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All Journal JURNAL SISTEM INFORMASI BISNIS Jurnal Sains dan Teknologi E-Dimas: Jurnal Pengabdian kepada Masyarakat Jurnal Ilmiah FIFO JURNAL ILMIAH GEOMATIKA JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal Pilar Nusa Mandiri Tekinfo | Scientific Journal of Industrial and Information Engineering Indonesian Journal of Artificial Intelligence and Data Mining JURNAL REKAYASA TEKNOLOGI INFORMASI ILKOM Jurnal Ilmiah J-SAKTI (Jurnal Sains Komputer dan Informatika) Building of Informatics, Technology and Science PRIMA: Journal of Community Empowering and Services REMIK : Riset dan E-Jurnal Manajemen Informatika Komputer Jurnal Sistem Komputer dan Informatika (JSON) Madani : Indonesian Journal of Civil Society Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Journal of System and Computer Engineering Bulletin of Computer Science Research GANESHA: Jurnal Pengabdian Masyarakat PROFICIO: Jurnal Pengabdian Masyarakat Jurnal Pengabdian Masyarakat (ABDIRA) J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Informatika, Komputer dan Bisnis (JIKOBIS) Jurnal Altifani Penelitian dan Pengabdian kepada Masyarakat Jurnal Informasi Sains dan Teknologi (ISAINTEK) Journal of Applied Agricultural Science and Technology Malcom: Indonesian Journal of Machine Learning and Computer Science International Journal of Economics and Management Research Journal of Digital Law and Policy Bulletin of Informatics and Data Science Science Information System and Technology West Science Nature and Technology Journal of Information System and Application Development International Journal of Economics and Management Research INTERNATIONAL JOURNAL OF SOCIETY REVIEWS (INJOSER)
Moh. Erkamim
Politeknik Negeri Bali
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Nursing Public Health Social Sciences Other

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Model Ensemble Stacking untuk Klasifikasi Big Data Stunting Berbasis XGBoost dan MLP Khairul Hawani Rambe; Frans Mikael Sinaga; Leni Anggraini Susanti; Moh. Erkamim
REMIK: Riset dan E-Jurnal Manajemen Informatika Komputer Vol. 10 No. 1 (2026): Volume 10 Nomor 1 Januari 2026
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/remik.v10i1.15903

Abstract

Klasifikasi status gizi balita berbasis data besar memerlukan pendekatan machine learning yang mampu menangani kompleksitas dan heterogenitas data secara akurat dan stabil. Populasi penelitian mencakup seluruh data rekam medis balita periode 2023–2024 yang diperoleh dari RS Mitra Medika Tanjung Mulia, dengan teknik pengambilan sampel menggunakan total sampling terhadap dataset yang tersedia. Sampel berupa data antropometri balita yang meliputi jenis kelamin, usia, berat badan, tinggi atau panjang badan, nilai Z-score, serta label status gizi. Metode yang digunakan adalah pendekatan kuantitatif berbasis machine learning dengan tahapan pra-pemrosesan, pembangunan model, dan evaluasi performa. Pra-pemrosesan mencakup pembersihan data, transformasi variabel kategorikal, normalisasi fitur numerik, serta pembagian data latih dan data uji dengan rasio 80:20. Model yang dikembangkan menggunakan pendekatan ensemble stacking dengan XGBoost sebagai base learner dan Multi-Layer Perceptron (MLP) sebagai meta learner. Evaluasi kinerja model dilakukan menggunakan confusion matrix, precision, recall, F1-score, dan akurasi. Hasil pengujian menunjukkan bahwa model stacking mencapai akurasi sebesar 99,64% dengan jumlah kesalahan prediksi yang sangat rendah serta nilai precision, recall, dan F1-score yang seimbang pada setiap kelas. Temuan ini menunjukkan bahwa integrasi algoritma boosting dan neural network mampu meningkatkan stabilitas dan kemampuan generalisasi model. Dengan demikian, pendekatan stacking XGBoost–MLP efektif dalam klasifikasi status gizi balita dan berpotensi diterapkan sebagai sistem pendukung keputusan deteksi dini masalah gizi berbasis big data.
Implementasi Dempster-Shafer Theory Sebagai Mesin Inferensi Pada Sistem Pakar Diagnosa Penyakit Cerebral Palsy Moh. Erkamim; Mursalim Tonggiroh; Novi Yona Sidratul Munti; Yuri Rahmanto
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 5 No. 2 (2023): Desember 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v5i2.6940

Abstract

Early diagnosis and appropriate intervention are very important to minimize the long-term impact of Cerebral Palsy in children. Currently, the diagnosis of Cerebral Palsy in children is often based on clinical observations, developmental tests, and brain imaging. It requires medical knowledge and careful observation by an experienced health professional, which is often difficult to access in many areas. For this reason, early diagnosis by parents is very important for taking action against children suffering from Cerebral Palsy. This research aims to develop an expert system that can diagnose Cerebral Palsy in children using the Dempster-Shafer Theory algorithm as an inference engine to make it easier to diagnose and produce the right diagnosis. The Dempster-Shafer Theory approach works by calculating the level of confidence or belief in a hypothesis or certain event based on existing evidence. An expert system built on a website has the ability to make diagnoses based on symptoms and display diagnosis results, definitions of the type of Cerebral Palsy disease in children, as well as actions or methods of treating it. Based on the test results, the accuracy level obtained was a value of 90% and was classified as "Good" criteria.
IMPLEMENTATION OF SMART CITY APPLICATION IN SUSTAINABLE TRANSPORT SYSTEMS: PROSPECTS AND DEVELOPMENT OF SMARTCITY IN INDONESIA Danarti Karsono; Muhammad Rizal Fernandita Pamungkas, Moh. Erkamim, A. Bamban Yuuwono
INTERNATIONAL JOURNAL OF SOCIETY REVIEWS Vol. 1 No. 11 (2024): INTERNATIONAL JOURNAL OF SOCIETY REVIEWS (INJOSER)
Publisher : Adisam Publisher

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

Abstract

The study aims to discuss the prospects and development of the Smart City concept in sustainable transportation systems in Indonesia. The study assesses the various challenges and opportunities emerging from the integration of information and communication technology into existing transport infrastructure. Through an in-depth literature exploration, the research identifies key factors that influence the implementation of Smart Cities and explores strategies that can accelerate the realization of efficient, inclusive, and sustainable smart transport. Research results show that the implementation of Smart Cities in Indonesia is still in its early stages, but has great potential due to the demands of rapid urbanization and development. The Smart City concept is expected to support reducing congestion, improving energy efficiency, and reducing greenhouse gas emissions. However, the research also reveals a number of major obstacles, including the need for massive investment in infrastructure, cyber security, and the digital gap between regions.
Hybrid Gradient Boosting and SMOTE-ENN for Toddler Nutritional Status Classification on Imbalanced Data Alfry Aristo Jansen Sinlae; Moh. Erkamim; Farid Fitriyadi; Lilik Suhery; Rachmat Destriana
Bulletin of Informatics and Data Science Vol 3, No 2 (2024): November 2024
Publisher : PDSI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61944/bids.v3i2.93

Abstract

Stunting in toddlers remains a serious global health issue with long-term impacts on children's physical and cognitive development. One of the main challenges in classifying nutritional status is class imbalance, where the number of normal cases significantly exceeds that of minority classes such as stunted and severely stunted. This study aims to develop a hybrid approach by integrating the Gradient Boosting algorithm with the SMOTE-ENN (Synthetic Minority Oversampling Technique–Edited Nearest Neighbors) method to improve classification performance on imbalanced data. The dataset used was obtained from the Kaggle platform, consisting of 121,000 entries with four nutritional status categories. Data preprocessing included label encoding, numerical feature standardization, and stratified data splitting with an 80:20 ratio. The model was evaluated using accuracy, precision, recall, F1-score, and ROC-AUC metrics. The proposed hybrid model successfully increased the recall for the stunted class from 61.80% to 98.41%, and the F1-score from 71.93% to 83.58%. Overall accuracy improved from 92.39% to 93.35%, while the ROC-AUC score increased from 99.08% to 99.63%. These findings demonstrate that integrating Gradient Boosting with SMOTE-ENN is effective in enhancing sensitivity to minority classes and improving overall multi-class classification performance.
Desain Interface Costumer Relationship Management (CRM) (Studi Kasus : CV Mediatama Percetakan) Fitriyadi, Farid; Indriastiningsih, Erna; Erkamim, Moh
Jurnal Informasi, Sains dan Teknologi Vol. 5 No. 02 (2022): Desember: Jurnal Informasi Sains dan Teknologi
Publisher : Politeknik Negeri FakFak

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/isaintek.v5i02.60

Abstract

Customer Relationship Management (CRM) merupakan sebuah strategi yang digunakan oleh suatu perusahaan untuk dapat mengkontrol, pengecekan, menciptakan dan mempertahankan suatu hubungan yang baik dan berkelanjutan dengan pelanggannya dan mengurangi kemungkinan para pelanggannya pindah ke perusahaan atau rekanan lain. CV Mediatama Percetakan merupakan sebuah perusahaan yang menjual berbagai macam buku pendidikan. CV Mediatama Percetakan membutuhkan sebuah strategi untuk dapat menjalin hubungan dan meningkatkan layanan kepada pelanggannya agar pelanggannya tetap loyal kepada CV Mediatama. Penelitian ini bertujuan untuk merancang dan membangun sebuah Tampilan Website / Interface Customer Relationship Management (CRM) yang berbasis web pada CV Mediatama agar menjalin hubungan dan meningkatkan pelayanannya kepada pelanggan. Desain Interface Website  CRM menggunakan model prototype. Dari penelitian ini akan menghasilkan sebuah Desain Interface Customer Relationship Management (CRM) berbasis web yang kemudian akan di uji dengan menggunakan metode pengujian Black-Box ,yaitu menguji perangkat lunak dari segi spesifikasi fungsional tanpa menguji desain dan kode program. Dengan perancangan dan pembangunan Customer Relationship Management (CRM) ini diharapakan CV Mediatama dan menjalin hubungan yang berkelanjutan dan dapat meningkatkan layanannya kepada pelanggan.
Bridging the Knowledge Gap through Organic Field School (OFiS) Method for Long Pepper (Piper longum) Farmers in Wonogiri, Indonesia Suswadi Suswadi; Mutiarra Ridyo Arum; Arbianti Arbianti; Tyas Soemarah Kurnia Dewi; Supartini Supartini; Moh Erkamim
PRIMA: Journal of Community Empowering and Services Vol 9, No 1 (2025): June
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/prima.v9i1.93525

Abstract

Organic certification is urgently needed for long pepper to meet global market standards and enhance product credibility. Wonogiri Regency is the largest center for long pepper production in Central Java, with this biopharmaceutical commodity cultivated for generations. Its promising market potential necessitates meeting global standards, including organic certification. This community service initiative aims to bridge knowledge gaps and improve farming practices through Good Agricultural Practices (GAP) for organic long pepper. The methods used include classroom activities to assess farmer knowledge and transfer knowledge through socialization and field activities in demonstration plots, starting with the identification of farmer training priorities. A pre-test survey revealed that while over 65% of farmers understood the planting stage, less than 50% were familiar with land preparation, planting, and harvesting. This low level of knowledge is due to a lack of information on farming practices that comply with organic Good Agricultural Practices (GAP). Key training priorities identified include: (1) preparation and application of organic fertilizers and pesticides, (2) propagation of organic long pepper seeds, and (3) post-harvest handling. To address these, the Organic Field School (OFiS) was established as a training platform, equipping farmers with practical skills. The results indicate that farmers gained significant knowledge and can now independently implement organic long pepper cultivation. OFiS method can bridge the farmer’s knowledge gap, increase farmers’ knowledge in preparation, growing, planting, and harvesting based on Good Agricultural Practices (GAP). OFiS serves as an effective solution to enhance sustainable agricultural practices, supporting farmers in producing high-quality organic long pepper that meets global standards.
Co-Authors A. Bamban Yuuwono Adi Candra, Adi Adi Nugroho Susanto Putro Adi Nur Khofid Aini, Delvi Nur Alfry Aristo Jansen Sinlae Ali Zainal Abidin Alaydrus Allesandro Umbu Balla Rundi Anindya Putri Tamara Arbianti Arbianti Argia Putri Ramadhani Arisantoso Arisantoso Asih Lestari, Asih Batubara, Ana Uzla Cantikasari, Yuliana Danarti Karsono Daniarti, Yeni Dwi Susilo Utami Edhi Prayitno, Edhi Egidius Fkun Eri Mardiani Erlin Dolphina Erni Widarti Farid Fitriyad Fatihah, Syalaysa Imani Fatkhul Imron Faustina Yuniastuti Faustina Yuniastuti Fitriyad, Farid Fitriyadi, Farid Fitriyadi, Farid Frans Mikael Sinaga Handayani, Nurdiana Hanifah Nurul Muthmainah Heriyani, Nofitri Hidayati , Diyah Nur I Gede Iwan Sudipa I Wayan Karang Utama Imam Setyo Nugroho Indriastiningsih, Erna Irfan AP Joko Sulistyono Judijanto, Loso Khairul Hawani Rambe Khofid, Adi Nur Khoirun Nisa Legito . legito, Legito Leni Anggraini Susanti Lilik Suhery, Lilik Loso Judijanto Maharani, Annissa Tiara Mohammad Imam Shalahudin Muhammad Muharrom Muhammad Rizal Fernandita Pamungkas Muhammad Rizal Fernandita Pamungkas Muhammad Syarif Hartawan Muhammad Zidni Subarkah Mulyadi Mulyadi Mursalim Tonggiroh Mustakim Mustakim Mutiarra Ridyo Arum Naylah Dzakiah Ngakan Kompiang Adi Suardana Ni Kadek Sri Devi Putri Swambini Ni Kadek Wintan Purnama Sari Ni Ketut Tri Srilaksmi Ni Komang Triana Andini Ni Made Ayu Nadia Putri Damayanti Nindi Permata Riau Nirma Ceisa Santi Nofri Yudi Arifin Novi Yona Sidratul Munti Nugraha, Tegar Wijanarko Surya Nurhayati Nurhayati Pamungkas, M Rizal Fernandita Pamungkas, Muh. Rizal F. Pamungkas, Muhammad Rizal Fernandita Rachmat Destriana Rahmat Catur Haryadi Rahmat Catur Haryadi Ramadhani, Argia Putri Rifky Lana Rahardian Riyanto, Umbar Rundi, Allesandro U.B. Rundi, Allesandro Umbu Balla Said Thaufik Rizaldi Saifuddin Saifuddin Saifuddin Saifuddin Sandra Dewi Saraswati Sapto Priyadi Sepriano Sepriano Septarini, Ri Sabti Setyawati, Nisrina Yulia Shabrina Hapsari Shalahudin, Mohammad Imam Siti Nurhayati Sitti Rachmawati Soares, Teotino Gomes Subarkah, Muhammad Zidni Sulhatun Sulhatun Sulistiyawati, Anggun Supartini Supartini Suswadi Syahputra, Ridwan Angga Tami, Nanda Putri Tanniewa, Adam M Tino Feri Efendi Tonggiroh, Mursalim Tyas SOEMARAH KURNIA DEWI Tyas Soemarah Kurnia Dewi Utama, I Wayan Karang Vera Wati Wardani, Qurrotul Ain Putri Kusuma Wartono Wartono Wartono Wartono Wartono, W Wati, Vera Winalia Agwil Wiyono wiyono Yanuardi Yanuardi Yuri Rahmanto Zandra Dwanita Widodo Zandra Dwanita Widodo Zilrahmi, Zilrahmi