gender, age, birth length, birth weight, body length, body weight, breastfeeding and stunting status. The research methods used are data collection, data preprocessing, classification, and evaluation using K-fold cross validation. The results obtained in this research are the implementation of the CART algorithm obtained a value of 89.86% and the results of CART with Ant Be Colony (ABC) feature selection, which obtained an accuracy value of 93.65%. This shows that there is an increase in the accuracy value in the use of CART algorithm optimization and Ant Be Colony (ABC) feature selection by 3.76%. With the research results that have been obtained, it can be categorized as excellent accuracy value excellent. It is hoped that further research can be carried out by adding other classification algorithms or adding feature selection.            Keywords: classification; feature selection; optimazation; stunting Abstrak: Salah satu masalah kesehatan utama pada anak adalah stunting yang menjadi salah satu perhatian dalam Sustainable Development Goals (SDGs). Khusus di Indonesia angka Pravelensi stunting pada tahun 2024 di angka 21.6%. Angka ini masih tergolong tinggi, karena target angka pravelensi stunting ialah 14%. Penelitian ini bertujuan untuk mengimplementasikan pengetahuan machine learning melalui algoritma Classification And Regression Trees (CART) berbasis seleksi fitur Ant Be Colony (ABC) yang bertujuan untuk mengetahui peningkatan akurasi dalam menganalisis dataset stunting. Data yang digunakan bersumber dari Kaggle yang terdiri dari 16500 dataset. Dataset terdiri dari jenis kelamin, usia, panjang lahir, berat lahir, panjangg badan, berat badan, menyusui dan status stunting.  Metode penelitian yang digunakan adalah pengumpulan data, preprocessing data, klasifikasi, dan evaluasi menggunakan K-fold cross validation. Hasil yang diperoleh pada penelitian ini adalah Implementasi algoritma CART memperoleh nilai sebesar 89,86% dan hasil seleksi fitur CART dengan Ant Be Colony (ABC) memperoleh nilai akurasi sebesar 93,65%. Hal ini menunjukkan adanya peningkatan nilai akurasi pada penggunaan optimasi algoritma CART dan pemilihan fitur Ant Be Colony (ABC) sebesar 3,76%. Dengan hasil penelitian yang telah diperoleh dapat dikategorikan nilai akurasi yang diperoleh sangat baik. Diharapkan dapat dilakukan penelitian selanjutnya dengan menambahkan algoritma klasifikasi lain atau menambahkan seleksi fitur. Kata kunci: klasifikasi; optimalisasi; seleksi fitur; stunting
ANALISIS SENTIMEN PENGGUNA APLIKASI AGODA DI GOOGLE PLAY STORE MENGGUNAKAN ALGORITMA NAIVE BAYES Nuraini , Rema Sekar; Krisbiantoro, Dwi; Imron, Mohammad; Subarkah, Pungkas
Journal of Information System Management (JOISM) Vol. 7 No. 1 (2025): Juni
Publisher : Universitas Amikom Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24076/joism.2025v7i1.2066

Abstract

Kemajuan teknologi telah mendorong digitalisasi di berbagai sektor, termasuk e-commerce yang terus mengalami pertumbuhan pesat, khususnya di Indonesia dengan peningkatan 30,5% pada tahun 2024. Salah satu aplikasi yaiu  Agoda telah diunduh lebih dari 50 juta kali sejak dirilis pada tahun 2011. Penelitian ini bertujuan untuk menganalisis ulasan pengguna aplikasi Agoda di Google Play Store menggunakan algoritma Naïve Bayes. Dari 7885 data ulasan yang dianalisis, ditemukan bahwa pengguna sering mengeluhkan masalah terkait pembatalan, pengembalian dana, proses pemesanan hotel, serta ketidakpuasan terhadap harga dan layanan. Hasil analisis menggunakan algoritma Naïve Bayes menunjukkan akurasi sebesar 91,9% pada skenario pembagian data 60:40 dan 50:50. Hasil ini menunjukkan efektivitas algoritma Naïve Bayes dalam menganalisis ulasan pengguna serta pentingnya pembagian data yang seimbang untuk meningkatkan akurasi model. Penelitian ini memberikan kontribusi dalam mengevaluasi kualitas layanan aplikasi Agoda dan mendukung pengembangan strategi peningkatan layanan melalui analisis data ulasan pengguna.
Literasi Digital Penggunaan Media Sosial Dalam Menangani Cyberbullying Di SD Al Izzah Primandani Arsi; Subarkah, Pungkas; Riyanto, Riyanto; Kusuma, Bagus Adhi; Riandini, Dini; Widi Lestari, Tri Endah; Hermanto, Nandang
Jompa Abdi: Jurnal Pengabdian Masyarakat Vol. 4 No. 2 (2025): Jompa Abdi: Jurnal Pengabdian Masyarakat
Publisher : Yayasan Jompa Research and Development

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57218/jompaabdi.v4i2.1571

Abstract

Kegiatan pengabdian masyarakat ini bertujuan untuk meningkatkan kesadaran dan pemahaman orang tua wali murid SD Al Izzah Purwokerto, Kabupaten Banyumas, terhadap pentingnya media sosial untuk menangani anti cyberbullying, karena saat ini banyak anak-anak atau remaja menjadi korban dan pelaku cyberbullying. Metode yang digunakan dalam kegiatan ini yaitu tahap persiapan, tahap pelaksanaan dan tahap evaluasi. Kegiatan ini diikuti oleh 42 peserta orang tua wali murid, dengan hasil evaluasi mengalami peningkatan secara signifikan. Hal ini dibuktikan dengan adanya pre test dan post test dengan memperoleh hasil mengalami kenaikan 40%. Kegiatan ini direkomendasikan untuk dilanjutkan dengan cakupan permasalahan yang lebih luas dan pelibatan instansi lain. Rekomendasi setelah pelatihan ini yaitu harapannya ada tindak lanjut secara berkala salah satunya kerja sama dengan dinas terkait agar pelatihan sejenis dilaksanakan kembali.
Implementasi Algoritma Dijkstra pada Game Strategi RPG Berbasis Web dengan Framework Javascript P5 Amin, M. Syaiful; Subarkah, Pungkas; Umma, Rofiqul; Prasetya, Eko Budi
Jurnal Ilmiah IT CIDA Vol 8 No 1: Juni 2022
Publisher : STMIK AMIKOM Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55635/jic.v8i1.157

Abstract

Teori graf adalah cabang matematika yang mempelajari graf dari suatu masalah yangmuncul, contoh masalah yang berkaitan dengan teori graf adalah menentukan jarakterpendek dari satu titik ke titik lainnya. Algoritma Dijkstra digunakan untukmenentukan jalur terpendek (Shortest Path Problem) untuk suatu graf. Penulismelakukan beberapa uji coba terkait dengan algoritma yang digunakan. Penulis jugamelakukan studi literatur untuk mengetahui permasalahan yang ada. Pada penelitianini, kami memilih implementasi teori graf pada game strategi RPG yang kami buatdengan algoritma yang digunakan yaitu Algoritma Dijkstra. Dalam penelitian ini, penulismelakukan berbagai tahapan seperti pembuatan konsep, desain tampilan dankomponen, pembuatan game, pengujian, analisis, dan hasil. Hasil dari penelitian iniadalah sebuah game berbasis web yang dibuat dengan menggunakan JavascriptFramework p5 yang mengimplementasikan algoritma Dijkstra sehingga dapatmenentukan rute terpendek menuju target yang telah ditentukan.Kata Kunci: Teori Graf, RPG Game, Algoritma Dijkstra
Implementasi Memory Game di MIT App Inventor Darmayanti, Irma; Ikhsan, Ali Nur; Utami, Dias Ayu Budi; Subarkah, Pungkas
Jurnal Ilmiah IT CIDA Vol 8 No 2: Desember 2022
Publisher : STMIK AMIKOM Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55635/jic.v8i2.165

Abstract

Permainan memori, atau yang kadang-kadang disebut konsentrasi, adalah permainan kartu yang cukup populer dimainkan oleh anak-anak dan orang dewasa di seluruh dunia. Memori yang baik adalah salah satu kualitas yang dibutuhkan untuk berhasil di dalamnya. Permainan  memori dapat membantu perkembangan kognitif anak secara keseluruhan diantaranya membantu anak berkonsentrasi, melatih memori jangka panjang, melatih memori visual, membantu anak berpikir kritis. Dengan pesatnya perkembangan teknologi, yang mana permainan tradisional sudah tidak cukup menarik lagi untuk dimainkan, oleh karena itu pada penelitian ini dibuatlah permainan memory yang dapat dimainkan pada smarthphone dengan sistem operasi android. Model atau metode penelitian yang digunakan adalah metode Prototyping. Model desain prototipe dibuat lebih cepat sehingga waktu yang dibutuhkan untuk pengembangan game lebih singkat. Karakteristik ini sangat sesuai dengan kebutuhan sistem yang ada yang hanya membutuhkan waktu yang singkat dalam pengembangannya. Tools yang akan digunakan peneliti adalah MIT App Inventor untuk membangun sebuah aplikasi Android. Hasil dari penelitian ini diharapkan dapat membuat game mobile berbasis androidyang dapat mengacak gambar dan kartu sehingga dapat mengoptimalkan permainan di game memory.
A Comparison of Welch Powell Algorithm and Greedy Algorithm in Odd Semester Lecture Room Scheduling Optimization Faculty of Computer Science Fadilah, Alif Nur; Subarkah, Pungkas; Pramudya, Reyvaldo Shiva; Syabani, Amin
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 8, No 4 (2024): October
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v8i4.23142

Abstract

Scheduling is a systematic method to optimize work time, and avoid failure when problems occur. Scheduling is widely applied in the world of education, one of which is in preparing course schedules. Scheduling itself needs to be optimized to ensure a smooth lecture process without any problems between courses. As happened at the Faculty of Computer Science, Amikom Purwokerto University, where in the preparation of the schedule there is no information about lecture rooms. Therefore, the author compiled a lecture hall scheduling optimization journal by comparing the performance between the Welch Powell Algorithm and the Greedy Algorithm as optimization and graph coloring on the lecture hall schedule.The data used in this study are 88 courses spread across 3 study programs, namely Informatics Study Program, Information Systems Study Program, and Informatics Engineering Study Program. This research uses a comparative method on graph vertex coloring, where execution time as duration, lines as algorithm complexity, and manual algorithm calculation as parameters. Based on the research that has been done, the results of 14 full spectrum colors are obtained which are then applied to 23 lecture rooms that can be used without clashes at the Faculty of Computer Science. This can minimize the possibility of overlapping room usage between courses. In addition to comparing the performance of the Welch-Powell Algorithm and the Greedy Algorithm to produce optimal scheduling of lecture rooms, this research can also optimize the schedule of lecturers when entering class to optimize students to be more organized in entering lecture classes at the Faculty of Computer Science, Amikom Purwokerto University.
Opinion Mining on Spotify Music App Reviews Using Bidirectional LSTM and BERT Arsi, Primandani; Firmanda, Reza Arief; Prayoga, Iphang; Subarkah, Pungkas
Jurnal Informatika Vol 12, No 2 (2025): October
Publisher : Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/inf.v12i2.25323

Abstract

The increasing number of user reviews on digital music platforms such as Spotify highlights the importance of sentiment analysis to better understand user perceptions. This study aims to develop a sentiment classification model for Spotify user reviews using a Bidirectional Long Short-Term Memory (BiLSTM) approach combined with BERT embeddings. The dataset consists of multilingual user reviews collected from the Google Play Store. Preprocessing steps include text cleaning, tokenization, and padding. BERT is utilized to generate contextual word embeddings, which are then processed by the BiLSTM model to classify sentiments as either positive or negative. The model’s performance is evaluated using a confusion matrix with accuracy, precision, recall, and F1-score metrics. The results show that the BiLSTM-BERT model achieves an F1-score of 0.8852, a recall of 0.9396, a precision of 0.8375, and an accuracy of 0.8374. These findings demonstrate the model’s effectiveness in handling multilingual sentiment analysis tasks, offering valuable insights for developers in enhancing user experience through data-driven decision-making.
A Study Concentration Selection With a C4.5 Algorithm, KNN, and Naive Beyes Busyro, Muhammad; Astuti, Tri; Astrida, Deuis Nur; Arsi, Primandani; Subarkah, Pungkas
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 4 (2025): JUTIF Volume 6, Number 4, Agustus 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.4.4157

Abstract

The course of concentration is a crucial aspect for students at the university amikom purwokerto.This decision doesn't just affect their academic journey., but also determine their readiness in the face of the working world.Various factors that affect the concentration selection, the challenges that students face, as well as solutions to help them choose concentrations that fit their interests and career goals.There are still many students who have been confused in deciding which courses best fit their interests and career goals..This confusion is often caused by a lack of adequate information and proper guidance. This study attempts to analyze the lecture amikom purwokerto concentration of students in the universities of the use of the method c4.5 algorithm 3, k-neareset naighbors and naïve beyes. Academic student data used as the basis analysis to determine the dominance in the lecture concentration.Of the result of the research uses phon 60,24 % decision is, there are using k-neareset naighbors 75.36 % and use naïve beyes 100,00 % there are, the prediction could be the basis for deciding the lecture the concentration by mainstream student.The result is expected to help the university in recommended it to students study concentration related to the election.
Sentiment Analysis Regarding Candidate Presidential 2024 Using Support Vector Machine Backpropagation Based Kisma, Atmaja Jalu Narendra; Arsi, Primandani; Subarkah, Pungkas
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 8, No 1 (2024): January
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v8i1.17294

Abstract

This research has the potential to make an important contribution to the development of computationally-based sentiment analysis, particularly in the political context. Anies Baswedan, Ganjar Pranowo, and Prabowo Subianto, three candidates for the presidency of Indonesia, are examined using a Backpropagation-based Support Vector Machine (SVM) methodology in this study. This approach is used to categorize emotions into three groups: neutral, adverse, and favorable. Between July 1 and July 30, 2023, data on tweets mentioning the three presidential contenders was gathered. After processing the data, SVM was used while lowering the backpropagation process. The study's findings demonstrate that the performance of the model in determining public sentiment is greatly enhanced by the application of backpropagation-based SVM techniques. For each presidential contender, the evaluation was conducted using the f1 score, recall, and precision metrics. The evaluation's findings indicate that while the model struggles to distinguish between favorable and negative feelings toward particular presidential contenders, it performs better when categorizing neutral feelings. The SVM model is more accurately able to identify popular sentiment toward the three presidential candidates when the backpropagation approach is used. The results of the sentiment analysis are also represented by word clouds for each presidential contender, giving an intuitive sense of the words that are frequently used in public discourse. This study sheds light on the possibilities of using Twitter data to analyze political sentiment using the backpropagation-based SVM algorithm. 
Co-Authors A. Kholil Hidayat Abdallah, Muhammad Marshal Abdul Azis Adam Prayogo Kuncoro Adam Prayogo Kuncoro Adam Prayogo Kuncoro Adhimah, Laily Farkhah Aditya Permana, Reza Afifah, Erika Luthfi Akhmad Mustolih Ali Nur Ikhsan Alif Nur Fadilah Alifah Dafa Iftinani Alifian , Raditya Sani Alya Khansa Dzakkiyah Amin, M. Syaiful Amira Aida Rashifa Anggi Tri Dewi Septiani Anggraeni, Eling Sekar Anggraeni, Epri Anggraini, Nova Anshari, Muhammad Rifqi Anunggilarso, Luky Rafi Arbangi Puput Sabaniyah Arief Rachman Hakim Arsi, Primandani Astrida, Deuis Nur Aulia Dian Agustina Aunillah, Puteri Johar Awal Rozaq, Hasri Akbar Awali, Uston Azhar Andika Putra Azhari Shouni Barkah Azizan Nurhakim Azmi, Mohd Sanusi Azzahra, Delia Oktaviana Baehaqi Wahyu Kurniawan Bagus Adhi Kusuma Bagus Adhi Kusuma Baihaqi, Wiga Maulana Bibit Raikhan Azzaki Bryan Jerremia Katiandhago Budi Utami, Dias Ayu Busyro, Muhammad Chendri Irawan Satrio Nugroho Chyntia Raras Ajeng Widiawati Cindy Magnolia Damayanti, Aulia Shafira Tri Damayanti, Wenti Risma Darmo, Cahyo Pambudi Dava Patria Utama Dermawan, Riky Dimas Desi Riyanti Dewi Fortuna Dhanar Intan Surya Saputra Dias Ayu Budi Utami Dias Ayu Budi Utami, Dias Ayu Budi Didit Suhartono Dinar Mustofa Dwi Krisbiantoro, Dwi Dwi Putra, Ruly Niko Elistiana, Khoerotul Melina Enggar Pri Pambudi Fadilah, Alif Nur Fandy Setyo Utomo Faridatun Nida Farizi, Amar Al Fiby Nur Afiana Fiby Nur Afiana Firmanda, Reza Arief Fitriya Maharani, Lulu Amnah Gina Cahya Utami Harun Alrasyid Hellik Hermawan Hendra Marcos Hendra Marcos, Hendra Hidayah, Debby Ummul hidayatulloh, hanif Ika Romadoni Yunita Ikhsan, Ali Nur Ilham, Fatah Iphang Prayoga Irfan Santiko Irma Damayanti Irma Darmayanti Isnaini, Khairunnisak Nur Isnaini, Khairunnisak Nur Jali Suhaman Katiandhago, Bryan Jerremia Khoerida, Nur Isnaeni Khofiyah, Salma Ngarifatul Kholifah Dwi Prasetyo Kartika, Nur Kisma, Atmaja Jalu Narendra Kusuma, Bagus Adhi Kusuma, Velizha Sandy Latifah Adi Triana Lestari, Tri Endah Widi Lestari, Vika Febri Luki Rafi Anuggilarso Maharani Kusuma Dewi Marlita, Reva Ma’ruf, Muhammad Merliani, Nanda Nurisya Mohammad Imron Muflikhatun, Siti Muhammad Marshal Abdallah Muhammad Rifqi Anshari Mustolih, Akhmad Nanda Nurisya Merliani Nandang Hermanto Nandang Hermanto Nasar Ghanim, Nadif Neta Tri Widiawati Nida, Faridatun Nikmah Trinarsih Nur Hidayah, Septi Oktaviani Nur Isnaeni Khoerida Nuraini , Rema Sekar Nurul Hidayati Permana, Reza Aditya Pramudya, Reyvaldo Shiva Prasetya, Eko Budi Prasetyo Kartika, Nur Kholifah Dwi Prastyadi Wibawa Rahayu Prastyadi Wibawa Rahayu Prayoga, Iphang Primandani Arsi Primandani Arsi Pritama, Argiyan Dwi Purba, Mariana Purwadi Ragil Wilujeng Ramadani, Nevita Cahaya Ranggi Praharaningtyas Aji Ratih Anggraeni Ratih Anggraeni Rayinda Maya Anjani Reza Aditya Permana Reza Arief Firmanda Riandini, Dini Riyanto Riyanto Riyanto Riyanto Riyanto Riyanto Riyanto Rizki Sadewo Rizki Wahyudi Rofiqoh, Dayana Rohman, M. Abdul Romadoni, Nova Salma Rosana Fadilla Sari Rujianto Eko Saputro Sabaniyah, Arbangi Puput Sadewo, Rizki Salma Ngarifatul Khofiyah Salsabiela, Ayuni Sandy Kusuma, Velizha Saputra, Dhanar Sari, Rida Purnama Sarmini Sarmini Satrio Nugroho, Chendri Irawan Sekhudin, Sekhudin Septi Oktaviani Nur Hidayah Septi Oktaviani Nur Hidayah Septiana Putri, Refida Sholikhatin, Siti Alvi SITI ALVI SHOLIKHATIN Siti Alvi Solikhatin Siti Alvi Solikhatin Siti Rahayu Selamat Sugiarti Sugiarti Suhaman, Jali Susanto, Wachyu Dwi Syabani, Amin Syamsiar, Syamsiar Tarwoto, Tarwoto Tri Astuti Trian Damai Triana, Latifah Adi Tripustikasari, Eka Tripustikasari Triyo Ginanjar Pamungkas Umma, Rofiqul Utami, Melida Ratna Utomo, Anwar Tri V, Jay Wachyu Dwi Susanto Wahyu, Herta Tri Wanda Fitrianingsih Wenti Risma Damayanti Wenti Risma Damayanti Widiawati, Neta Tri Yofi Yulianto Yuli Purwati Yunita, Ika Romadhoni Yunita, Ika Romadoni