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All Journal Al-Fiziya: Journal of Materials Science, Geophysics, Instrumentation and Theoretical Physics JURNAL SISTEM INFORMASI BISNIS Prosiding Seminar Nasional Sains Dan Teknologi Fakultas Teknik Jurnal Ilmiah Kursor Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Teknologi dan Sistem Komputer JITK (Jurnal Ilmu Pengetahuan dan Komputer) MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer CCIT (Creative Communication and Innovative Technology) Journal Jurnal Teknologi Informasi dan Multimedia Mutawatir : Jurnal Keilmuan Tafsir Hadith Journal of Applied Data Sciences Prosiding Seminar Nasional Teknik Elektro, Sistem Informasi, dan Teknik Informatika (SNESTIK)
MUHAMMAD TAJUDDIN
Universitas Bumigora Mataram
Religion Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Electrical & Electronics Engineering Energy Engineering Materials Science & Nanotechnology Physics

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Rancang Bangun Sistem Informasi Self Acreditation Berbasis Online Muhammad Tajuddin; M. Hisyam; Suharliyanto Suharliyanto
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 17 No. 2 (2018)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v17i2.153

Abstract

Balai Pengembangan Pendidikan Anak Usia Dini dan Pendidikan Masyarakat BP-PAUDDIKMAS Nusa Tenggara Barat (NTB) melihat akreditasi Pusat Kegiatan Belajar Masyarakat (PKBM) masih dilakukan secara manual oleh Badan Akreditasi Nasional Pendidikan Nonformal (BAN-PNF), maka dilakukan inovasi berbasis teknologi informasi dengan nama Self Akreditasi Dalam Jaringan Pusat Kegiatan Belajar Masyarakat (SADAR PKBM) yang berbasis online. Penelitian fokus pada sistem pengajuan akreditasi oleh PKBM secara mandiri sebelum mengajukan akreditasi secara manual. Penelitian ini bertujuan untuk memudahkan pelaksanaan penilaian akreditasi PKBM sebelum mengajukan akreditasi dan juga meningkatkan ektifitas dan efisiensi dalam penilaian akreditasi serta pengembangan SADAR PKBM berbasis online sangat membantu PKBM. Penilaian SADAR PKBM mencakup 8 aspek penilaian, yaitu standar isi, standar proses, standar kompetensi lulusan, standar pendidik dan tenaga kependidikan, standar sarana dan prasarana, standar pengelolaan, standar pembiayaan dan standar penilaian. Metode System Development Life Cycle (SDLC) digunakan dengan teknik terstruktur dan teknik Prototyping untuk membuat deskripsi secara sistimatis dan akurat dengan cara mencari informasi faktual sesuai standar akreditasi yang mendetail dan mengidentifikasi masalah-masalah untuk justifikasi keadaan dan kondisi penilaian yang digunakan assesor dalam menjalankan tugasnya. Hasil aplikasi SADAR PKBM agar PKBM menyadari pentingnya mutu yang tolok ukurnya adalah akreditasi, sehingga hasil SADAR PKBM dapat digunakan sebagai persiapan sebelum mengajukan akreditasi.
Komparasi Ekstraksi Fitur dalam Klasifikasi Teks Multilabel Menggunakan Algoritma Machine Learning Lusiana Efrizoni; Sarjon Defit; Muhammad Tajuddin; Anthony Anggrawan
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 21 No. 3 (2022)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v21i3.1851

Abstract

Ektraksi fitur dan algoritma klasifikasi teks merupakan bagian penting dari pekerjaan klasifikasi teks, yang memiliki dampak langsung pada efek klasifikasi teks. Algoritma machine learning tradisional seperti Na¨ıve Bayes, Support Vector Machines, Decision Tree, K-Nearest Neighbors, Random Forest, Logistic Regression telah berhasil dalam melakukan klasifikasi teks dengan ektraksi fitur i.e. Bag ofWord (BoW), Term Frequency-Inverse Document Frequency (TF-IDF), Documents to Vector (Doc2Vec), Word to Vector (word2Vec). Namun, bagaimana menggunakan vektor kata untuk merepresentasikan teks pada klasifikasi teks menggunakan algoritma machine learning dengan lebih baik selalumenjadi poin yang sulit dalam pekerjaan Natural Language Processing saat ini. Makalah ini bertujuan untuk membandingkan kinerja dari ekstraksi fitur seperti BoW, TF-IDF, Doc2Vec dan Word2Vec dalam melakukan klasifikasi teks dengan menggunakan algoritma machine learning. Dataset yang digunakan sebanyak 1000 sample yang berasal dari tribunnews.com dengan split data 50:50, 70:30, 80:20 dan 90:10. Hasil dari percobaan menunjukkan bahwa algoritma Na¨ıve Bayes memiliki akurasi tertinggi dengan menggunakan ekstraksi fitur TF-IDF sebesar 87% dan BoW sebesar 83%. Untuk ekstraksi fitur Doc2Vec, akurasi tertinggi pada algoritma SVM sebesar 81%. Sedangkan ekstraksi fitur Word2Vec dengan algoritma machine learning (i.e. i.e. Na¨ıve Bayes, Support Vector Machines, Decision Tree, K-Nearest Neighbors, Random Forest, Logistic Regression) memiliki akurasi model dibawah 50%. Hal ini menyatakan, bahwa Word2Vec kurang optimal digunakan bersama algoritma machine learning, khususnya pada dataset tribunnews.com.
Game for Sasak Script Based on Knuth Morris Pratt Algorithm and ADDIE Model Muhammad Tajuddin; Ahmat Adil; Andi Sofyan Anas
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 22 No. 1 (2022)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v22i1.2363

Abstract

Knowledge of the Sasak script is very few Sasak people are interested in learning it. The writing system of the Sasak script is in danger of becoming extinct, so the local government must carry out literacy education so that the Sasak script does not become extinct from the face of the Lombok earth and must be applied to elementary and junior high schools, not only in the learning and teaching process. Directing children can be done by introducing them to the game-based Sasak baluk olas script. The Sasak script game based on KMP (Knuth Morris Pratt) Algorithm and ADDIE (Analysis, Design, Development, Implementation, Evaluation) which integrates game thinking and game elements has proven helpful in learning new knowledge. For this reason, the purpose of this study is to discuss how to develop applications for the Sasak Baluk Olas script on smartphones based on the Android system. designed based on the famous visual novel concept that combines multimedia elements including audio, animation, graphics, and images to make it more interesting and lively. All of these elements combine with gamification elements such as quizzes, rewards, badges, and feedback to make it a gamification application. Based on all the abilities of the Sasak Baluq Olas script, it can help potential users, especially elementary and junior high school students in Mataram City to increase the level of understanding and awareness of the Sasak script so that it does not become extinct
Between Meccan Origins and Medinan Expansion: A Diachronic Reading of Secondary Embedding in Qs. Al-Muddaththir [74]: 31 Muhammad Tajuddin; Muh. Awaluddin A; Bambang Sampurno; Basyir Arif
Mutawatir : Jurnal Keilmuan Tafsir Hadith Vol. 15 No. 2 (2025): DECEMBER
Publisher : Department of Qur'an dan Hadith Faculty of Ushuluddin and Philosophy UIN Sunan Ampel Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15642/mutawatir.2025.15.2.60-85

Abstract

This study examines the phenomenon of secondary embedding in the Qur’an, understood as the incorporation of Medinan material into surahs of Meccan provenance through a process of intra-textual development during the prophetic period. The case under consideration is Qs. al-Muddaththir [74]:31, a verse whose exceptional length constitutes a marked statistical departure from the otherwise compact rhythmic pattern of the surah. Drawing on Nicolai Sinai’s analytical framework and the principle of structural cohesion, this article argues that when the verse is analytically bracketed as a distinct literary layer, the thematic continuity of the surrounding passage remains intact, no discernible narrative gap emerges, and the surah’s overall rhythmic and structural balance is preserved. It is further proposed that the motive underlying this embedding is responsive in character, the verse appears to address dialogical concerns arising from the early audience’s engagement with the Qur’anic proclamation, while the phrase fī qulūbihim maraḍ aligns terminologically with vocabulary characteristic of the Medinan discursive context. This study contributes to the growing scholarly conversation on the dynamic textual development of the Qur’an, particularly as it pertains to surah structure and its relationship to the evolving social and theological horizons of the early Muslim community. It further offers a methodological contribution to the diachronic study of surah composition, demonstrating how structural and terminological analysis may illuminate the Qur’an’s responsive engagement with its formative historical context.
Financial Condition Prediction Using a Soft Voting Ensemble Model Based on Structured Financial Indicators and Unstructured News Data Ibnu Rasyid Munthe; Sumijan Sumijan; Muhammad Tajuddin
Journal of Applied Data Sciences Vol 7, No 3: September 2026
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v7i3.1417

Abstract

The rapid growth of capital market participation has increased the need for reliable analytical tools to assess the financial conditions of listed companies. Conventional approaches commonly rely on structured financial indicators and may not fully capture contextual information reflected in financial news. This study aims to evaluate the predictive potential of structured financial data and unstructured textual data using a soft voting ensemble framework. The structured dataset consists of 1,263 financial records collected from the reports of manufacturing companies listed on the Indonesia Stock Exchange, whereas the unstructured dataset contains 6,329 online financial news records related to Indonesian stocks and listed companies. The structured data were processed through missing-value handling, normalization, and class balancing, while the textual data were processed through cleaning, case folding, tokenization, filtering, stemming, and Term Frequency–Inverse Document Frequency (TF-IDF) feature extraction. The proposed ensemble model combines the probability outputs of six base classifiers: Decision Tree, Support Vector Machine, Multinomial Naive Bayes, Logistic Regression, Random Forest, and K-Nearest Neighbors. Experimental results show that the soft voting ensemble achieved an accuracy of 92.66% on the structured dataset and 98.53% on the unstructured dataset. These findings indicate that both financial indicators and textual information can provide valuable predictive signals for identifying company financial conditions. The contribution of this study lies in the comparative evaluation of two distinct data sources using a consistent ensemble-learning framework. However, the two datasets were evaluated independently rather than integrated into a single multimodal pipeline. Therefore, future research should develop a data-fusion mechanism to assess whether combining financial indicators and news-based sentiment can further improve predictive performance and strengthen decision support for investors and financial analysts.
LANDSLIDE VULNERABILITY MAPPING USING FUZZY LOGIC METHOD FOR DISASTER MITIGATION: Case Study of Bungaya District, Gowa Regency Amirin Kusmiran; Jusniati; Ayusari Wahyuni; Minarti Minarti; Muhammad Tajuddin
Al-Fiziya: Journal of Materials Science, Geophysics, Instrumentation and Theoretical Physics Vol. 8 No. 2 (2025): AL-FIZIYA JOURNAL OF MATERIALS SCIENCE, GEOPHYSICS, INSTRUMENTATION AND THEORET
Publisher : Department of Physics, Faculty of Science and Technology, UIN Syarif Hidayatullah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/fiziya.v8i2.48919

Abstract

Landslides are a significant threat to the Bungaya District in Gowa Regency, Indonesia, with five incidents recorded in 2019. This study aimed to map landslide vulnerability using the Fuzzy Logic method implemented in ArcGIS software and propose appropriate mitigation strategies. The analysis incorporated six parameters: rainfall intensity, soil type, elevation, slope, land cover type, and geology. The results revealed four categories of vulnerability: not vulnerable (592.91 ha), low (3,093.32 ha), medium (9,139.72 ha), and high (7,557.29 ha). Areas with high vulnerability were characterized by steep topography, easily eroded soil and rock types, and inappropriate land-use practices. Rannaloe, Sapaya, Bissoloro, and Buakkang villages were classified as highly susceptible to landslides. Mitigation strategies were proposed based on the vulnerability level, with a combination of technical and vegetative methods recommended for high- and moderate-vulnerability areas, whereas vegetative methods alone were deemed sufficient for low-vulnerability regions. This study contributes to advancing spatially informed disaster risk management by integrating susceptibility mapping with actionable mitigation recommendations tailored to the vulnerability levels identified in the Bungaya District.
Co-Authors Abdul Manan Abdul Manan Abdul Manan Abdul Manan Abdurahim, Abdurahim Adam Bachtiar Maulachela Ahmad Zuli Amrullah Ahmat Adil Akbar Juliansyah Amirin Kusmiran Andi Sofyan Anas Anthony Anggrawan Arif, Basyir Ayusari Wahyuni Bambang Sampurno Dicksa Ananda Christian Tue Efrizoni, Lusiana Elga Alfariza Endang Siti Astuti Hamdani Husnan Husain Husain Husain Husain Ibnu Rasyid Munthe Jaya, Nenet Natasudian Jusniati M. Hisyam Minarti Minarti Muh. Awaluddin A Nenet Natasudian Jaya Ni Luh Putu Merawati R Fanny Priniti R. Fanny Printi Ardi Raden Fanny Printi Ardi Renita Fitriani Ria Rismayati Rifqi Hammad Sarjon Defit Suharliyanto Suharliyanto Sumijan Susandri, Susandri Syahroni Hidayat Veithzal Rivai Zainal Zaenal Abidin Zainal A Hasibuan