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All Journal Dinamik Techno.Com: Jurnal Teknologi Informasi Pixel : Jurnal Ilmiah Komputer Grafis Bulletin of Electrical Engineering and Informatics Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Transformatika Jurnal Informatika dan Teknik Elektro Terapan Scientific Journal of Informatics Register: Jurnal Ilmiah Teknologi Sistem Informasi Jurnal Informatika Upgris JNKI (Jurnal Ners dan Kebidanan Indonesia) (Indonesian Journal of Nursing and Midwifery) JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Jurnal Teknologi Informasi MURA Indonesian Journal of Learning Education and Counseling Digital Zone: Jurnal Teknologi Informasi dan Komunikasi Jurnal Abdimas PHB : Jurnal Pengabdian Masyarakat Progresif Humanis Brainstorming Jurnal Sistem Informasi, Manajemen, dan Akuntansi (SIMAK) JTIK (Jurnal Teknik Informatika Kaputama) Jurnal Riset Sistem Informasi dan Teknologi Informasi (JURSISTEKNI) Brahmana : Jurnal Penerapan Kecerdasan Buatan Infotek : Jurnal Informatika dan Teknologi Jurnal Teknik Informatika (JUTIF) Jurnal Pendidikan dan Teknologi Indonesia Brilliance: Research of Artificial Intelligence Jurnal Rekam Medis dan Manajemen Informasi Kesehatan Jurnal Pengabdian Teknik dan Ilmu Komputer (PETIK) Magistrorum et Scholarium: Jurnal Pengabdian Masyarakat Jurnal Teknologi Informasi Mura Science Technology and Management Journal (STMJ) Scientific Journal of Informatics Bridge: Jurnal Publikasi Sistem Informasi dan Telekomunikasi
M. Zakki Abdillah
Department Of Information Systems, Universitas Nasional Karangturi, Indonesia
Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Public Health Social Sciences Other

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ANALISIS DAN PERANCANGAN SISTEM INFORMASI MANAJEMEN GEREJA MENGGUNAKAN UML (UNIFED MODELLING LANGUAGE) Abdillah, M. Zakki; Pranata, Ivan Gautama Suprayitno
Jurnal Informatika dan Teknik Elektro Terapan Vol. 12 No. 3 (2024)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v12i3.4831

Abstract

Penelitian ini membahas tentang sistem perancangan website. Tujuan dari penelitian ini adalah untuk merancang sebuah sistem berbasis web yang dapat mempermudah pengelolaan jadwal kegiatan. Metode yang digunakan dalam penelitian ini meliputi analisis kebutuhan, dan perancangan sistem. Sistem dalam penelitian ini menggunakan Unified Modelling Language (UML) dimana terdapat beberapa tahap yang dapat digunakan untuk membangun sistem website penjadwalan. Selain menggunakan UML, Penenelitian ini menggunakan diagram alir atau biasa disebut flowchart. Adapun dalam penelitian ini menggunakan Entity Relationship diagram (ERD). Hasil penelitian menunjukkan bahwa sistem penjadwalan yang dikembangkan mampu meningkatkan efisiensi dan akurasi dalam pengelolaan jadwal kegiatan gereja. Pengguna, baik dari kalangan pengurus gereja maupun jemaat, memberikan tanggapan positif terkait kemudahan penggunaan dan fungsionalitas yang disediakan oleh sistem ini. Berdasarkan hasil penelitian, perancangan sistem website penjadwalan dapat dilakukan dengan proses penginputan data order sampai dengan laporan.
GEOGRAPHIC INFORMATION SYSTEM (GIS) FOR MAPPING GREENPARK USING LEAFLET JS Abdillah, M. Zakki; Nawangnugraeni, Devi Astri; Yuniarto, Abdul Hakim Prima
JTIK (Jurnal Teknik Informatika Kaputama) Vol. 5 No. 2 (2021): Volume 5, Nomor 2, Juli 2021
Publisher : STMIK KAPUTAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59697/jtik.v5i2.552

Abstract

Geographical Information System (GIS) is one of systems that functions to process spatial data so that it becomes information that can be understood by ordinary people. Leafletjs is one of the technologies in the development of Geographical Information Systems based online and open source, so the development more dynamic and flexible. This stud present the processing of spatial data into an online-based Geographical Information System. The database used in this development includes Green Space which is divided into 2 classifications, namely Public and Private, and there are 738 total data. With the large amount of data it is possible to process informatively using web-based Geographical Information System using Leafletjs technology. The results of the research, resulting in a percentage of 19.61% data on public greenpark, this results almost the minimum standards for greenpark in an area. So with the web-based information system, people can see the greenpark data in the form of a digital map that easy to understand because it is presented on a polygon map.
Improvement of exclusive breastfeeding practices using the web-based mHealth application “Mama Bekping” Dewi, Mariza Mustika; Widyatun, Diah; Abdillah, M. Zakki
JNKI (Jurnal Ners dan Kebidanan Indonesia) (Indonesian Journal of Nursing and Midwifery) Vol. 13 No. 4 (2025)
Publisher : Alma Ata University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21927/jnki.2025.13(4).569-581

Abstract

Background: Exclusive breastfeeding (EBF) is the practice of giving only breast milk to infants aged 0–6 months without any additional food, except for vitamin supplements and medicines. The prevalence of exclusive breastfeeding among working mothers is significantly lower in urban areas due to inflexible work schedules, early return to work, short maternity leave, fatigue, and lack of support for expressing breast milk at the workplace. The web-based mHealth application “Mama Bekping” was proposed by researchers to provide educational features for working mothers regarding breast care, methods to increase milk supply, proper pumping techniques, and notifications to remind mothers to express breast milk.Objectives: To determine whether the web-based mHealth application “Mama Bekping” can improve knowledge and adherence of working mothers in breast milk pumping.Methods: This study used a quasi-experimental design with two group pretest–posttest. The sample consisted of 80 breastfeeding mother selected using purposive sampling, with a 1-month intervention. Parameters measured were maternal knowledge and adherence to breast milk pumping. Data normality was tested using the Shapiro–Wilk test, while the effect was analyzed using the dependent t-test.Results: The average pumping frequency from week 1 to week 4 was consistent at 14 times per week. However, within 4 weeks, an increase was observed from 12–13 times to 15 times per week. The mean knowledge score before and after intervention showed a 20-point difference, with a minimum difference of 35 points and a maximum difference of 40 points. The dependent t-test revealed a p-value = 0.000 (p < α), indicating a significant effect.Conclusions: The web-based mHealth application “Mama Bekping” effectively increases the knowledge and adherence of working mothers in breast milk pumping, thereby supporting the success of exclusive breastfeeding programs
Accurate hybrid prediction model for poverty line, number, and percentage of impoverished individuals Toni Wijanarko Adi Putra; Yohanes Suhari; Achmad Solechan; Solikhin Solikhin; M. Zakki Abdillah
Bulletin of Electrical Engineering and Informatics Vol 15, No 1: February 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v15i1.10533

Abstract

Poverty remains a major social issue in many developing countries, including Indonesia, as seen in the Central Java region. Over the last five years, the number of impoverished people in Central Java has shown fluctuations, with data from the Central Statistics Agency indicating figures of 3,897.20 thousand (2018), 3,743.23 thousand (2019), 3,980.90 thousand (2020), 4,109.7 thousand (2021), and 3,831.44 thousand (2022). Analyzing these trends is crucial for future poverty reduction efforts. This study aims to develop a web-based predictive system capable of forecasting the poverty line, as well as the number and percentage of poor residents in Central Java. The research utilizes a hybrid forecasting model that integrates the Holt-Winters triple exponential smoothing (HWTES) method with fuzzy time series (FTS), alongside algorithmic approaches such as rate of change (RoC) and frequency-based segmentation. The model's accuracy, evaluated using the average absolute percentage error (MAPE), shows low error rates: 0.9% for the number of impoverished people, 1.6% for the percentage, and 0.7% for the poverty threshold. Compared to the standard HWTES model, this hybrid model demonstrates greater precision. As a result, it can serve as an effective tool to support strategic planning and enhance poverty alleviation programs in Central Java.
Artificial Intelligence in Monetary Response: The Role of Investor Sentiment in the Effectiveness of Bank Indonesia’s Interventions Sumantiawan, Dody Indra; Abdillah , M. Zakki; Muhammad Kholilurrahman
Jurnal Teknik Informatika (Jutif) Vol. 7 No. 2 (2026): JUTIF Volume 7, Number 2, April 2026
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2026.7.2.5184

Abstract

Exchange rate stability is a core pillar of macroeconomic resilience, especially for emerging economies like Indonesia. The effectiveness of Bank Indonesia’s (BI) monetary interventions in stabilizing the Rupiah depends not only on policy instruments but also on market perceptions and investor sentiment. This study examines the relationship between investor sentiment and the effectiveness of BI’s interventions by integrating Natural Language Processing (NLP), event study, and moderated regression analysis. The dataset spans 2023–2025 and includes daily exchange rate data, an investor sentiment index derived from financial forums and business news using VADER and TextBlob algorithms, and BI intervention records. An event study with a ±5 day window evaluates the short-term impact of interventions on exchange rate returns, while moderated regression analyzes the interaction between sentiment and interventions. Results indicate that BI interventions produce short-term exchange rate recovery, with a cumulative average abnormal return (CAAR) of 0.55% on the third day after intervention. Regression findings show that investor sentiment significantly influences Rupiah movements (p < 0.01), and the interaction between sentiment and interventions is also significant (p < 0.05), indicating greater effectiveness under positive or neutral sentiment. These findings underscore that intervention success is closely tied to market psychology. Therefore, BI should incorporate AI-driven sentiment analysis into policy design to enhance intervention effectiveness and strengthen public communication credibility. This study enriches the literature on behavioral macroeconomics and offers a data-driven framework for adaptive monetary policymaking in the digital economy.
Perbandingan Prediksi Pengunjung Website Menggunakan SARIMA, LSTM dan Holt-Winters TES Oei Joviano Matthew Wijaya; M. Zakki Abdillah
Infotek: Jurnal Informatika dan Teknologi Vol. 9 No. 1 (2026): Infotek : Jurnal Informatika dan Teknologi
Publisher : Fakultas Teknik Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jit.v9i1.32909

Abstract

Rapid technological developments have changed people's lifestyles, marked by an increase in online activity. APJII states that by 2025, 229 million Indonesians will be internet users, while BPS recorded 3,816,750 digital businesses in 2023. This growth has encouraged the use of websites as the primary medium for business and information. Therefore, understanding visitor trends and seasonal patterns is crucial for effective and efficient management. This study offers a new contribution by predicting the number of visitors to the website of PT. XYZ, a tea company in Indonesia. It uses three time series models: Seasonal Auto Regressive Integrated Moving Average (SARIMA), Long Short-Term Memory (LSTM), and Holt-Winters Triple Exponential Smoothing (Holt-Winters TES) with a prediction period of 71 days prior and to predict 14 days ahead. The dataset used consists of 32,518 visitor data entries. Model performance is evaluated using Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and Mean Absolute Percentage Error (MAPE). The results show that LSTM achieved the lowest error with an MSE of 8257.23, an RMSE of 90.87, and a MAPE of 12.73%. Therefore, the LSTM model achieved the highest accuracy, while Holt-Winters TES performed better than SARIMA in certain aspects. Visitor predictions can support strategic decision-making and content management
A Web-Based Forecasting Approach to Estimating the Number of Low-Income Households Eligible for Social Food Aid Using Holt’s Double Exponential Smoothing Mukhamad Masrur; Solikhin Solikhin; Muhammad Walid Syahrul Churum; M. Zakki Abdillah; Toni Wijanarko Adi Putra
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol 11 No 2 (2025): July
Publisher : Information Systems - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/register.v11i2.4922

Abstract

This work presents a web-based forecasting methodology for predicting the quantity of low-income households qualified for social food assistance utilizing Holt’s Double Exponential Smoothing (HDES) technique. Precise assessment is crucial for governmental bodies and social welfare organizations to guarantee efficient aid distribution and effective resource allocation. The proposed method amalgamates time series forecasting models with a web-based application to deliver real-time predictions and accessibility for decision-makers. Historical data on low-income household statistics were employed to formulate and authenticate the forecasting model. The findings indicate that HDES delivers dependable short-term predictions with low error rates, accurately reflecting patterns in the data. This online application offers policymakers an effective means for monitoring socio-economic trends and enhancing the responsiveness of social assistance initiatives. This research contributes by integrating statistical forecasting with web-based applications to aid social policy decisions.
Design and Validation of LexiPlay: A Multisensory Game-Based Application for Literacy Learning among Children with Dyslexia Menik Tetha Agustina; Pratama Irwin Talenta; M. Zakki Abdillah
Indonesian Journal of Learning Education and Counseling Vol. 8 No. 2 (2026): March
Publisher : ILIN Institute Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31960/ijolec.v8i2.3325

Abstract

Children with dyslexia often experience difficulties in reading, spelling, and phonological processing, which may hinder their literacy development. Although various educational applications have been developed to support learning, many existing platforms do not sufficiently integrate multisensory learning principles and game-based features that are essential for supporting children with dyslexia. Therefore, this study aims to develop and validate LexiPlay, a multisensory game-based learning application designed to support literacy development among children with dyslexia, and to examine its validity and practicality as a learning medium. This study employed a Research and Development (R&D) approach based on the Borg and Gall model. Data were collected through observation, interviews, and documentation. The development process involved expert validation, instrument validation, individual trials, and small-group trials with students with dyslexia. The collected data were analyzed using both qualitative and quantitative approaches. The results indicate that the LexiPlay application achieved a “highly valid” classification based on expert evaluation and was considered “highly practical” based on limited field testing. The application integrates multisensory learning elements, gamification features, and a dyslexia-friendly interface, which contribute to improving student engagement and supporting early literacy learning. These findings suggest that LexiPlay has strong potential as an innovative digital learning tool to support literacy development in children with dyslexia and provide important implications for special education, inclusive education practices, and the development of evidence-based digital learning interventions.
Co-Authors Abdul Hakim Prima Yuniarto Abdul Razak Naufal Achmad Dimyati Achmad Solechan Agustina, Menik Tetha Ahmad Nugroho Ahmad Nugroho Ahmad Nugroho Al’Amin, M. Astrid Novita Putri, Astrid Cholil, Saifur Rohman Cicilia Yolisday Darmawan, Arya Daroji Daroji Devi Astri Nawangnugraeni Devi Astri Nawangnugraeni Dewi, Mariza Mustika Dimas Benyamin Dwi Prasojo, Nikolas Erba Lutfina Erba Lutfina Felix Surya Sanjaya Keisan Feoder Yufanka Khoirudin Khoirudin Laily Amalia Maria Yuliana Belaon Muhammad Kholilurrahman Muhammad Ramdan Muhammad Walid Syahrul Churum mukhamad masrur NAWANGNUGRAENI, DEVI ASTRI Nugroho, Ahmad Nur Wakhidah Oei Joviano Matthew Wijaya Pranata, Ivan Gautama Suprayitno Pratama Irwin Talenta Rafael Ercole Hermanto ROBY SETIAWAN Sekarlangit Sekarlangit, Sekarlangit Setyo, Victoricky Kurnia Siska Narulita Solikhin Solikhin Solikhin Solikhin Sumantiawan, Dody Indra Suseno, Akrim Teguh Toni Wijanarko Adi Putra Tranhuji Gumbara Widyatun, Diah Wijaya, Tan Steven Yohanes Suhari Yonatan, Christopher Nikolas