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Anam, M Khairul

Universitas Samudra

Author-ID : 1573830

Religion Aerospace Engineering Humanities Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Physics Public Health Social Sciences Other

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Analisis Pilkada Medan pada Sosial Media Menggunakan Analisis Sentimen dan Social Network Analyisis Anam, M. Khairul; Firdaus, Muhammad Bambang; Fitri, Triyani Arita; Lusiana; Agustin, Wirta; Agustin
The Indonesian Journal of Computer Science Vol. 11 No. 1 (2022): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v11i1.3027

The simultaneous regional head elections were over, but during the campaign until it was decided to become regional head there were many comments, both pro and contra. The city of Medan is one of the regions that will hold the 2020 ELECTION during the pandemic. The Medan City Election has decided that the pair Bobby Nasution and Aulia Rachman have won. This victory certainly gets a variety of comments on social media, especially Twitter. This study conducts sentiment analysis to see the sentiment that occurs, namely seeing negative, positive, or neutral comments. This sentiment analysis uses two methods to see the resulting accuracy, namely Support Vector Machine (SVM) and Naïve Bayes Classifier (NBC). This study also looks at the interactions that occur using Social Network Analysis (SNA). In addition to sentiment analysis and SNA, this study also looks at the existence of BOT accounts used in the #PilkadaMedan. The results obtained from the sentiment analysis show that NBC has the highest accuracy, which is 81, 72% with a data proportion of 90:10. Then on SNA, the @YanHarahap account got the highest nodes, namely 911 nodes. Then from 10326 tweets, 11% were suspected of being BOT by the DroneEmprit Academic system.

Penerapan Metode Support Vector Machine Untuk Analisis Sentimen Terhadap Produk Skincare Jasmarizal; Junadhi; Rahmaddeni; M. Khairul Anam
The Indonesian Journal of Computer Science Vol. 13 No. 1 (2024): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i1.3654

Perawatan kulit telah menjadi aspek yang signifikan dalam pola hidup modern. Kesadaran masyarakat terhadap penampilan dan kesehatan kulit semakin meningkat, mendorong permintaan terus berkembang untuk produk skincare. Konsumen sering menghadapi kesulitan dalam memilih produk yang sesuai dengan jenis kulit mereka, di mana ulasan dari pengguna lain bisa menjadi panduan berharga, namun juga berpotensi menyebabkan kebingungan jika tidak dikelola dengan baik. Mengetahui sentimen konsumen terhadap produk skincare tidak hanya membantu produsen dan pengecer memahami penerimaan produk, tetapi juga memberikan arahan bagi konsumen lain dalam pengambilan keputusan. Kemajuan dalam teknologi analisis sentimen memungkinkan penelitian yang lebih efisien dan akurat terhadap pandangan konsumen mengenai produk skincare. Analisis sentimen dapat dijalankan secara otomatis menggunakan algoritma dan model kecerdasan buatan, di mana Support Vector Machine (SVM) menjadi salah satu metode yang efektif dalam permasalahan klasifikasi. SVM memberikan wawasan mendalam mengenai sentimen yang terkandung dalam ulasan konsumen. Dataset yang digunakan mengandung komentar dan ulasan dari pengguna terkait produk skincare MS Glow, dengan total 3.006 data. Proses selanjutnya melibatkan tahap pre-processing data, yang mencakup langkah-langkah seperti Case Folding, Normalisasi Data, Tokenisasi, Filtrasi Stop Words, dan Stemming. Pada tahap pemodelan, SVM digunakan untuk mengklasifikasi sentimen atau opini pengguna terhadap produk skincare tersebut. Hasil akhir menunjukkan bahwa model dengan ketidakseimbangan kelas mengalami overfitting, di mana performa model optimal hanya pada data pelatihan dan kurang efektif pada data uji. Namun, dengan melatih model menggunakan kelas yang seimbang dan menerapkan teknik SMOTE, ditemukan hasil optimal, mencapai akurasi sebesar 99.60% dan nilai f1-score sebesar 98.55%.

OPTIMALISASI KINERJA KLASIFIKASI TEKS BERDASARKAN ANALISIS BERBASIS ASPEK DAN MODEL HYBRID DEEP LEARING Salsabila Rabbani; Agustin; Susandri; Rahmiati; M. Khairul Anam
The Indonesian Journal of Computer Science Vol. 13 No. 3 (2024): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i3.4034

The conflict between Palestine and Israel has generated strong debates and reactions on social media, including in Indonesia. Public perception of various aspects is certainly important to identify issues in the Palestinian-Israeli conflict. However, the process of manually classifying aspects of the Palestinian-Israeli conflict requires human resources and considerable time. This research aims to explore the views of Indonesians on the Palestinian-Israeli conflict through sentiment analysis based on aspects of Territory, Religion, Politics, and History. Using deep learning technology, specifically a combination model of Convolutional Neural Networks with Long Short-Term Memory (CNN-LSTM), this research analyzes opinion and views data collected from X social media platform (Twitter). This research shows the results of the dataset obtained that the Political aspect dominates more than other aspects. The model evaluation results obtained an accuracy value of 96%, which indicates that the model's ability to classify X users' sentiments towards the Palestinian-Israeli conflict achieved a high level of success.

Comparison of Support Vector Machine and XGBSVM in Analyzing Public Opinion on Covid-19 Vaccination Rahmaddeni, Rahmaddeni; Anam, M. Khairul; Irawan, Yuda; Susanti, Susanti; Jamaris, Muhammad
ILKOM Jurnal Ilmiah Vol 14, No 1 (2022)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v14i1.1090.32-38

The corona virus has become a global pandemic and has spread almost all over the world, including Indonesia. There are many negative impacts caused by the spread of COVID-19 in Indonesia, so the government takes vaccination measures in order to suppress the spread of COVID-19. The public's response to vaccination was quite diverse on Twitter, some were supportive and some were not. The data used in this study came from Twitter which was taken using the drone emprit portal, using the keyword, namely "vaccination". The classification will be carried out using the SVM and hybrid methods between SVM and XGBoost or what is commonly called XGBSVM. The purpose of this study is to provide an overview to the public whether the Covid-19 vaccination actions carried out tend to be positive, neutral or negative opinions. The results of the sentiment evaluation that have been carried out can be seen that SVM has the highest accuracy of 83% with 90:10 data splitting, then XGBSVM produces 79% accuracy with 90:10 data splitting.

Sentiment Analysis for Online Learning using The Lexicon-Based Method and The Support Vector Machine Algorithm Anam, M. Khairul; Fitri, Triyani Arita; Agustin, Agustin; Lusiana, Lusiana; Firdaus, Muhammad Bambang; Nurhuda, Agus Tri
ILKOM Jurnal Ilmiah Vol 15, No 2 (2023)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v15i2.1590.290-302

The pros and cons regarding online learning has been a hot topic in society, both on social media and in the real world. Indonesian netizens still post opinions about online learning on social media such as Twitter. This study aims to analyze public comments to determine whether the trend of the comments is positive, negative, or neutral. The classification of netizen opinions is called sentiment analysis. This study applies 2 ways of carrying out sentiment analysis. The first stage employs the SVM algorithm with data labeling automatically obtained from the Emprit Academy drone portal while the second stage is still using the SVM algorithm but the data labeling with lexicon-based method. The results of this study are comparisons of labels obtained automatically from the Emprit Academy drone portal and labeling using lexicon based. The SVM algorithm obtains an accuracy of 90%, while the use of lexicon-based increases the accuracy value by 5% to 95%. It can be concluded that labeling data using a lexicon-based method can improve the accuracy of the SVM algorithm.

Integrated E-Learning System Development Using Next.js with Anti-Cheating Testing and Payment Integration Eva Yumami; Muhammad Ikhsan Wibowo; Agusviyanda; M. Khairul Anam
Sisfo: Jurnal Ilmiah Sistem Informasi Vol. 10 No. 1 (2026): Sisfo: Jurnal Ilmiah Sistem Informasi, Mei 2026
Publisher : Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/sisfo.v10i1.27066

The advancement of information technology has significantly increased the adoption of e-learning in the educational process. However, many e-learning systems still face limitations, such as the lack of integration between learning management, evaluation systems, and payment features. This study aims to design and implement a web-based e-learning system called NexusLearn that integrates course management, Computer-Based Testing (CBT) with anti-cheating mechanisms, and a payment gateway into a unified platform. The system is developed using the Software Development Life Cycle (SDLC) method, which includes requirement analysis, system design, implementation, and testing. The application is built using the Next.js framework and applies Role-Based Access Control (RBAC) to manage user access based on roles. The results show that the system successfully integrates learning, assessment, and transaction features into a single platform. The CBT module supports dynamic question navigation, real-time timers, automatic answer saving, and anti-cheating mechanisms such as tab-switch detection and automatic submission. The payment feature enables secure and automated transactions through Midtrans integration. Based on Black-box Testing results, all system functionalities operate as intended across key features, including authentication, course management, examination, and payment processing. These findings indicate that the NexusLearn system effectively improves integration, security, and efficiency in e-learning environments and has strong potential for implementation in educational institutions.

Application of Fuzzy Inference System Sugeno Model for Forecasting Antam Gold Prices in Indonesia: A Case Study of Monthly Data 2023–2025 Irwanda Syahputra; Alfa Saleh; Khairul Anam
Sisfo: Jurnal Ilmiah Sistem Informasi Vol. 10 No. 1 (2026): Sisfo: Jurnal Ilmiah Sistem Informasi, Mei 2026
Publisher : Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/sisfo.v10i1.27233

Antam gold prices represent one of the most volatile investment indicators in Indonesia, influenced by macroeconomic factors including rupiah exchange rates, global inflation, and geopolitical uncertainty. The ability to accurately forecast gold prices has become a strategic necessity for investors and market participants. This study applies a Fuzzy Inference System (FIS) with the Sugeno model to forecast Antam gold prices using monthly data from January 2023 to December 2025, comprising 36 data points. The input variables are gold prices from the previous month (t-1) and two months prior (t-2), while the output variable is the predicted price for period t. Data is split 75:25 for training and testing. Evaluation using Mean Absolute Percentage Error (MAPE) yields 2.14%, categorized as excellent accuracy. This study provides empirical evidence that the simple yet interpretable Fuzzy Sugeno method achieves high accuracy in commodity price time series forecasting.

PENGUJIAN USER EXPERIENCE PADA APLIKASI SMART HOME MENGGUNAKAN USE QUESTIONNAIRE Muhammad Bambang Firdaus; Irfan Putra Pratama; Andi Tejawati; M Khairul Anam; Fadli Suandi
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 7 No 1 (2022): Januari
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v7i1.1929

This research was conducted to design an Android-based Smart Home application user interface that is easily understood by users to control the system and test the User Experience on the smart home application design. The data collection methods used were questionnaires, observations, and literature studies. For the system development method using the Linear Sequential Model / Waterfall Model method. Applications used in making designs and smart home applications include Android Studio, Sublime, Xampp, Adobe Xd, and Adobe Illustrator. The testing methods used include Usability testing and Usability Measurement using the USE Quistionnaire. This research produces a Smart Home application design that can be used by users to easily control the system.

MOBILE GAME EDUKASI PAUD SEBAGAI MEDIA PENGENALAN DENGAN TEKNIK SPEECH RECOGNITION Nurjayadi Nurjayadi; Indah Mukhlis Tamara; M. Khairul Anam; Muhammad Bambang Firdaus; Hamdani Hamdani
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 7 No 2 (2022): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v7i2.2431

Pembelajar anak usia dini lebih suka belajar melalui bermain. Namun, ketika Covid-19 menyebar, proses belajar mengajar sangat dibatasi. Akibatnya anak kecil lebih banyak menghabiskan waktunya untuk bermain daripada belajar, dan mereka disibukkan dengan ponsel atau smartphone mereka, terlepas dari teman mereka, yang membuat mereka malas untuk belajar. Pendidikan usia dini anak memiliki enam tujuan: norma agama dan moral, pengembangan keterampilan fisik dan motorik, pengembangan kognitif, pengembangan sosial-emosional, pengembangan bahasa, dan pengembangan artistik. Belajar sambil bermain adalah cara yang bagus untuk menggunakan teknologi sebagai media pembelajaran di masa pandemi ini. Membuat belajar lebih mudah bagi anak-anak melalui Android dan teknik Speech Recognition (perintah suara) membuat belajar menjadi menyenangkan bagi anak-anak! Dalam metode waterfall, kerja suatu sistem dilakukan secara berurutan atau linier. Dengan bantuan aplikasi game edukasi ini, anak-anak akan belajar bagaimana berkomunikasi dan memperluas wawasan mereka ketika belajar atau menjawab pertanyaan di kemudian hari. Berbagai materi akan disajikan dalam game ini untuk membantu mengenalkan siswa pada huruf arab, angka, dan hijaiyyah. Ini adalah alat yang sangat baik untuk dimiliki oleh orang tua atau guru PAUD.

APLIKASI ABSENSI KERJA LEMBUR KARYAWAN BERBASIS CLOUD COMPUTING SEBAGAI SOFTWARE AS A SERVICE (SAAS) Martilinda Panjaitan; Agustin Agustin; Herwin Herwin; M. Khairul Anam
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 8 No 1 (2023): Januari
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v8i1.2964

Rista Lamtama Engineering is a Riau Andalan Pulp and Paper contractor company engaged in project services. Consisting of 136 employees, the processing of overtime attendance data for the company Rista Lamtama Engineering is still carried out conventionally, namely recapping the overtime attendance data one by one and then processing it using Microsoft Excel. This method is not efficient and effective in terms of time and effort. Employees who work overtime in the field experience difficulties in attending to the office. An attendance system like this creates fraud when filling in attendance in the form of entrusted absences, even though they don't come overtime, causing misunderstandings between employees and the office and can be detrimental to PT. Overcoming this problem, an attendance application was created by utilizing cloud computing with software as a service (SaaS) services. The existence of cloud computing technology allows data access from anywhere and using a fixed or mobile device. The system built can help the company Rista Lamtama Engineering in managing employee overtime data, a system created using cloud computing is also more effective in storing data on employees who work overtime and reduces employee fraud in absenteeism overtime because of the location when employees attend attendance can be seen. The system built for Android Studio-based employee overtime attendance applications. All available features are running well and judging from the tests that have been carried out with compatibility testing, blackbox testing,and usability testing, it can be concluded that the system built has met the needs of employees of PT. Rista Lamtama Engineering, for its own cloud computing, utilizes the firebase database firestore where all employee data that has performed overtime attendance has been successfully stored in the firebase database firestore.

Co-Authors -, Tashid Abrar Hadi Ade Riyanda Putra Adi Surya Darma Agustin Agustin Agustin Agustin Agustin Agusviyanda Agusviyanda Agusviyanda Ahmad Ihsan Ahmad Tantoni Ahmad Zamsuri Ahmad Zamsuri, Ahmad Aisum Aliyah Sari Akram, Rizalul Al Amin Fadillah Sani Alfa Saleh Alfisyahrin Alfisyahrin Alkadri Masnur Ambiyar, Ambiyar Andesa, Khusaeri Andi Supriadi Chan, Andi Supriadi Anwar, Reksi Aprillian Kartino Arba, Muhammad Hendra Arda Yunianta Arda Yunianta Arief Hidayat Arita Fitri, Triyani Arsyah, Ulya Ilhami Atalya Kurnia Sari Atmaja, Teuku Hadi Wibowo Ayu Mahessya, Raja Bambang Kurniawan Br.Situmorang, Elisabet Sinta Romaito Budiman, Edy Budiman, Edy Bunga Nanti Pikir Bunga Nanti Pikir Chatarina Umbul Wahyuni Cut, Banta Damar Sanggara Habibie Daryanto, Diki Dea Safitri Dedy Irfan Devi Yuliana Dewi Sari Wahyuni Dewi Sari Wahyuni Didik Sudyana Didik Sudyana Diki Daryanto Diky Daryanto Eddy Kurniawan Pradana Efrizoni, Lusiana Emerlada, Esi Tri Erlin Erlin Erlinda, Susi Ersan Fadrial, Yogi Esi Tri Emerlada Fadli Suandi Fahrul Yamani Fajar Arifandi Fajrizal Fatdha, T.Sy. Eiva Faza Alameka Fernando Elda Pati Fika Felanda Ardelia Firdaus, Muhammad Bambang Fransiskus Zoromi Fransiskus Zoromi Fransiskus Zoromi Fransiskus Zoromi, Fransiskus Fryonanda, Harfebi Gendhy Dwi Harlyan Gubtha Mahendra Putra Gunadi Gunawan, Chichi Rizka Habibi Ulayya Hadi Asnal, Hadi Hairah, Ummul Hamdani Hamdani Hamdani - Hamdani . Hamdani Hamdani Hamdani Hamdani Hamdani Hamdani Hanif Aulia Happy Yugo Prasetiya Haris Kurniawan, Haris Hasan J. Alyamani Haviluddin Haviluddin Hazira, Nadila Helda Yeni Helda Yenni Helda Yenni, Helda Hendra Saputra Hendrawan, Riki hendri, nofri Herianto Herianto Herwin Herwin Herwin Herwin, Herwin Ike Yunia Pasa Ikhsan Ikhsan Imam Andhika Indah Mukhlis Tamara Indra Prayogo Indra Prayogo Indri Febrianti Irfan Putra Pratama Irfansyah Irfansyah Irsyad, Akhmad Irwanda Syahputra Irwanda Syahputra Irzal Arif Wisky Istianah Istianah Jamaris, Muhamad Jamaris, Muhammad Jasmarizal Jetno Harja Junadhi Junadhi Junadhi Junadhi Junadhi, Junadhi Kadek Mirnawati Karfindo, Karfindo Karpen Karpen Kartina Diah K. W. Kharisma Rahayu Khusaeri Andesa Khusaeri Andesa Kresnapati, I Nyoman Bagus Aji Kudadiri, Parlindungan Lathifah Lathifah Lathifah Lathifah Lathifah Lathifah Lathifah Lathifah Lathifah, Lathifah Latifah Liza Fitria Lucky Lhaura Van FC Lucky Lhaura Van FC, Lucky Lhaura Lusiana Lusiana Efrizoni Lusiana Efrizoni Lusiana Lusiana M Syauqi Hafizh M. Ikhsan Wibowo Machdalena Mahamad, Abd Kadir Mahendra, Muhammad Ihza Mardainis Mardainis Mardainis Martilinda Panjaitan Mega Susanti Mega Susanti Melda Royani Michal Dennis Michel Kasaf Mi`rajul Rifqi Mohamad, Nur Ikhwan Bin Muhaimin, Abdi Muhamad Jamaris Muhamad Sadar Muhamad Sadar, Muhamad Muhammad Bambang F Muhammad Bambang Firdaus Muhammad Bambang Firdaus Muhammad Bambang Firdaus Muhammad Budi Saputra muhammad Fuad Muhammad Ikhsan Wibowo Muhammad Nur Ihwan Muhammad Wisdan Pratama Putra Muhammad Yusuf Halim Munawir Munawir Munawir Munawir Munawir Mutiana Pratiwi N.A, Randi Nadila Rahmadhani Nadya Alinda Rahmi Nadya Satya Handayani Nanda, Novianda Nanda Nariza Wanti Wulan Sari Nasrul Sani Neci Nirwanda Nisa, Aida Nora Lizarti Novi Yona Sidratul Munti Novia Arista Nu'man, Nu'man Nurhuda, Agus Tri Nurjayadi Nurjayadi Nurjayadi Nurjayadi Nurul Fadillah Nurul fadillah, Nurul Nurul Indriani Nurwijayanti Pandu Pratama Putra, Pandu Pratama Paradila, Dinda Parlindungan Kudadiri Permana, Randy Pradipta , Rahman Pranata, Angga Purwanto Putra, Ryanda Satria Rahmaddeni Rahmaddeni Rahmaddeni Rahmaddeni Rahmi, Nadya Alinda Rahmiati Rahmiati Rahmiati Rebecca La Volla Nyoto Refni Wahyuni Reksi Anwar Rini Yanti Rini Yanti Rini Yanti Rinno Hendika Putra Rio Andika Malik Rivaldi Dwi Andhika Rohana Yola Parastika Hutasoit Rohmat Romadhoni Rometdo Muzawi Ruri Hartika Zain Saiful Bukhori Saiyaratul Mawaddah Salsabila Rabbani Salsabila Rabbani Saon, Sharifah Saputra, Eko Ikhwan Sari Irma Yani Sitorus Sari, Atalya Kurnia Sarjon Defit Silvyana Dwi Putri Sofiansyah Fadli Sofiansyah Fadli Soni Sovia, Rini suaidah suaidah Sumijan Sumijan Susandri, Susandri Susanti Susanti Susanti Susanti Susanti Susanti Susanti, Mega Susanti, Susanti SUSI ERLINDA Susi Erlinda Susi Erlinda Syam, Salmaini Safitri Syamsiar, Syamsiar T. Sy. Eiva Fatdha Taruk, Medi Tashid Tashid Tashid Tatang Hidayat Taufik Taufik Tejawati, Andi Tengku Alvin Firdaus Teri Ade Putra Tjut Rizqi Maysyarah Hadi TM Rezaka Alfitra Torkis Nasution Tri Putri Lestari Tri Putri Lestari Tri Putri Lestari Tri Putri Lestari Tri Putri Lestari, Tri Putri Triyani Arita Fitri Ulfah, Aniq Noviciate Wahyudianto, Mochamad Rizky Waksito, Alan Zulfikar Waskita, Ghozi Indra Wifra, Rizki Wirta Agustin Wirta Agustin Yaakub, Saleh Yansyah Saputra Wijaya Yenni, Heda Yesaya Twin Situmorang Yesri Elva Yogi Ersan Fadrial Yogi Yunefri, Yogi Yoyon Efendi Yuda Irawan Yudhistira, Dewangga Yumami, Eva Zainal Arifin Zeki Kurniadi zeki Kurniadi Zupri Henra Hartomi

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