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All Journal RABIT: Jurnal Teknologi dan Sistem Informasi Univrab Informatics and Digital Expert (INDEX) Jurnal Manajemen Sistem Informasi Community Service Journal : Jurnal Pengabdian Masyarakat Mardira
Meyer Mega Eklesia Silaban
Politeknik Negeri Indramayu
Computer Science & IT Engineering

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Prediksi Masa Studi Mahasiswa Unama Jambi Menggunakan Metode Algoritma C4.5 Mega, Meyer; Jasmir, Jasmir
Jurnal Manajemen Sistem Informasi Vol 8 No 1 (2023): MANAJEMEN SISTEM INFORMASI
Publisher : LPPM Universitas Dinamika Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1113.318 KB) | DOI: 10.33998/jurnalmsi.2023.8.1.770

Abstract

Every year the number of students at The University of Dynamics of the Nation jambi is always increasing but the students who graduate are different from the number of students who enter. Therefore, the author conducts a data mining analysis on student data so that it can be used by academic supervisors to find out the graduation status of students and as a warning so that students can graduate on time so as to reduce the number of delays in graduation. The author uses student data in 2016 and 2017 as training data and 2020 as testing data as many as 120 training data and 109 testing data and has carried out the data cleaning and attribute selection process using the forward selection method. In conducting the analysis, the author used the Tools Weka tool. The author uses the C4.5 algorithm method with 12 attributes, but there are 4 attributes that are most influential after selecting data using the forward selection method on WEKA. In this case, the author uses 4 test options, namely 5 Fold Cross Validation, 10 Fold Cross Validation, 70% Percentage Split, and 80% Percentage Split. The C4.5 Algorithm method produces the largest accuracy value in the training data, namely 5 Fold Cross Validation by 92.5% and in the testing data by 100%.
Sinergi Transformasi Digital dan Strategi Green Tourism dalam Mendukung Keberlanjutan Bisnis (Studi Kasus: PT Ancol Taman Impian) Sahid Triambudhi; Rosena Shintabella; Meyer Mega Eklesia Silaban
Informatics and Digital Expert (INDEX) Vol. 8 No. 1 (2026): INDEX, Mei 2026
Publisher : LPPM Universitas Perjuangan Tasikmalaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36423/index.v8i1.2661

Abstract

Industri pariwisata menghadapi tekanan ganda pasca-pandemi, yaitu keharusan memulihkan kinerja ekonomi sekaligus memenuhi standar keberlanjutan lingkungan (Environmental, Social, and Governance - ESG). PT Pembangunan Jaya Ancol Tbk menghadapi tantangan dalam mengelola lonjakan pengunjung yang berpotensi meningkatkan jejak karbon dan inefisiensi operasional jika tetap menggunakan sistem manajemen konvensional. Penelitian ini bertujuan untuk menganalisis peran transformasi digital sistem informasi yang mencakup online ticketing website ancol.com, ancol mobile apps (android dan IOS), self-services kiosk, point of sales (untuk kasir dan petugas pintu gerbang), online travel agent (OTA), third-party apps (customer engagement, customer relations management, social media analytics, dll sebagai solusi strategis dalam mendukung keberlanjutan destinasi wisata. Penelitian menggunakan metode deskriptif kuantitatif dengan menganalisis data sekunder dari Laporan Keberlanjutan dan Laporan Tahunan Ancol periode 2022-2024. Fokus analisis mencakup korelasi antara implementasi digitalisasi (sistem e-ticketing, aplikasi pengunjung, dan pemantauan utilitas) dengan indikator efisiensi material, intensitas energi, dan pertumbuhan pendapatan usaha. Hasil penelitian menunjukkan bahwa transformasi digital berkontribusi signifikan terhadap efisiensi sumber daya. Peralihan ke ekosistem digital penuh berbasis pengalaman pengguna (website, mobile apps, self-service kiosk) dan pelayanan oleh tim ancol (sistem POS) pada akhirnya berhasil menurunkan penggunaan material kertas (paperless) secara signifikan di pintu gerbang utama. Secara operasional, sistem informasi mendukung pemantauan energi yang presisi, menghasilkan rasio intensitas energi yang tetap efisien meskipun jumlah kunjungan wisatawan meningkat signifikan dari tahun 2022-2024. Dari aspek ekonomi, digitalisasi memperluas kanal pendapatan dan mempercepat pemulihan finansial perusahaan. Disimpulkan bahwa integrasi teknologi informasi bukan hanya alat pendukung operasional, melainkan fondasi utama dalam mewujudkan pariwisata berkelanjutan.
Evaluasi Efektivitas Fitur Layanan Candi Borobudur Berdasarkan Analisis Sentimen Ulasan Google Maps Menggunakan Teknik Naive Bayes Meyer Mega Eklesia Silaban; Rosena Shintabella; Sahid Triambudhi
Informatics and Digital Expert (INDEX) Vol. 8 No. 1 (2026): INDEX, Mei 2026
Publisher : LPPM Universitas Perjuangan Tasikmalaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36423/index.v8i1.2747

Abstract

Perkembangan pariwisata digital telah mentransformasi interaksi wisatawan dengan destinasi wisata, menjadikan platform ulasan daring seperti Google Maps sebagai sumber informasi penting sekaligus aset data yang bernilai untuk evaluasi kualitas layanan. Penelitian ini bertujuan untuk menganalisis persepsi wisatawan terhadap efektivitas fitur layanan Candi Borobudur berdasarkan sentimen ulasan Google Maps menggunakan algoritma Naive Bayes. Data penelitian berupa 1000 ulasan pengguna Google Maps yang dikumpulkan melalui observasi digital dan proses ekspor data ulasan pada periode tertentu. Tahapan penelitian meliputi pengumpulan data, preprocessing teks menggunakan Orange Data Mining, pelabelan sentimen otomatis berbasis lexicon multibahasa, ekstraksi fitur TF-IDF, serta klasifikasi sentimen menggunakan algoritma Naive Bayes ke dalam tiga kelas, yaitu positif, netral, dan negatif. Evaluasi model dilakukan menggunakan metode 5-fold cross validation. Hasil penelitian menunjukkan bahwa model Naive Bayes memperoleh performa yang baik dengan nilai accuracy sebesar 0,894, precision sebesar 0,896, recall sebesar 0,894, F1-score sebesar 0,894, dan Area Under Curve (AUC) sebesar 0,983. Hasil analisis menunjukkan bahwa sebagian besar ulasan pengunjung cenderung memiliki sentimen positif, khususnya terhadap aspek keindahan wisata, fasilitas, dan pengalaman berkunjung, meskipun masih ditemukan sentimen negatif terkait kepadatan pengunjung, harga tiket, dan pengelolaan fasilitas tertentu. Penelitian ini diharapkan dapat menjadi sumber evaluasi berbasis data bagi pengelola wisata dalam meningkatkan kualitas layanan dan pengalaman pengunjung secara berkelanjutan.
Enhancing Graduate Competencies toImprove Industry Employability throughPre-Internship Training and Industrial Internship Programs Sahid Triambudhi; Rosena Shintabella; Meyer Mega Eklesia Silaban
Community Service Journal : Jurnal Pengabdian Masyarakat Mardira Vol. 1 No. 2 (2025): Community Service in Indonesia
Publisher : Politeknik Mardira Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.71266/csj.v1i2.61

Abstract

This community service project aims to strengthen student competencies through the implementation of both pre-internship briefing sessions and industrial internship placement. The program was carried out by the Department of Informatics Engineering at the Indramayu State Polytechnic (Polindra) as part of its commitment to improving students’ job readiness and aligning vocational education with industrial demands. The activity involved a structured workflow including industry needs identification, coordination with the Industrial Internship Program Team (PMI), preparation of learning materials, arrangement of seminar logistics, on-site briefing seminars, and post-program evaluations. A total of 182 students were successfully placed in various partner industries for internship programs following the briefing seminar. The results show significant improvements in students’ soft and technical skills, confidence levels, workplace adaptability, and understanding of professional ethics. Partner industries also provided positive feedback regarding student performance and contribution. The program demonstrated the essential role of vocational institutions in bridging academic knowledge and industrial application, while offering measurable benefits to both students and industry partners.
OPTIMASI ARSITEKTUR BI-LSTM DENGAN ATTENTION MECHANISM UNTUK KLASIFIKASI PERUBAHAN PERANGKAT LUNAK PADA ULASAN PERANGKAT BERGERAK Alifia Puspaningrum; Muhamad Mustamiin; Meyer Mega Eklesia Silaban; Esti Mulyani
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 2 (2026): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i2.8338

Abstract

Analyzing mobile application user reviews plays a crucial role in software evolution. However, manual processes are often constrained by the large volume of data and language ambiguity. This research develops an automated classification model to categorize reviews into bug reports, feature requests, and non-informative using a Bi-Long Short-Term Memory (LSTM) architecture reinforced with an Attention Mechanism. Experimental results show that the model achieves 94.33% training accuracy and 71.95% testing accuracy, outperforming the standard Bi-LSTM which only reached 87.58% in training accuracy and 70.85% in testing. In terms of efficiency, this model converges faster, reaching peak performance in only 100 epochs, compared to 500 epochs for the standard Bi-LSTM. Furthermore, experiments show that increasing architectural complexity, such as combining Bi-LSTM with Attention, triggers overfitting and weight fluctuations. Thus, the integration of the Attention Mechanism in BiLSTM is proven to provide an optimal balance between computational efficiency and prediction accuracy, effectively supporting decision-making systems for developers.
Co-Authors Alifia Puspaningrum Esti Mulyani Jasmir, Jasmir Muhamad Mustamiin Rosena Shintabella Sahid Triambudhi