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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Semantik Jurnal Pemberdayaan Masyarakat Madani (JPMM) MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer JURNAL PENDIDIKAN TAMBUSAI Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Idealis : Indonesia Journal Information System Jurnal Kajian Ilmiah Indonesian Journal of Applied Research (IJAR) Jurnal Pendidikan dan Teknologi Indonesia Jurnal Indonesia : Manajemen Informatika dan Komunikasi Bit (Fakultas Teknologi Informasi Universitas Budi Luhur) Indonesian Community Journal Telematika MKOM
Indra Indra
Program Studi Teknik Informatika Fakultas Teknologi Informasi Universitas Budi Luhur
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PERBANDINGAN METODE BALANCED SCORECARD DAN NAÏVE BAYES DALAM PREDIKSI DAN REKOMENDASI PADA PENILAIAN KINERJA GURU (STUDI KASUS : SMK YADIKA 12 DEPOK) Zaqi Kurniawan; Indra
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 4 No. 2 (2023): Jurnal Indonesia : Manajemen Informatika dan Komunikasi (JIMIK)
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) AMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jimik.v4i2.230

Abstract

Teacher Performance Assessment guarantees a quality learning process at all levels of education. Educational supervision will be carried out with the aim to improve the quality of teaching / teacher so that the competitiveness of students studying at the school will increase towards a better direction. Supervision assessment is a class visit technique to obtain data about the actual situation regarding the ability and skills of teachers in teaching and mastery of class. To determine the teacher's performance, one approach can be done using the Balanced Scorecard approach and Naïve Bayes classification. The determination of teacher performance is then processed using Analytic Network Process-based modeling to improve teacher evaluation criteria that are still low. With the help of Super Decision software, a decision support system was created in determining teacher performance. The results of this study are the recommendations of permanent teachers in Junior High Schools, High Schools, and Vocational Schools Yadika 12 Depok based on performance to be objective and make more efficient decisions.
PKM Penerapan Teknologi Aplikasi Zakat Berbasis Mobile Application Pada Masjid Raudhotul Jannah Komplek Taman Cipulir Estate Agus Umar Hamdani; Indra Indra; Puspita Rani; Riskiana Wulan
I-Com: Indonesian Community Journal Vol 4 No 2 (2024): I-Com: Indonesian Community Journal (Juni 2024)
Publisher : Fakultas Sains Dan Teknologi, Universitas Raden Rahmat Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33379/icom.v4i2.4407

Abstract

Optimizing the management of zakat funds can be used to empower the economy of the poor so as to reduce poverty levels. Therefore, there needs to be a body tasked with managing zakat funds so that they can provide optimal contributions to the community. The zakat administrators of the Roudhotul Jannah Taman Cipulir Estate Mosque were given the task of collecting and managing zakat funds from mosque congregations. This service is carried out by writing in a book and inputting zakat funds through the zakat management website. The weakness of the current zakat management is that the data collection process for muzakki and mustahiq is still carried out by zakat administrators, causing the administration process to be slow. Apart from that, prospective muzakki who are outside the mosque environment cannot be served well. Based on the conditions above, training and assistance in managing zakat is needed for the zakat administrators of the Raudhotul Jannah Mosque in order to create optimal services. The method used in this activity is training and mentoring. This activity takes the form of training on the use of mobile application-based zakat management applications for zakat administrators. Based on the evaluation of the implementation of this community service activity, the percentage of partner satisfaction was 88% and the percentage of mobile application-based zakat management application testing was 96%, so it is hoped that there will be an increase in knowledge and understanding regarding good zakat governance and can continue to be used in the future..
Increasing Knowledge of Residents in Pinang Griya Permai Housing in Waste Management through Training of Organic and Anorganic Waste Recycling by the Teratai Waste Bank Indra; Syafrullah, Muhammad; Rahayu, Sri; Saputro, Heru; Saputra, Rilo Anggoro; Bagaskoro, Muhammad Akbar; Fauzan, Rubi Ahmad; Fatayati, Fitri Nur; Sabasteo, Jeremy Noel
Jurnal Pemberdayaan Masyarakat Madani (JPMM) Vol. 7 No. 2 (2023): Jurnal Pemberdayaan Masyarakat Madani (JPMM) (DOAJ & SINTA 3 Indexed)
Publisher : Fakultas Ekonomi dan Bisnis Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/JPMM.007.2.10

Abstract

Garbage is currently still a problem for the community where there is a lack of knowledge of waste management properly. The waste bank is present as a solution to assist the government in reducing the accumulation of waste and helping to improve the economy of housewives, especially residents affected by the COVID-19 pandemic. Bank Sampah Teratai (BST) is one of the social group organizations engaged in environmental economics, especially in managing household waste for residents of RW. 05 Pinang Griya Permai, Pinang - Tangerang. Bank Sampah Teratai located in Pinang Griya Permai Tangerang is a partner in this activity. Observation results show that Bank Sampah Teratai does not yet have adequate knowledge in waste management, both organic and inorganic. Based on the above problems, a community partnership program was formed with the academic community (lecturers and students) of Universitas Budi Luhur to help solve problems at the Bank Sampah Teratai. Based on these conditions, training on organic and inorganic waste management was carried out for residents of the Pinang Griya Permai housing. This training provides understanding, and appropriate skills, which help residents to carry out organic and inorganic waste management. Based on the results of the questionnaire after the training was carried out, 100% of participants stated that the material presented was in accordance with their needs, and the material presented was also considered good by 100% of the participants. The long-term result of this training is an increase in the understanding and skills of the residents to manage organic and inorganic waste. This training has been a useful contribution to improving skills for members of the Bank Sampah Teratai in particular, and skills for residents of Pinang Griya Permai housing in general.
Rule-Based Natural Language Processing in Volcanic Ash Data Searching System Priandana, Rangga Kusuma; Indra, Indra
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 18, No 1 (2024): January
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.88081

Abstract

Indonesia is a country with a unique geography. The confluence of three tectonic plates located in the country results in frequent natural disasters, from earthquakes to volcanic activity. BMKG is a monitoring agency tasked with providing information related to these natural disasters. However, one type of natural disaster data, the SIGMET data (Significant Meteorological Information) used to provide information on volcanic ash, has a complicated format that is difficult for ordinary people to understand. Therefore, this research seeks to make finding information related to volcanic ash and volcanic eruptions in Indonesia easier in terms of access and comprehension. In this research, an application design will be carried out that can search SIGMET data by implementing natural language processing with a production rule base. The research results have an accuracy rate of 84% using 25 test sample sentences that combine sentences and words contained in the important words section.
Analisis Klasterisasi Kinerja Anggaran pada Satuan Kerja di Lingkup Kanwil DJPb DKI Jakarta Priyono, Agus; Gagal Rencana, Feri Susilo; Indra, Indra
Jurnal Pendidikan dan Teknologi Indonesia Vol 5 No 4 (2025): JPTI - April 2025
Publisher : CV Infinite Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jpti.753

Abstract

Penelitian ini bertujuan untuk menganalisis pola kinerja anggaran satuan kerja Kanwil DJPb DKI Jakarta menggunakan metode klasterisasi. Data yang digunakan mencakup Indikator Kinerja Pelaksanaan Anggaran (IKPA), realisasi anggaran, dan pagu anggaran tahun 2024. Teknik klasterisasi yang digunakan adalah K-Means dan Klasterisasi Hirarki (Single Linkage), serta validasi klaster menggunakan metode Silhouette Score. Hasil penelitian menunjukkan bahwa metode K-Means membagi satuan kerja ke dalam empat klaster dengan distribusi yang signifikan, dengan mayoritas satuan kerja (65,3%) menunjukkan kinerja anggaran yang tinggi, sementara 3,8% satuan kerja tergolong dalam klaster dengan kinerja rendah. Klasterisasi Hirarki mengungkap adanya outlier yang perlu ditindaklanjuti, termasuk satuan kerja tanpa realisasi anggaran dan satuan kerja dengan pagu sangat besar,. Temuan utama menunjukkan bahwa sebagian besar satuan kerja telah berhasil merealisasikan anggaran secara optimal, namun terdapat klaster yang memerlukan perhatian khusus akibat rendahnya persentase realisasi atau kendala struktural dalam pengelolaan anggaran. Kombinasi kedua metode memberikan pemahaman yang lebih komprehensif mengenai pola kinerja anggaran, serta identifikasi kelompok yang memerlukan intervensi kebijakan. Rekomendasi diberikan untuk meningkatkan efisiensi anggaran pada klaster dengan kinerja rendah dan mempertahankan kualitas kinerja pada klaster dominan. Penelitian ini memberikan wawasan mengenai pola pengelolaan anggaran yang dapat menjadi dasar kebijakan perbaikan kinerja satuan kerja di lingkungan DJPb.
Detecting Trending Topics Using Soft Frequent Pattern Mining (SFPM) on Indonesian Language Tweets Related to Earthquake News Indra, Indra; Prakoso, M Syawaladi Kukuh; Rosul, Mekar Bunga Allamanda; Mufti, Mufti
Jurnal Nasional Pendidikan Teknik Informatika: JANAPATI Vol. 14 No. 2 (2025)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v14i2.85086

Abstract

Social media users frequently post updates regarding ongoing natural disasters, including specific details and locations. These posts are crucial for real-time insights into such events; however, their informal tone and use of slang can make them difficult to utilize effectively. This study employs Soft Frequent Pattern Mining to detect trending earthquake topics in Indonesia using a specific Indonesian language dataset from X. The three-week testing period revealed varied performances: the first week showed a topic recall of 0.57, the second improved to 0.72, and the third drastically decreased to 0.28, indicating a temporary lack of significant trending topics. Averaging topic recall at 0.52, keyword precision at 0.34, and keyword recall at 0.45, the results highlight substantial room for improvements. This underlines the importance of methodological optimizations in future research to enhance the system’s effectiveness in identifying and validating widely discussed issues.
Perancangan Data Warehouse Menggunakan Metode Star Schema dan ETL Untuk Menghasilkan Laporan Efektifitas Proses Rekrutmen Kandidat di Enigma Camp Hartanto, Rosa; Candra Kirana, Jution; Indra
Jurnal Pendidikan dan Teknologi Indonesia Vol 5 No 12 (2025): JPTI - Desember 2025
Publisher : CV Infinite Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jpti.1229

Abstract

Enigma Camp merupakan perusahaan IT Bootcamp dan manajemen talenta yang berfokus pada pelatihan programmer dengan modul yang disesuaikan untuk memenuhi standar industri. Dalam hal konsolidasi data dan analisa, Enigma Camp sering kali mengalami kesulitan dan membutuhkan banyak waktu. Hal tersebut dikarenakan data rekrutmen bersumber dari banyak aplikasi platform rekrutmen dengan ukuran data yang besar. Perancangan Data Warehouse ini diharapkan mampu mempermudah konsolidasi data tersebut sehingga informasi data dapat digunakan untuk memonitor, menganalisis, serta meningkatkan efektivitas dan efisiensi keseluruhan proses rekrutmen di Enigma Camp. Model Data Warehouse memerlukan identifikasi kebutuhan informasi yang akurat dan pemilihan sumber data yang terpercaya. Proses perancangannya mengimplementasikan skema bintang (Star Schema) yang melibatkan tahapan ETL (Extract, Transform, Load) guna mengintegrasikan, mengekstrak, membersihkan, mentransformasi, dan memuat data ke dalam Data Warehouse. Penggunaan metode Star Schema dipilih karena kemampuannya dalam menampung beragam tabel dimensi, termasuk sub-tabel dimensi, yang berpotensi menghasilkan informasi lebih kaya untuk mendukung pengambilan keputusan. Sistem Data Warehouse yang dirancang ini mampu menyajikan laporan analisis rekrutmen secara efektif, sehingga mendukung pengambilan keputusan strategis yang lebih cepat dan tepat. Hal ini berkontribusi pada peningkatan efisiensi operasional dan kualitas rekrutmen kandidat di Enigma Camp.
Optimasi Model Data Warehouse Menggunakan Skema Bintang untuk Mendukung Analisis Multidimensi Kredit Usaha Rakyat Syariah Indra; Firdaus, Hanafi; Firmansyah, Eko; Desianti, Vania
Jurnal Pendidikan dan Teknologi Indonesia Vol 5 No 10 (2025): JPTI - Oktober 2025
Publisher : CV Infinite Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jpti.1405

Abstract

Sistem Informasi Kredit Program (SIKP) pada akhir 2024 menanggung beban 592.294 data debitur dan 1.220.833 data akad Kredit Usaha Rakyat (KUR) Syariah. Beban ini menurunkan performa query (kueri), menghambat kebutuhan rekapitulasi mendesak, dan menimbulkan inkonsistensi karena ekstraksi manual tanpa timestamp (penanda waktu). Penelitian ini bertujuan mengoptimasi model data warehouse berbasis star schema (skema bintang) agar kinerja kueri meningkat, kualitas data terjaga, dan tersedianya analisis multidimensi untuk pemantauan kinerja pembiayaan serta penilaian risiko. Perancangan dilakukan dengan satu tabel fakta utama beserta dimensi waktu, wilayah, jenis pembiayaan, dan kategori debitur. Data historis diproses melalui ETL (Extract, Transform, Load) sebelum dianalisis dengan OLAP (Pemrosesan Analitik Daring) guna mendukung agregasi lintas hierarki. Ruang lingkup pengujian mencakup kueri rekapitulasi agregat menurut waktu, wilayah, jenis pembiayaan, dan kategori debitur dengan menggunakan data historis SIKP tahun 2023 dan 2024. Pengujian menunjukkan percepatan eksekusi kueri hingga 85% dibandingkan skema operasional awal, disertai peningkatan konsistensi pelaporan dan sifat yang fleksibel untuk pemutaran perspektif analitis. Secara praktis, rancangan ini menyediakan pelaporan strategis yang cepat tanpa mengorbankan kestabilan operasional penerimaan transaksi SIKP. Secara teoretis, hasilnya menguatkan posisi star schema sebagai arsitektur yang relevan untuk big data dan analitik keuangan syariah.
Detecting Disaster Trending Topics on Indonesian Tweets Using BNgram Indra Indra; Nur Aliza
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 23 No. 1 (2023)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v23i1.3308

Abstract

People on social media share information about natural disasters happening around them, such as the details about the situation and where the disasters are occurring. This information is valuable for understanding real-time events, but it can be challenging to use because social media posts often have an informal style with slang words. This research aimed to detect trending topics as a way to monitor and summarize disaster-related data originating from social media, especially Twitter, into valuable information. The research method used was BNgram. The selection of BNgram for detecting trending topics was based on its proven ability to recall topics well, as shown in previous research. Some stages in detection were data preprocessing, named entity recognition, calculation using DF-IDF, andhierarchical clustering. The resulting trending topics were compared with the topics obtained using the Document pivot method as the basic method. This research showed that BNgram performs better in detecting trending natural disaster-based topics compared to the Document pivot. Overall, BNgram had a higher topic recall score, and its keyword precision and keyword recall values were slightly better. In conclusion, recognizing the significance of social media in disaster-related information can increase disaster response strategies and situational awareness. Based on the comparison, BNgram was proven to be a more effective method for extracting important information from social media during natural disasters.
Co-Authors Agus Priyono Agus Umar Hamdani Anggi Triyani Bagaskoro, Muhammad Akbar Besar Agung Martono Candra Kirana, Jution Darmawan, Rizqi Desianti, Vania Fatayati, Fitri Nur Fauzan, Rubi Ahmad Firdaus, Hanafi Firmansyah, Eko Gagal Rencana, Feri Susilo Hartanto, Rosa Indra Indra Juan Kalyzta Mufti Mufti MUFTI MUFTI, MUFTI Muhammad Ardi Willdan Nanang Wahyu Hidayat Nur Aliza Painem, Painem Priandana, Rangga Kusuma Puspita Rani Riskiana Wulan Rosul, Mekar Bunga Allamanda Sabasteo, Jeremy Noel Saputra, Rilo Anggoro saputro, heru Selfiana Halfiani Sismadi, Wawan Sri Hartati SRI RAHAYU Surahmat, Asep Syafrullah, Muhammad Titing Widyastuti