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All Journal Jurnal TIMES Jurnal Mantik Penusa INTECOMS: Journal of Information Technology and Computer Science The IJICS (International Journal of Informatics and Computer Science) Jurnal Riset Informatika ComTech: Computer, Mathematics and Engineering Applications Jurnal Mantik bit-Tech JATI (Jurnal Mahasiswa Teknik Informatika) Journal of Intelligent Decision Support System (IDSS) JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Bulletin of Information Technology (BIT) Jurnal Minfo Polgan (JMP) BEES: Bulletin of Electrical and Electronics Engineering Jurnal Nasional Teknologi Komputer Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI) Jurnal Hasil Pengabdian Masyarakat (JURIBMAS) Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Jurnal Testing dan Implementasi Sistem Informasi Journal of Algorithmic Digital Engineering and Networks The Journal of Information Technology, Computer Science, and Electrical Engineering
Muhammad Iqbal
Universitas Pembangunan Panca Budi
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Social Sciences

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Rancang Bangun Sistem Informasi Posyandu Ibu dan Anak Berbasis Web Chairul Rizal; Supiyandi Supiyandi; Muhammad Iqbal; Randi Rian Putra; Muhammad Israr Fathoni
Jurnal Testing dan Implementasi Sistem Informasi Vol. 1 No. 2 (2023): Jurnal Testing dan Implementasi Sistem Informasi
Publisher : Lembaga Riset dan Inovasi Almatani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55583/jtisi.v1i2.539

Abstract

Desa Sei Limbat adalah desa yang berada di Kabupaten Langkat Propinsi Sumatera Utara. Desa ini memiliki 6 dusun serta hanya mempunyai 3 Posyandu. Posyandu saat ini memiliki peran yang berarti untuk mendukung pelayanan kesehatan masyarakat. Selain itu, kegiatan Posyandu selama ini berjalan lancar juga karena adanya buku Sistem Informasi Posyandu (SIP) sebagai pedoman pelaksanaan. Hadirnya teknologi memberi kontribusi dalam penataan sistem manajemen dan proses kerja di instansi pemerintah maupun swasta. Penerapan Teknologi Informasi di kehidupan desa salah satunya adalah penggunaan Sistem Informasi Posyandu ibu dan anak berbasis web. Tujuan dari penelitian ini adalah merancang sistem informasi posyandu berbasis web dengan mengintegrasikan 3 posyandu dari 6 dusun di desa Sei Limbat. Tahapan analisis dan perancangan menggunakan metode RAD (Rapid Application Development). Hasil dari penelitian ini terbangunnya Sistem informasi Posyandu ibu dan anak yang dapat memudahkan dalam pengelolaan posyandu di Desa Sei Limbat Kabupaten Langkat.
Implementasi Multi-Objective Optimization Based On Ratio Analysis (MOORA) Dalam Sistem Pengambilan Keputusan Pemilihan Jurusan Berbasis Minat Siswa Supiyandi Supiyandi; Chairul Rizal; Muhammad Iqbal; Randi Rian Putra; Hafizh Sallam
Jurnal Testing dan Implementasi Sistem Informasi Vol. 1 No. 2 (2023): Jurnal Testing dan Implementasi Sistem Informasi
Publisher : Lembaga Riset dan Inovasi Almatani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55583/jtisi.v1i2.540

Abstract

Di era digital sekarang ini dibutuhkan kemampuan individu yang lebih kreatif dan inovatif diberbagai bidang, sehingga siswa SMK harus lebih mempersiapkan kompetensinya. Dalam hal ini kompetensi berkaitan dengan jurusan yang mereka pilih. Rata-rata siswa salah mengambil jurusan sekitar 35%, ikut teman sekitar 50%, untuk siswa yang benar-benar tepat memilih jurusan 15%. Untuk hal ini maka dibutuhkan metode sistem pendukung keputusan MOORA dalam hal mennetukan jurusan sesuai dengna minat dan bakat siswa. Pengembangan sistem menggunakan metode Waterfall. Tujuan penelitian ini mendesain sistem pendukung keputusan yang dapat digunakan untuk pemilihan jurusan sesuai minat siswa dengan memanfaatkan keputusan hasil metode MOORA. Hasil dari penelitian ini menggambarkan perhitungan MOORA untuk pemilihan jurusan maka calon siswa mendapatkan keputusan untuk memilih jurusan Multimedia karena memiliki nilai tertinggi
Rancang Bangun Aplikasi Pendataan Kendaraan Operasional Menggunakan Metode Prototipe Astri Aprilia Pratiwi; Muhammad Iqbal
Bulletin of Information Technology (BIT) Vol 4 No 2: Juni 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v4i2.714

Abstract

PT. HM Sampoerna Tbk is a leading tobacco company in Indonesia as well as an affiliate of the world's leading tobacco company, Philip Morris International, which has many operational vehicles to support the process of distributing their products but the process of managing operational vehicles for maintenance or repair is still not optimal. Operational vehicles that are poorly maintained can cause problems with the vehicle at any time, causing large losses for the company. Operational vehicle maintenance must be carried out regularly so that the company's operational activities are not disrupted and to keep the vehicle in good condition and primed for traveling to distribute the company's products. The author develops an operational vehicle data collection application using the prototype method, namely rapid software development to present an overview of existing ideas and problems and then obtain feedback from users so that prototypes can be repaired immediately. The application design uses DFD and ERD and the results obtained from this research are applications that can provide information about the history of operational vehicle repairs, remind operational vehicle data management staff to carry out periodic maintenance.
Analisis Metode Certainty Factor Pada Sistem Pakar Diagnosa Kerusakan Sepeda Motor Anzas Ibezato Zalukhu; Irwan Syahputra; Suhardiansyah; Muhammad Iqbal; Rian Farta Wijaya
Bulletin of Information Technology (BIT) Vol 4 No 4: Desember 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v4i4.1083

Abstract

Motorcycles are a predominant mode of transportation in Indonesian society, comprising 84.5% of the total transportation vehicles in 2021 according to national BPS data. Despite providing convenience in mobility, motorcycles are susceptible to disturbances or damages that can hinder normal usage and potentially lead to accidents. Many motorcycle riders lack knowledge or awareness regarding potential issues with their motorcycles. This research aims to analyze the implementation of the certainty factor method in an expert system for identifying motorcycle malfunctions, with a focus on Giska Servis workshop. The certainty factor method serves as a reasoning tool to determine identification outcomes based on identified symptoms. The results of this study are expected to contribute to facilitating motorcycle riders in diagnosing symptoms of malfunctions in their vehicles. The certainty factor method offers a systematic and structured approach to identifying motorcycle issues. Through the implementation of this method, the research attempts to measure the success rate of the expert system in diagnosing malfunctions. Data from the identification results at Giska Servis workshop will be comprehensively analyzed to evaluate the accuracy and effectiveness of the certainty factor method in this context.By highlighting the success of this method, this research is expected to provide valuable insights for the development of expert systems for motorcycle issue identification. The findings of this study can serve as a guide for workshops and motorcycle users to enhance understanding and management of vehicle issues, thereby minimizing the potential for accidents and extending the lifespan of motorcycles.
Implementasi Algoritma Naïve Bayes dalam Menganalisis Sentimen Review Pengguna Tokopedia pada Produk Kesehatan Andi Ernawati; Ayu Ofta Sari; Siti Nurhaliza Sofyan; Muhammad Iqbal; Rian Farta Wijaya Wijaya
Bulletin of Information Technology (BIT) Vol 4 No 4: Desember 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v4i4.1090

Abstract

It must be realized that customer satisfaction is the main goal for companies in developing their business. Because customers' opinions written on social media will have a big influence on the company and potential customers. In its development, it is increasingly found in various online media, one of which is Tokopedia. Product reviews are an important source of information regarding quality, service and delivery from both consumers and manufacturers. With a very large amount of data for each product on Tokopedia, analyzing and concluding product review information will definitely take a lot of time if done manually. To overcome this, a sentiment analysis system is needed that can automatically extract important information that can objectively determine product quality and handle large amounts of textual information. The sentiment analysis system consists of several stages, namely crawling, pre-processing, word weighting, and sentiment classification. By applying the Naïve Bayes algorithm through selecting range and frequency features, accuracy, accuracy and recall results will be obtained using the Confusion Matrix test. The dataset used is from the kaggle.com site regarding customer sentiment on health products with the type of mask. using the Naïve Bayes Algorithm Method to determine the sentiment of user reviews by classifying 2 positive and negative classes using the NLP approach produces an accuracy value of 88%.
Penerapan Data Mining Untuk Klasifikasi Penduduk Miskin Di Kabupaten Labuhanbatu Menggunakan Random Forest Dan K-Nearest Neighbors Andi Ernawati; Khairul; Zulham Sitorus; Muhammad Iqbal; Darmeli Nasution
Bulletin of Information Technology (BIT) Vol 6 No 2: Juni 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v6i1.1783

Abstract

This study aims to apply and compare the performance of two data mining algorithms—Random Forest (RF) and K-Nearest Neighbors (KNN)—in classifying poverty status among residents of Labuhanbatu Regency. The dataset includes information on occupation, income, housing, and education from 21,137 individuals. After undergoing preprocessing, model training, hyperparameter optimization, and evaluation, both models were assessed using five key metrics: accuracy, precision, recall, F1-score, and AUC. The results show that Random Forest performed slightly better than KNN, achieving an accuracy of 0.6023, precision of 0.4827, recall of 0.4177, F1-score of 0.4479, and an AUC of 0.5681. In comparison, KNN obtained an accuracy of 0.5990, precision of 0.4771, recall of 0.4006, F1-score of 0.4355, and an AUC of 0.5622. Based on these findings, it can be concluded that Random Forest is more effective for poverty classification on this dataset, although the performance difference is relatively small.
Analisis Sentimen Terhadap Dampak Inflasi Menggunakan Naive Bayes Siti Nurhaliza Sofyan; Muhammad Iqbal
Bulletin of Information Technology (BIT) Vol 6 No 1: Maret 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v6i1.1796

Abstract

This research aims to analyze public sentiment regarding the impact of inflation in 2024 on survival. Inflation is seen as one of the most important factors influencing a country's economic growth. In this research, the results of public sentiment in 300 tweets on the Twitter application were obtained, namely the emotion 'joy' was 194 or 64%, 'surprise' was 71 or 23%, 'fear' was 20 or 6%, 'sadness' was 9 or 3% , 'disgusted' by 7 or 2% and 'angry' by 0.06% . This research uses the orange mining application with multilingual sentiment analysis techniques visualized through box plots and scatter plots, which aims to classify Twitter users based on their emotional responses. The decline in the level of economic growth has led to the emergence of the view that inflation has a negative effect on economic growth, not a positive effect. The findings of this research provide insight into the government's role in overcoming current inflation and providing sustainable benefits and are expected to be used as material for evaluating the government's role.
Analisis Sentimen Penerapan Deep Learning dan Analisis Sentimen terhadap Gap Kompetensi Lulusan Lembaga Pendidikan dan Pelatihan Vokasi terhadap Dunia Kerja dengan Metode Long Short-Term Memory (LSTM) Susilawati Yahya; Zulham Sitorus; Muhammad Iqbal; Darmeli Nasution; Rian Farta Wijaya
Bulletin of Information Technology (BIT) Vol 6 No 2: Juni 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v6i2.2031

Abstract

The gap between vocational graduates’ competencies and labor market demands remains a pressing issue in Indonesia. This study aims to analyze alumni perceptions regarding the alignment between competencies acquired during their studies at LP3I Banda Aceh and real-world job requirements. A quantitative approach was adopted using a deep learning method based on Long Short-Term Memory (LSTM). Data were collected through an online survey containing open-ended responses from 934 alumni, followed by preprocessing, tokenization, lexicon-based sentiment labeling, and data splitting into training and testing sets. The models developed included pure LSTM, LSTM with class weights, and Bidirectional LSTM (BiLSTM). Results indicate that BiLSTM achieved the highest performance with 90% accuracy and a weighted F1-score of 0.91. Additionally, 44.5% of respondents expressed neutral or negative sentiments, highlighting a mismatch between acquired competencies and industry demands. These findings underscore the urgency of curriculum evaluation and stronger collaboration between vocational institutions and the labor market. This study demonstrates that deep learning offers an efficient and objective tool for competency mapping in vocational education.
Analisis Sentimen Ulasan Pengguna Aplikasi DANA pada Google Play Store Menggunakan TF-IDF dan Naïve Bayes Puspita Wanny; Muhammad Iqbal
BEES: Bulletin of Electrical and Electronics Engineering Vol 7 No 1 (2026): July 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bees.v7i1.10083

Abstract

The DANA application is a digital wallet service widely used by the public to support various digital financial transaction activities. The high number of users results in numerous reviews on the Google Play Store containing various responses, experiences, and opinions regarding the quality of the DANA application service. However, the large number of review data makes the manual process of identifying and grouping opinions less effective and takes a relatively long time. This study aims to analyze and classify the sentiment of DANA application user reviews on the Google Play Store into positive, negative, and neutral categories and to determine the performance of the algorithm used in the classification process. The solution implemented is sentiment analysis using a text mining approach and Natural Language Processing (NLP) to process user reviews automatically. The research data was obtained through a scraping process and resulted in 3,509 DANA application user reviews. The data then went through preprocessing stages including cleaning, case folding, normalization, tokenizing, stopword removal, and stemming. Then, sentiment labeling and word weighting were carried out using the Term Frequency-Inverse Document Frequency (TF-IDF) method. The data was then divided into 80% training data and 20% testing data. Classification was then performed using the Multinomial Naïve Bayes algorithm. Model performance was evaluated using a Confusion Matrix with Accuracy, Precision, Recall, and F1-Score metrics. The results showed that the Naïve Bayes model produced an Accuracy value of 80.48%, Precision of 76.75%, Recall of 80.48%, and F1-Score of 78.13%. These results indicate that the combination of the TF-IDF method and the Naïve Bayes algorithm is capable of classifying the sentiment of DANA app user reviews with quite good performance and can be used to help obtain an overview of user perceptions of the DANA app based on reviews provided on the Google Play Store
Analisis Algoritma Genetika dan Algoritma Monroe pada Penjadwalan Tenaga Kesehatan di Rumah Sakit H. Amri Tambunan Deli Serdang Ade Guna Suteja; Muhammad Iqbal; Muhammad Syahputra Novelan
Jurnal Nasional Teknologi Komputer Vol 6 No 3 (2026): Juli 2026
Publisher : CV. Hawari

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The study aims to analyze the influence of multimedia web interface design on the user retention rate on the Google Classroom e-learning platform at Universitas Pembangunan Panca Budi (UNPAB). Given the transition of digital learning systems within the campus environment, evaluating user experience becomes crucial for determining future platform standards. The research method used is quantitative with a causal associative approach. The research sample consists of 118 students from the Information Technology Study Program, class of 2022, selected using purposive sampling techniques. Data were collected through questionnairs with a Likert Scale and analyzed using simple linear regression via statistical software. The results showed that the interface design variable has a positive and significant effect on user retention with a t count value of 12,653 and a significance value of 0,000 (<0,05). The coefficient of determination (R2) indicates that interface design contributes 58,0% to user retention rate, while the remaining 42,0% is influenced by other factors outside the study. These findings confirm that intuitive and functional multimedia interfaces play a vital role in maintaining the sustainability of user interaction within digital learning management systems.
Co-Authors , Arpan Abdul Khaliq Abdul Muin Nasution Ade Guna Suteja Ahkyar Khadafi Aidul Safii Akmal Pratama Harahap Andi Ernawati Andi Ernawati Anzas Ibezato Zalukhu Ardiansyah Ardiansyah Astri Aprilia Pratiwi Atja Ramadhan Ayu Ofta Sari Bagas Alivia M Boy Rizky Akbar Chairul Rizal Dadang Iskandar Mulyana` Darmeli Nasution Dika Dika Dimas Armadansyah DWI SURYANTO Efendi, Syahril Eko Hariyanto Eva Mufida Padilla Firdaus Firdaus Hafizh Sallam Hafni Hafni Irwan Irwan Irwan Syahputra Kairul Fahmi Khairul Khairunnisa Khairunnisa Kurnia Wira Syahputra Maida Indrayani Maisya Fitri Anugrah Muhammad Adli Afdika Muhammad Eka Muhammad Irfan Sarif Muhammad Israr Fathoni Muhammad Noor Hasan Siregar Muhammad Syahputra Novelan Muhammad Zen Nadya Septiani Nadya Nelviony Parhusip Niska, Debi Yandra Nurlina Sari Harahap Puspita Wanny Putra, Randi Rian Rian Farta Wijaya Rian Farta Wijaya Wijaya Rindi Antika Robin Antoni Rudi Hermawan Sapna Indah Br Ginting Sartika Siburian Siti Hapsoh Lubis Siti Nurhaliza Sofyan Siti Nurhaliza Sofyan Sitorus, Zulham Sri Wahyuni Suhardiansyah Sumarno Supiyandi Supiyandi Susilawati Yahya Syaiful Asmi Hasibuan Zulham