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Anam, M Khairul

Universitas Samudra

Author-ID : 1573830

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DESIGN THINKING APPROACH FOR OPTIMIZING TRANSACTION IN ANDROID-BASED CAMPUS CANTEENS M. Khairul Anam; Parlindungan Kudadiri; Hamdani Hamdani; Triyani Arita Fitri; Fransiskus Zoromi
Jurnal Sistem Informasi dan Informatika (Simika) Vol. 7 No. 2 (2024): Jurnal Sistem Informasi dan Informatika (Simika)
Publisher : Program Studi Sistem Informasi, Universitas Banten Jaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47080/simika.v7i2.3357

Android is extensively used by some startups for food ordering applications, such as go food, grab food, Shopee food applications. However, the application cannot be used in a small scope such as the canteen on campus. At STMIK Amik Riau, the existing canteens still use manual methods in ordering and payment, therefore to facilitate canteen transactions, innovation was carried out, namely by using the e-canteen application. This application was created to make it easier to order menus, find out what menus are on that day and to prevent purchases without making payments. The e-canteen application had several features such as the name of the canteen, selection of available menus, menu prices, and payment processing. The making of e-canteen used a design Thinking approach. Design Thinking is a creative approach that collects ideas directly from application users. Design thinking has several stages, such as: empathize, define, ideate, prototype and test. The testing process showed how the target users interacted with the prototype that had been created. The results obtained from this study demonstrated that the e-canteen application significantly facilitated canteen services by simplifying the ordering and payment processes. Specifically, users were able to place orders more efficiently and complete payments seamlessly, which improved overall user satisfaction and operational efficiency within the campus canteen.

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.

Implementation of a Medicine Distribution System to Determine Health Assistance Priorities for Flood-Affected Communities in Aceh Tamiang M. Khairul Anam; Tjut Rizqi Maysyarah Hadi; Michel Kasaf; Agusviyanda; M. Ikhsan Wibowo
JURIBMAS : Jurnal Hasil Pengabdian Masyarakat Vol 5 No 1 (2026): Juli 2026
Publisher : LKP KARYA PRIMA KURSUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62712/juribmas.v5i1.979

Flooding in Kasih Sayang Village, Manyak Payed District, Aceh Tamiang Regency created challenges in the distribution of health assistance, particularly in data collection, prioritizing recipients, and recording medicine distribution. This community service activity aimed to implement a medicine distribution system to support the prioritization of health assistance for flood-affected communities. The methods used included initial visits, observation, interviews, questionnaires, program implementation, and partner response evaluation. The program was carried out through the symbolic handover of medicines and medical equipment to the village midwife and village head, followed by a trial of the medicine distribution application with partners. The results showed that the application could be used properly by partners and helped make recipient data management more organized, faster, and systematic. The evaluation involving the village head, village officials, and village midwife showed an average score of 3.72, which was categorized as very high. The highest score was found in the need for a system to determine aid recipient priorities at 3.90, followed by the urgency of post-flood health assistance at 3.85. Overall, this program provided practical benefits in supporting a more orderly, transparent, and accountable management of health assistance at the village level.

Pendidikan Darurat dan Pemulihan Psikososial Anak Pascabencana Banjir Bandang di Desa Tualang Baro Kasaf, Michel; Hadi, Tjut Rizqi Maysyarah; Harja, Jetno; Anam, M Khairul; Taufik, Taufik; Alfitra, TM Rezaka; Alfisyahrin, Alfisyahrin
Jurnal Masyarakat Madani Indonesia Vol. 5 No. 2 (2026): Mei
Publisher : Alesha Media Digital

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59025/a1dvy087

Bencana banjir bandang yang melanda Desa Tualang Baro, Kecamatan Manyak Payed, Kabupaten Aceh Tamiang, memberikan dampak serius pada sektor pendidikan berupa kerusakan fasilitas fisik dan trauma psikologis yang menurunkan motivasi belajar anak. Masalah spesifik yang dihadapi mitra adalah hilangnya perlengkapan alat tulis siswa serta terbatasnya akses edukasi yang mampu memulihkan kesiapan mental anak pascabencana. Kegiatan Pengabdian kepada Masyarakat ini bertujuan untuk memulihkan kondisi psikososial, meningkatkan kembali semangat belajar, serta menjaga keberlanjutan pendidikan anak melalui intervensi darurat yang terencana. Metode yang digunakan adalah pendekatan partisipatif yang melibatkan dosen dan mahasiswa melalui tiga tahapan utama: persiapan kebutuhan logistik, pelaksanaan edukasi interaktif selama tiga hari, serta evaluasi respon partisipan. Hasil kegiatan menunjukkan bahwa distribusi paket alat tulis yang terdiri dari buku, alat gambar, dan perlengkapan sekolah lainnya berhasil memenuhi kebutuhan dasar belajar siswa. Indikator keberhasilan terlihat dari antusiasme dan partisipasi aktif anak-anak dalam sesi belajar bersama, di mana terjadi peningkatan kepercayaan diri dan pengurangan tanda-tanda trauma secara bertahap melalui pendekatan yang menyenangkan. Kesimpulannya, integrasi antara penyediaan sarana belajar fisik dan pendampingan edukatif merupakan strategi awal yang proporsional dan efektif dalam mendukung pemulihan pendidikan anak di situasi krisis.

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.

Co-Authors -, Tashid Abrar Hadi Ade Riyanda Putra Agustin Agustin Agustin Agustin Agustin Agustin Agusviyanda Agusviyanda Agusviyanda Agusviyanda Ahmad Ihsan Ahmad Zamsuri Ahmad Zamsuri, Ahmad Aisum Aliyah Sari Akram, Rizalul Al Amin Fadillah Sani Alfa Saleh Alfisyahrin, Alfisyahrin Alfitra, TM Rezaka Alkadri Masnur Ambiyar, Ambiyar Andesa, Khusaeri Andhika, Imam 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 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 Darma, Adi Surya Daryanto, Diki Dea Safitri Dedy Irfan Devi Yuliana Dewi Sari Wahyuni Didik Sudyana Didik Sudyana Diki Daryanto Diky Daryanto Dona Wahyuning Laily Eddy Kurniawan Pradana Efrizoni, Lusiana Elangga Sony Widiharsono Elva, Yesri Emerlada, Esi Tri Erlin Erlin Erlinda, Susi Ersan Fadrial, Yogi Esi Tri Emerlada Fadli Suandi Fahrul Yamani Faisol Mas’ud 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 Fuquh Rahmat Shaleh Gendhy Dwi Harlyan Gubtha Mahendra Putra Gunadi Gunanti Mahasri Gunawan, Chichi Rizka Habibi Ulayya Hadi Asnal, Hadi Hairah, Ummul Halim, Muhammad Yusuf Hamdani Hamdani - Hamdani . Hamdani Hamdani Hamdani Hamdani Hamdani Hamdani Handayani, Nadya Satya Hanif Aulia Happy Yugo Prasetiya Haris Kurniawan, Haris Harja, Jetno Hartomi, Zupri Henra Hasan J. Alyamani Haviluddin Haviluddin Hazira, Nadila Helda Yeni Helda Yenni, Helda Hendra Saputra Hendrawan, Riki hendri, nofri Herianto Herianto Herwin Herwin Ika Purnamasari Ike Yunia Pasa Ikhsan Ikhsan Indah Mukhlis Tamara Indra Prayogo Indra Prayogo Indri Febrianti Irfan Putra Pratama Irfansyah Irfansyah Irfansyah Irfansyah Irsyad, Akhmad Irwanda Syahputra Irwanda Syahputra Irzal Arief Wisky Istianah Istianah Jamaris, Muhamad Jamaris, Muhammad Jasmarizal Junadhi Junadhi Junadhi Junadhi Junadhi, Junadhi Kadek Mirnawati Karfindo, Karfindo 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 Lia Oktavia Ika Putri Lilis Cahaya Septiana Liza Fitria Lucky Lhaura Van FC Lucky Lhaura Van FC, Lucky Lhaura Lusiana Lusiana Efrizoni Lusiana Lusiana M Syauqi Hafizh M. Ikhsan Wibowo Machdalena Mahamad, Abd Kadir Mahendra, Muhammad Ihza Mahessya, Raja Ayu 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 Budi Saputra muhammad Fuad Muhammad Ikhsan Wibowo Muhammad Nur Ihwan Muhammad Wisdan Pratama Putra Munawir Munawir Munawir N.A, Randi Nadila Rahmadhani Nadya Alinda Rahmi Nanda, Novianda Nanda Nariza Wanti Wulan Sari Nasrul Sani Neci Nirwanda Nina Nurmalia Dewi Nisa, Aida Nora Lizarti Novi Yona Sidratul Munti Nu'man, Nu'man Nurhuda, Agus Tri Nurjayadi Nurjayadi Nurjayadi Nurjayadi Nurjayadi Nurjayadi Nurkholifah Dwi Rahayu Nurul fadillah, Nurul Nurul Indriani Nurwijayanti Pandu Pratama Putra, Pandu Pratama Paradila, Dinda Parlindungan Kudadiri Permana, Randy Pradipta , Rahman Pranata, Angga Pratiwi, Mutiana 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, Rometdo Ruri Hartika Zain Saiful Bukhori Salman Aldo Alfaresi Salsabila Rabbani Salsabila Rabbani Saon, Sharifah Saputra, Eko Ikhwan Sari Irma Yani Sitorus Sari, Atalya Kurnia Sarjon Defit Setyantini, Woro Hastuti 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 Torkis Nasution Tri Putri Lestari Tri Putri Lestari Tri Putri Lestari Tri Putri Lestari, Tri Putri Triyani Arita Fitri Ulfah, Aniq Noviciate Wahyudianto, Mochamad Rizky Wahyuni, Dewi Sari Waksito, Alan Zulfikar Waskita, Ghozi Indra Wifra, Rizki Wirta Agustin Wirta Agustin Yaakub, Saleh Yansyah Saputra Wijaya Yenni, Heda Yesaya Twin Situmorang Yogi Ersan Fadrial Yogi Yunefri, Yogi Yoyon Efendi Yuda Irawan Yudhistira, Dewangga Yumami, Eva Zainal Arifin Zeki Kurniadi zeki Kurniadi

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